328 results on '"Crump JA"'
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2. Global diversity and antimicrobial resistance of typhoid fever pathogens: Insights from a meta-analysis of 13,000 Salmonella Typhi genomes.
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Carey, ME, Dyson, ZA, Ingle, DJ, Amir, A, Aworh, MK, Chattaway, MA, Chew, KL, Crump, JA, Feasey, NA, Howden, BP, Keddy, KH, Maes, M, Parry, CM, Van Puyvelde, S, Webb, HE, Afolayan, AO, Alexander, AP, Anandan, S, Andrews, JR, Ashton, PM, Basnyat, B, Bavdekar, A, Bogoch, II, Clemens, JD, da Silva, KE, De, A, de Ligt, J, Diaz Guevara, PL, Dolecek, C, Dutta, S, Ehlers, MM, Francois Watkins, L, Garrett, DO, Godbole, G, Gordon, MA, Greenhill, AR, Griffin, C, Gupta, M, Hendriksen, RS, Heyderman, RS, Hooda, Y, Hormazabal, JC, Ikhimiukor, OO, Iqbal, J, Jacob, JJ, Jenkins, C, Jinka, DR, John, J, Kang, G, Kanteh, A, Kapil, A, Karkey, A, Kariuki, S, Kingsley, RA, Koshy, RM, Lauer, AC, Levine, MM, Lingegowda, RK, Luby, SP, Mackenzie, GA, Mashe, T, Msefula, C, Mutreja, A, Nagaraj, G, Nagaraj, S, Nair, S, Naseri, TK, Nimarota-Brown, S, Njamkepo, E, Okeke, IN, Perumal, SPB, Pollard, AJ, Pragasam, AK, Qadri, F, Qamar, FN, Rahman, SIA, Rambocus, SD, Rasko, DA, Ray, P, Robins-Browne, R, Rongsen-Chandola, T, Rutanga, JP, Saha, SK, Saha, S, Saigal, K, Sajib, MSI, Seidman, JC, Shakya, J, Shamanna, V, Shastri, J, Shrestha, R, Sia, S, Sikorski, MJ, Singh, A, Smith, AM, Tagg, KA, Tamrakar, D, Tanmoy, AM, Thomas, M, Thomas, MS, Thomsen, R, Thomson, NR, Tupua, S, Vaidya, K, Valcanis, M, Veeraraghavan, B, Weill, F-X, Wright, J, Dougan, G, Argimón, S, Keane, JA, Aanensen, DM, Baker, S, Holt, KE, Global Typhoid Genomics Consortium Group Authorship, Carey, ME, Dyson, ZA, Ingle, DJ, Amir, A, Aworh, MK, Chattaway, MA, Chew, KL, Crump, JA, Feasey, NA, Howden, BP, Keddy, KH, Maes, M, Parry, CM, Van Puyvelde, S, Webb, HE, Afolayan, AO, Alexander, AP, Anandan, S, Andrews, JR, Ashton, PM, Basnyat, B, Bavdekar, A, Bogoch, II, Clemens, JD, da Silva, KE, De, A, de Ligt, J, Diaz Guevara, PL, Dolecek, C, Dutta, S, Ehlers, MM, Francois Watkins, L, Garrett, DO, Godbole, G, Gordon, MA, Greenhill, AR, Griffin, C, Gupta, M, Hendriksen, RS, Heyderman, RS, Hooda, Y, Hormazabal, JC, Ikhimiukor, OO, Iqbal, J, Jacob, JJ, Jenkins, C, Jinka, DR, John, J, Kang, G, Kanteh, A, Kapil, A, Karkey, A, Kariuki, S, Kingsley, RA, Koshy, RM, Lauer, AC, Levine, MM, Lingegowda, RK, Luby, SP, Mackenzie, GA, Mashe, T, Msefula, C, Mutreja, A, Nagaraj, G, Nagaraj, S, Nair, S, Naseri, TK, Nimarota-Brown, S, Njamkepo, E, Okeke, IN, Perumal, SPB, Pollard, AJ, Pragasam, AK, Qadri, F, Qamar, FN, Rahman, SIA, Rambocus, SD, Rasko, DA, Ray, P, Robins-Browne, R, Rongsen-Chandola, T, Rutanga, JP, Saha, SK, Saha, S, Saigal, K, Sajib, MSI, Seidman, JC, Shakya, J, Shamanna, V, Shastri, J, Shrestha, R, Sia, S, Sikorski, MJ, Singh, A, Smith, AM, Tagg, KA, Tamrakar, D, Tanmoy, AM, Thomas, M, Thomas, MS, Thomsen, R, Thomson, NR, Tupua, S, Vaidya, K, Valcanis, M, Veeraraghavan, B, Weill, F-X, Wright, J, Dougan, G, Argimón, S, Keane, JA, Aanensen, DM, Baker, S, Holt, KE, and Global Typhoid Genomics Consortium Group Authorship
- Abstract
BACKGROUND: The Global Typhoid Genomics Consortium was established to bring together the typhoid research community to aggregate and analyse Salmonella enterica serovar Typhi (Typhi) genomic data to inform public health action. This analysis, which marks 22 years since the publication of the first Typhi genome, represents the largest Typhi genome sequence collection to date (n=13,000). METHODS: This is a meta-analysis of global genotype and antimicrobial resistance (AMR) determinants extracted from previously sequenced genome data and analysed using consistent methods implemented in open analysis platforms GenoTyphi and Pathogenwatch. RESULTS: Compared with previous global snapshots, the data highlight that genotype 4.3.1 (H58) has not spread beyond Asia and Eastern/Southern Africa; in other regions, distinct genotypes dominate and have independently evolved AMR. Data gaps remain in many parts of the world, and we show the potential of travel-associated sequences to provide informal 'sentinel' surveillance for such locations. The data indicate that ciprofloxacin non-susceptibility (>1 resistance determinant) is widespread across geographies and genotypes, with high-level ciprofloxacin resistance (≥3 determinants) reaching 20% prevalence in South Asia. Extensively drug-resistant (XDR) typhoid has become dominant in Pakistan (70% in 2020) but has not yet become established elsewhere. Ceftriaxone resistance has emerged in eight non-XDR genotypes, including a ciprofloxacin-resistant lineage (4.3.1.2.1) in India. Azithromycin resistance mutations were detected at low prevalence in South Asia, including in two common ciprofloxacin-resistant genotypes. CONCLUSIONS: The consortium's aim is to encourage continued data sharing and collaboration to monitor the emergence and global spread of AMR Typhi, and to inform decision-making around the introduction of typhoid conjugate vaccines (TCVs) and other prevention and control strategies. FUNDING: No specific funding was awarded f
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- 2023
3. Differences in diagnosis, management, and outcomes of acute febrile illness by health facility level in southern Ethiopia
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Shimelis, T, Vaz Nery, S, Schierhout, G, Tadesse, BT, Dittrich, S, Crump, JA, and Kaldor, JM
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Antimalarials ,Medical research ,Multidisciplinary ,Fever ,Humans ,Infant ,Diseases ,Ethiopia ,Health Facilities ,Signs and symptoms ,Child ,Microbiology ,Malaria - Abstract
We assessed the diagnosis, management and outcomes of acute febrile illness in a cohort of febrile children aged under 5 years presenting at one urban and two rural health centres and one tertiary hospital between 11 August 2019 and 01 November 2019. Pneumonia was diagnosed in 104 (30.8%) of 338 children at health centres and 128 (65.0%) of 197 at the hospital (p
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- 2022
4. Assessment of Rapid Diagnostic Tests for Typhoid Diagnosis and Assessment of Febrile Illness Outbreaks in Fiji
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Strobel, AG, Airs, S, Nguyen, C, Vadei, TR, Matanitobua, S, Kama, M, Watson, CH, Crump, JA, Mulholland, EK, Strugnell, RA, Parry, CM, Strobel, AG, Airs, S, Nguyen, C, Vadei, TR, Matanitobua, S, Kama, M, Watson, CH, Crump, JA, Mulholland, EK, Strugnell, RA, and Parry, CM
- Abstract
Typhoid is an endemic in Fiji with increases observed since the early 2000s and frequent outbreaks reported. We assessed the diagnostic accuracy of currently available typhoid rapid diagnostic tests (RDTs) (TUBEX, Typhidot Rapid, and Test-It assay) to establish their performance against blood culture in Fiji and to examine their suitability for rapid typhoid outbreak identification. The performance of RDTs was assessed in the public health reference laboratory in Suva, Fiji, according to the manufacturers' instructions. A simulation was used to examine the potential use of RDTs for attribution of a febrile illness outbreak to typhoid. For the diagnostic evaluation, 179 patients were included; 49 had blood culture-confirmed typhoid, 76 had fever as a result of non-typhoid etiologies, and 54 were age-matched community controls. The median (interquartile range) age was 29 (20-46) years. Of the participants, 92 (51.4%) were male and 131 (73.2%) were indigenous Fijians. The sensitivities of the tests were 77.6% for TUBEX, 75.5% for Typhidot Rapid, and 57.1% for Test-It assay. The Test-It assay had the highest specificity of 93.4%, followed by Typhidot Rapid 85.5% and TUBEX 60.5%. Typhidot Rapid had the best performance in the simulation for attribution of a febrile illness outbreak to typhoid. Typhoid RDTs performed suboptimally for individual patient diagnosis due to low sensitivity and variable specificity. We demonstrate that RDTs could be useful in the field for rapid attribution of febrile illness outbreaks to typhoid. Typhidot Rapid had the best combination of sensitivity, specificity, positive and negative predictive values, cost, and ease of use for this purpose.
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- 2022
5. Genomic epidemiology of Salmonella Typhi in Central Division, Fiji, 2012 to 2016
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Davies, MR, Duchene, S, Valcanis, M, Jenkins, AP, Jenney, A, Rosa, V, Hayes, AJ, Strobel, AG, McIntyre, L, Lacey, JA, Klemm, EJ, Wong, VK, Sahukhan, A, Thomson, H, Page, A, Hocking, D, Wang, N, Tudravu, L, Rafai, E, Dougan, G, Howden, BP, Crump, JA, Mulholland, K, Strugnell, RA, Davies, MR, Duchene, S, Valcanis, M, Jenkins, AP, Jenney, A, Rosa, V, Hayes, AJ, Strobel, AG, McIntyre, L, Lacey, JA, Klemm, EJ, Wong, VK, Sahukhan, A, Thomson, H, Page, A, Hocking, D, Wang, N, Tudravu, L, Rafai, E, Dougan, G, Howden, BP, Crump, JA, Mulholland, K, and Strugnell, RA
- Abstract
BACKGROUND: Typhoid fever is endemic in some Pacific Island Countries including Fiji and Samoa yet genomic surveillance is not routine in such settings. Previous studies suggested imports of the global H58 clade of Salmonella enterica var Typhi (Salmonella Typhi) contribute to disease in these countries which, given the MDR potential of H58, does not auger well for treatment. The objective of the study was to define the genomic epidemiology of Salmonella Typhi in Fiji. METHODS: Genomic sequencing approaches were implemented to study the distribution of 255 Salmonella Typhi isolates from the Central Division of Fiji. We augmented epidemiological surveillance and Bayesian phylogenomic approaches with a multi-year typhoid case-control study to define geospatial patterns among typhoid cases. FINDINGS: Genomic analyses showed Salmonella Typhi from Fiji resolved into 2 non-H58 genotypes with isolates from the two dominant ethnic groups, the Indigenous (iTaukei) and non-iTaukei genetically indistinguishable. Low rates of international importation of clones was observed and overall, there were very low levels an antibiotic resistance within the endemic Fijian typhoid genotypes. Genomic epidemiological investigations were able to identify previously unlinked case clusters. Bayesian phylodynamic analyses suggested that genomic variation within the larger endemic Salmonella Typhi genotype expanded at discreet times, then contracted. INTERPRETATION: Cyclones and flooding drove 'waves' of typhoid outbreaks in Fiji which, through population aggregation, poor sanitation and water safety, and then mobility of the population, spread clones more widely. Minimal international importations of new typhoid clones suggest that targeted local intervention strategies may be useful in controlling endemic typhoid infection. These findings add to our understanding of typhoid transmission networks in an endemic island country with broad implications, particularly across Pacific Island Countries
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- 2022
6. Tenacious Endemic Typhoid Fever in Samoa
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Sikorski, MJ, Desai, SN, Tupua, S, Thomsen, RE, Han, J, Rambocus, S, Nimarota-Brown, S, Punimata, L, Tusitala, S, Sialeipata, M, Hoffman, SA, Tracy, JK, Higginson, EE, Tennant, SM, Gauld, JS, Klein, DJ, Ballard, SA, Robins-Browne, RM, Dougan, G, Nilles, EJ, Howden, BP, Crump, JA, Naseri, TK, Levine, MM, Sikorski, MJ, Desai, SN, Tupua, S, Thomsen, RE, Han, J, Rambocus, S, Nimarota-Brown, S, Punimata, L, Tusitala, S, Sialeipata, M, Hoffman, SA, Tracy, JK, Higginson, EE, Tennant, SM, Gauld, JS, Klein, DJ, Ballard, SA, Robins-Browne, RM, Dougan, G, Nilles, EJ, Howden, BP, Crump, JA, Naseri, TK, and Levine, MM
- Abstract
BACKGROUND: Typhoid fever has been endemic on the island nation of Samoa (2016 population, 195 979) since the 1960s and has persisted through 2019, despite economic development and improvements in water supply and sanitation. METHODS: Salmonella enterica serovar Typhi isolates from the 2 hospitals with blood culture capability and matched patient demographic and clinical data from January 2008 through December 2019 were analyzed. Denominators to calculate incidence by island, region, and district came from 2011 and 2016 censuses and from 2017-2019 projections from Samoa's Bureau of Statistics. Data were analyzed to describe typhoid case burden and incidence from 2008 to 2019 by time, place, and person. RESULTS: In sum, 53-193 blood culture-confirmed typhoid cases occurred annually from 2008 to 2019, without apparent seasonality. Typhoid incidence was low among children age < 48 months (17.6-27.8/105), rose progressively in ages 5-9 years (54.0/105), 10-19 years (60.7-63.4/105), and 20-34 years (61.0-79.3/105), and then tapered off; 93.6% of cases occurred among Samoans < 50 years of age. Most typhoid cases and the highest incidence occurred in Northwest Upolu, but Apia Urban Area (served by treated water supplies) also exhibited moderate incidence. The proportion of cases from short-cycle versus long-cycle transmission is unknown. Samoan S. Typhi are pansusceptible to traditional first-line antibiotics. Nevertheless, enhanced surveillance in 2019 detected 4 (2.9%) deaths among 140 cases. CONCLUSIONS: Typhoid has been endemic in Samoa in the period 2008-2019. Interventions, including mass vaccination with a Vi-conjugate vaccine coadministered with measles vaccine are planned.
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- 2020
7. Global, regional, and national disability-adjusted life-years (DALYs) for 359 diseases and injuries and healthy life expectancy (HALE) for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Kyu, Hh, Abate, D, Abate, Kh, Abay, Sm, Abbafati, C, Abbasi, N, Abbastabar, H, Abd-Allah, F, Abdela, J, Abdelalim, A, Abdollahpour, I, Abdulkader, Rs, Abebe, M, Abebe, Z, Abil, Oz, Aboyans, V, Abrham, Ar, Abu-Raddad, Lj, Abu-Rmeileh, Nme, Accrombessi, Mmk, Acharya, D, Acharya, P, Ackerman, In, Adamu, Aa, Adebayo, Om, Adekanmbi, V, Ademi, Z, Adetokunboh, Oo, Adib, Mg, Adsuar, Jc, Afanvi, Ka, Afarideh, M, Afshin, A, Agarwal, G, Agesa, Km, Aggarwal, R, Aghayan, Sa, Agrawal, A, Ahmadi, A, Ahmadi, M, Ahmadieh, H, Ahmed, Mb, Ahmed, S, Aichour, An, Aichour, I, Aichour, Mte, Akinyemiju, T, Akseer, N, Al-Aly, Z, Al-Eyadhy, A, Al-Mekhlafi, Hm, Al-Raddadi, Rm, Alahdab, F, Alam, K, Alam, T, Alashi, A, Alavian, Sm, Alene, Ka, Alijanzadeh, M, Alizadeh-Navaei, R, Aljunid, Sm, Alkerwi, A, Alla, F, Allebeck, P, Alonso, J, Alsharif, U, Altirkawi, K, Alvis-Guzman, N, Aminde, Ln, Amini, E, Amiresmaili, M, Ammar, W, Amoako, Ya, Anber, Nh, Andrei, Cl, Androudi, S, Animut, Md, Anjomshoa, M, Ansha, Mg, Antonio, Cat, Anwari, P, Arabloo, J, Aremu, O, Ärnlöv, J, Arora, A, Arora, M, Artaman, A, Aryal, Kk, Asayesh, H, Ataro, Z, Ausloos, M, Avila-Burgos, L, Avokpaho, Efga, Awasthi, A, Ayala, Quintanilla, Ayer, R, Azzopardi, Ps, Babazadeh, A, Badali, H, Balakrishnan, K, Bali, Ag, Banach, M, Banoub, Jam, Barac, A, Barboza, Ma, Barker-Collo, Sl, Bärnighausen, Tw, Barquera, S, Barrero, Lh, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Behzadifar, M, Bekele, Bb, Bekru, Et, Belachew, Ab, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bensenor, Im, Berhane, A, Bernabe, E, Bernstein, Rs, Beuran, M, Beyranvand, T, Bhala, N, Bhatt, S, Bhaumik, S, Bhutta, Za, Biadgo, B, Biehl, Mh, Bijani, A, Bikbov, B, Bilano, V, Bililign, N, Bin, Sayeed, Bisanzio, D, Bjørge, T, Bleyer, A, Bobasa, Em, Bou-Orm, Ir, Boufous, S, Bourne, R, Brady, Oj, Brant, Lc, Brayne, C, Brazinova, A, Breitborde, Njk, Brenner, H, Briant, Ps, Briko, An, Britton, G, Brugha, T, Buchbinder, R, Busse, R, Butt, Za, Cahuana-Hurtado, L, Campuzano, Rincon, Cano, J, Cárdenas, R, Carrero, Jj, Carter, A, Carvalho, F, Castañeda-Orjuela, Ca, Castillo, Rivas, J, Castro, F, Catalá-López, F, Cercy, Km, Cerin, E, Chaiah, Y, Chang, Jc, Charlson, Fj, Chattu, Vk, Chiang, Pp, Chitheer, A, Choi, Jj, Christensen, H, Christopher, Dj, Chung, Sc, Cicuttini, Fm, Cirillo, Massimo, Collado-Mateo, D, Cooper, C, Cortesi, Pa, Cortinovis, M, Cousin, E, Criqui, Mh, Cromwell, Ea, Cross, M, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dandona, L, Dandona, R, Dargan, Pi, Daryani, A, Das, Gupta, Das, R, Neves, J, Dasa, Tt, Davitoiu, Dv, De, La, Hoz, Fp, Leo, De, D, De, Neve, Jw, Steur, De, H, Degefa, Mg, Degenhardt, L, Deiparine, S, Demoz, Gt, Denova-Gutiérrez, E, Deribe, K, Dervenis, N, Des, Jarlais, Dey, S, Dharmaratne, Sd, Dhimal, M, Dinberu, Mt, Dirac, Ma, Djalalinia, S, Doan, L, Dokova, K, Doku, Dt, Dorsey, Er, Doyle, Ke, Driscoll, Tr, Dubey, M, Dubljanin, E, Duken, Ee, Duncan, Bb, Duraes, Ar, Ebrahimi, H, Ebrahimpour, S, Echko, Mm, Edessa, D, Edvardsson, D, Effiong, A, Eggen, Ae, Ehrlich, Jr, Bcheraoui, El, C, El-Khatib, Z, Elyazar, Irf, Enayati, A, Endalifer, Ml, Endries, Ay, Er, B, Erskine, He, Eskandarieh, S, Esteghamati, A, Esteghamati, S, Fakhim, H, Faramarzi, M, Fareed, M, Farhadi, F, Farid, Ta, Farinha, Cses, Farioli, A, Faro, A, Farzadfar, F, Fazaeli, Aa, Feigin, Vl, Fentahun, N, Fereshtehnejad, Sm, Fernandes, E, Fernandes, Jc, Ferrari, Aj, Ferreira, Ml, Filip, I, Fischer, F, Fitzmaurice, C, Foigt, Na, Foreman, Kj, Frank, Td, Fukumoto, T, Fullman, N, Fürst, T, Furtado, Jm, Gakidou, E, Gall, S, Gallus, S, Ganji, M, Garcia-Basteiro, Al, Gardner, Wm, Gebre, Ak, Gebremedhin, At, Gebremichael, Tg, Gelano, Tf, Geleijnse, Jm, Genova-Maleras, R, Geramo, Ycd, Gething, Pw, Gezae, Ke, Ghadami, Mr, Ghadiri, K, Ghasemi-Kasman, M, Ghimire, M, Ghoshal, Ag, Gill, Ps, Gill, Tk, Ginawi, Ia, Giussani, G, Gnedovskaya, Ev, Goldberg, Em, Goli, S, Gómez-Dantés, H, Gona, Pn, Gopalani, Sv, Gorman, Tm, Goulart, Ac, Goulart, Bng, Grada, A, Grosso, G, Gugnani, Hc, Guillemin, F, Guo, Y, Gupta, Pc, Gupta, R, Gupta, T, Gutiérrez, Ra, Gyawali, B, Haagsma, Ja, Hachinski, V, Hafezi-Nejad, N, Haghparast, Bidgoli, Hagos, Tb, Hailegiyorgis, Tt, Haj-Mirzaian, A, Hamadeh, Rr, Hamidi, S, Handal, Aj, Hankey, Gj, Hao, Y, Harb, Hl, Harikrishnan, S, Haririan, H, Haro, Jm, Hassankhani, H, Hassen, Hy, Havmoeller, R, Hay, Rj, Hay, Si, Hedayatizadeh-Omran, A, Heibati, B, Hendrie, D, Henok, A, Heredia-Pi, I, Herteliu, C, Heydarpour, F, Heydarpour, P, Hibstu, Dt, Hoek, Hw, Hoffman, Hj, Hole, Mk, Homaie, Rad, E, Hoogar, P, Hosgood, Hd, Hosseini, Sm, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hotez, Pj, Hoy, Dg, Hsairi, M, Htet, As, Huang, Jj, Iburg, Km, Ikeda, Ct, Ilesanmi, Os, Irvani, Ssn, Irvine, Cms, Islam, Sms, Islami, F, Jacobsen, Kh, Jahangiry, L, Jahanmehr, N, Jain, Sk, Jakovljevic, M, James, Sl, Jayatilleke, Au, Jeemon, P, Jha, Rp, Jha, V, Js, Ji, Johnson, Co, Jonas, Jb, Jonnagaddala, J, Jorjoran, Shushtari, Z, Joshi, A, Jozwiak, Jj, Jungari, Sb, Jürisson, M, Kabir, Z, Kadel, R, Kahsay, A, Kalani, R, Kanchan, T, Kar, C, Karami, M, Karami, Matin, B, Karch, A, Karema, C, Karimi, N, Karimi, Sm, Kasaeian, A, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Kaul, A, Kawakami, N, Kazemi, Z, Karyani, Ak, Keighobadi, Mm, Keiyoro, Pn, Kemmer, L, Kemp, Gr, Kengne, Ap, Keren, A, Khader, Ys, Khafaei, B, Khafaie, Ma, Khajavi, A, Khalid, N, Khalil, Ia, Khan, Ea, Khan, Ms, Khan, Ma, Khang, Yh, Khater, Mm, Khazaei, M, Khoja, At, Khosravi, A, Khosravi, Mh, Kiadaliri, Aa, Kidanemariam, Zt, Kiirithio, Dn, Kim, Ci, Kim, D, Kim, Ye, Kim, Yj, Kimokoti, Rw, Kinfu, Y, Kisa, A, Kissimova-Skarbek, K, Knudsen, Aks, Kocarnik, Jm, Kochhar, S, Kokubo, Y, Kolola, T, Kopec, Ja, Kosen, S, Kotsakis, Ga, Koul, Pa, Koyanagi, A, Krishan, K, Krishnaswami, S, Krohn, Kj, Kuate, Defo, Kucuk, B, Bicer, B, Kumar, Ga, Kumar, M, Kuzin, I, Lad, Dp, Lad, Sd, Lafranconi, A, Lalloo, R, Lallukka, T, Lami, Fh, Lang, Jj, Langan, Sm, Lansingh, Vc, Latifi, A, Lau, Km, Lazarus, Jv, Leasher, Jl, Ledesma, Jr, Lee, Ph, Leigh, J, Leili, M, Leshargie, Ct, Leung, J, Levi, M, Lewycka, S, Li, S, Li, Y, Liang, X, Liao, Y, Liben, Ml, Lim, Ll, Lim, Ss, Limenih, Ma, Linn, S, Liu, S, Looker, Kj, Lopez, Ad, Lorkowski, S, Lotufo, Pa, Lozano, R, Lucas, Tcd, Lunevicius, R, Lyons, Ra, Ma, S, Macarayan, Erk, Mackay, Mt, Maddison, Er, Madotto, F, Maghavani, Dp, Mai, Ht, Majdan, M, Majdzadeh, R, Majeed, A, Malekzadeh, R, Malta, Dc, Mamun, Aa, Manda, Al, Manguerra, H, Mansournia, Ma, Mantilla, Herrera, Mantovani, Lg, Maravilla, Jc, Marcenes, W, Marks, A, Martins-Melo, Fr, Martopullo, I, März, W, Marzan, Mb, Massano, J, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mazidi, M, Mcalinden, C, Mcgrath, Jj, Mckee, M, Mcmahon, Bj, Mehata, S, Mehrotra, R, Mehta, Km, Mehta, V, Mejia-Rodriguez, F, Mekonen, T, Melese, A, Melku, M, Memiah, Ptn, Memish, Za, Mendoza, W, Mengistu, G, Mensah, Ga, Mereta, St, Meretoja, A, Meretoja, Tj, Mestrovic, T, Miazgowski, B, Miazgowski, T, Millear, Ai, Miller, Tr, Mini, Gk, Mirarefin, M, Mirica, A, Mirrakhimov, Em, Misganaw, At, Mitchell, Pb, Mitiku, H, Moazen, B, Mohajer, B, Mohammad, Ka, Mohammadi, M, Mohammadifard, N, Mohammadnia-Afrouzi, M, Mohammed, Ma, Mohammed, S, Mohebi, F, Mokdad, Ah, Molokhia, M, Monasta, L, Montañez, Jc, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Lakeh, M, Moradinazar, M, Moraga, P, Morawska, L, Moreno, Velásquez, I, Morgado-Da-Costa, J, Morrison, Sd, Moschos, Mm, Mousavi, Sm, Mruts, Kb, Muche, Aa, Muchie, Kf, Mueller, Uo, Muhammed, Os, Mukhopadhyay, S, Muller, K, Mumford, Je, Murthy, Gvs, Musa, Ki, Mustafa, G, Nabhan, Af, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Nahvijou, A, Naik, G, Najafi, F, Nam, Hs, Nangia, V, Nansseu, Jr, Neamati, N, Negoi, I, Negoi, Ri, Neupane, S, Newton, Crj, Ngunjiri, Jw, Nguyen, Aq, Nguyen, G, Nguyen, Ht, Nguyen, Hlt, Nguyen, Lh, Nguyen, M, Nguyen, Nb, Nguyen, Sh, Nichols, E, Ningrum, Dna, Nixon, Mr, Nomura, S, Noroozi, M, Norrving, B, Noubiap, Jj, Nouri, Hr, Shiadeh, 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Sanjay, Krohn, Kristopher J, Kuate Defo, Barthelemy, Kucuk Bicer, Burcu, Kumar, G Anil, Kumar, Manasi, Kuzin, Igor, Lad, Deepesh P, Lad, Sheetal D, Lafranconi, Alessandra, Lalloo, Ratilal, Lallukka, Tea, Lami, Faris Hasan, Lang, Justin J, Langan, Sinéad M, Lansingh, Van C, Latifi, Arman, Lau, Kathryn Mei-Ming, Lazarus, Jeffrey V, Leasher, Janet L, Ledesma, Jorge R, Lee, Paul H, Leigh, Jame, Leili, Mostafa, Leshargie, Cheru Tesema, Leung, Janni, Levi, Miriam, Lewycka, Sonia, Li, Shanshan, Li, Yichong, Liang, Xiaofeng, Liao, Yu, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S, Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Looker, Katharine J, Lopez, Alan D, Lorkowski, Stefan, Lotufo, Paulo A, Lozano, Rafael, Lucas, Tim C D, Lunevicius, Raimunda, Lyons, Ronan A, Ma, Stefan, Macarayan, Erlyn Rachelle King, Mackay, Mark T, Maddison, Emilie R, Madotto, Fabiana, Maghavani, Dhaval P, Mai, Hue Thi, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Mamun, Abdullah A, Manda, Ana-Laura, Manguerra, Helena, Mansournia, Mohammad Ali, Mantilla Herrera, Ana Maria, Mantovani, Lorenzo Giovanni, Maravilla, Joemer C, Marcenes, Wagner, Marks, Ashley, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Marzan, Melvin B, Massano, João, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K, Mazidi, Mohsen, McAlinden, Colm, McGrath, John J, McKee, Martin, McMahon, Brian J, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M, Mehta, Varshil, Mejia-Rodriguez, Fabiola, Mekonen, Tesfa, Melese, Addisu, Melku, Mulugeta, Memiah, Peter T N, Memish, Ziad A, Mendoza, Walter, Mengistu, Getnet, Mensah, George A, Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J, Mestrovic, Tomislav, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I, Miller, Ted R, Mini, G.K., Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M, Misganaw, Awoke Temesgen, Mitchell, Philip B, Mitiku, Habtamu, Moazen, Babak, Mohajer, Bahram, Mohammad, Karzan Abdulmuhsin, Mohammadi, Moslem, Mohammadifard, Noushin, Mohammadnia-Afrouzi, Mousa, Mohammed, Mohammed A, Mohammed, Shafiu, Mohebi, Farnam, Mokdad, Ali H, Molokhia, Mariam, Monasta, Lorenzo, Montañez, Julio Cesar, Moosazadeh, Mahmood, Moradi, Ghobad, Moradi, Mahmoudreza, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Moreno Velásquez, Ilai, Morgado-Da-Costa, Joana, Morrison, Shane Dougla, Moschos, Marilita M, Mousavi, Seyyed Meysam, Mruts, Kalayu Brhane, Muche, Achenef Asmamaw, Muchie, Kindie Fentahun, Mueller, Ulrich Otto, Muhammed, Oumer Sada, Mukhopadhyay, Satinath, Muller, Kate, Mumford, John Everett, Murthy, G.V.S., Musa, Kamarul Imran, Mustafa, Ghulam, Nabhan, Ashraf F, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Nahvijou, Azin, Naik, Gurudatta, Najafi, Farid, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Neamati, Nahid, Negoi, Ionut, Negoi, Ruxandra Irina, Neupane, Suba, Newton, Charles Richard Jame, Ngunjiri, Josephine W, Nguyen, Anh Quynh, Nguyen, Grant, Nguyen, Ha Thu, Nguyen, Huong Lan Thi, Nguyen, Huong Thanh, Nguyen, Long Hoang, Nguyen, Minh, Nguyen, Nam Ba, Nguyen, Son Hoang, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nixon, Molly R, Nomura, Shuhei, Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacque, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nsoesie, Elaine O, Nyasulu, Peter S, Odell, Christopher M, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T, Olagunju, Tinuke O, Olivares, Pedro R, Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L, Ong, Sok King, Oren, Eyal, Ortiz, Alberto, Ota, Erika, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa Ojo, P A, Mahesh, Pacella, Rosana, Pakhare, Abhijit P, Pakpour, Amir H, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Eun-Kee, Park, Jame, Parry, Charles D H, Parsian, Hadi, Pasdar, Yahya, Patel, Shanti, Patil, Snehal T, Patle, Ajay, Patton, George C, Paturi, Vishnupriya Rao, Paudel, Deepak, Paulson, Katherine R, Pearce, Neil, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Pham, Hai Quang, Phillips, Michael R, Pigott, David M, Pillay, Julian David, Piradov, Michael A, Pirsaheb, Meghdad, Pishgar, Farhad, Plana-Ripoll, Oleguer, Polinder, Suzanne, Popova, Svetlana, Postma, Maarten J, Pourshams, Akram, Poustchi, Hossein, Prabhakaran, Dorairaj, Prakash, Swayam, Prakash, V., Prasad, Narayan, Purcell, Caroline A, Qorbani, Mostafa, Quistberg, D Alex, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi, Zohreh, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajati, Fatemeh, Ranjan, Prabhat, Rao, Puja C, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Reddy, K Srinath, Reiner, Robert C, Reitsma, Marissa Bettay, Remuzzi, Giuseppe, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio Luiz P, Roberts, Nicholas L S, Robinson, Stephen R, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Roth, Gregory A, Rothenbacher, Dietrich, Rubagotti, Enrico, Sachdev, Perminder S, Sadat, Nafi, Sadeghi, Ehsan, Saeedi Moghaddam, Sahar, Safari, Hosein, Safari, Yahya, Safari-Faramani, Roya, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, Haniye Sadat, Salam, Nasir, Salama, Joseph S, Salamati, Payman, Saleem, Zikria, Salimi, Yahya, Salimzadeh, Hamideh, Salomon, Joshua A, Salvi, Sundeep Santosh, Salz, Inbal, Samy, Abdallah M, Sanabria, Juan, Sanchez-Niño, Maria Dolore, Santomauro, Damian Francesco, Santos, Itamar S, Santos, João Vasco, Santric Milicevic, Milena M, Sao Jose, Bruno Piassi, Sardana, Mayank, Sarker, Abdur Razzaque, Sarmiento-Suárez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R, Sawhney, Monika, Saxena, Sonia, Schaeffner, Elke, Schmidt, Maria Inê, Schneider, Ione J C, Schutte, Aletta Elisabeth, Schwebel, David C, Schwendicke, Falk, Scott, James G, Sekerija, Mario, Sepanlou, Sadaf G, Serván-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A, Shaikh, Masood Ali, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Sharafi, Heidar, Sharafi, Kiomar, Sharif, Mehdi, Sharif-Alhoseini, Mahdi, Sharma, Jayendra, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shibuya, Kenji, Shiferaw, Mekonnen Sisay, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokoohinia, Yalda, Shokraneh, Farhad, Shoman, Haitham, Shrime, Mark G, Si, Si, Siabani, Soraya, Sibai, Abla Mehio, Siddiqi, Tariq J, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Silva, João Pedro, Silveira, Dayane Gabriele Alve, Singam, Narayana Sarma Venkata, Singh, Jasvinder A, Singh, Narinder Pal, Singh, Virendra, Sinha, Dhirendra Narain, Skiadaresi, Eirini, Skirbekk, Vegard, Sliwa, Karen, Smith, David L, Smith, Mari, Soares Filho, Adauto Martin, Sobaih, Badr Hasan, Sobhani, Soheila, Soofi, Moslem, Sorensen, Reed J D, Soyiri, Ireneous N, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Srinivasan, Vinay, Stanaway, Jeffrey D, Starodubov, Vladimir I, Stein, Dan J, Steiner, Caitlyn, Steiner, Timothy J, Stokes, Mark A, Stovner, Lars Jacob, Subart, Michelle L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Sulo, Gerhard, Sunguya, Bruno F, Sur, Patrick John, Sykes, Bryan L, Sylaja, P.N., Sylte, Dillon O, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Tandon, Nikhil, Tassew, Segen Gebremeskel, Tavakkoli, Mohammad, Taveira, Nuno, Taylor, Hugh R, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekelemedhin, Shishay Wahdey, Tekle, Merhawi Gebremedhin, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Tessema, Belay, Teweldemedhin, Mebrahtu, Thankappan, Kavumpurathu Raman, Theis, Andrew, Thirunavukkarasu, Sathish, Thomas, Nihal, Tilahun, Binyam, To, Quyen G, Tonelli, Marcello, Topor-Madry, Roman, Torre, Anna E, Tortajada-Girbés, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Troeger, Christopher E, Tsadik, Afewerki Gebremeskel, Tsoi, Derrick, Tudor Car, Lorainne, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Undurraga, Eduardo A, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Williams, Hywel C, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zandian, Hamed, Zar, Heather J, Zenebe, Zerihun Menlkalew, Zhou, Maigeng, Zipkin, Ben, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna, and Murray, Christopher J L
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Male ,Health Status ,health statu ,HALE ,mortality rate ,communicable disease ,DALYs ,Global Burden of Disease ,Risk Factors ,Prevalence ,Medicine and Health Sciences ,Singapore ,OUTCOMES ,disability-adjusted life year ,international cooperation ,Medicine (all) ,11 Medical And Health Sciences ,Central African Republic ,newborn disease ,IRON-DEFICIENCY ,AIDS ,priority journal ,Bahrain ,disease severity ,Female ,Quality-Adjusted Life Years ,cerebrovascular accident ,Ukraine ,Life Sciences & Biomedicine ,INTERVENTIONS ,Slovakia ,DISORDERS ,Burundi ,WEIGHTS ,GBD 2017 DALYs and HALE Collaborators ,Communicable Diseases ,Article ,STYLE ,Medicine, General & Internal ,Life Expectancy ,General & Internal Medicine ,Humans ,Disabled Persons ,human ,Healthy Lifestyle ,HALE, DALYs, global burden of disease ,Mortality ,Aged ,Science & Technology ,Mortality, Premature ,HIV ,ischemic heart disease ,major clinical study ,PREVENTION ,non communicable disease ,GBD, disability-adjusted life-years ,age ,sex factor ,Socioeconomic Factors ,Algeria ,Federation of Bosnia and Herzegovina ,lower respiratory tract infection ,Wounds and Injuries ,GENDER ,Human medicine ,trend study ,chronic obstructive lung disease - Abstract
Background How long one lives, how many years of life are spent in good and poor health, and how the population's state of health and leading causes of disability change over time all have implications for policy, planning, and provision of services. We comparatively assessed the patterns and trends of healthy life expectancy (HALE), which quantifies the number of years of life expected to be lived in good health, and the complementary measure of disability-adjusted life years (DALYs), a composite measure of disease burden capturing both premature mortality and prevalence and severity of ill health, for 359 diseases and injuries for 195 countries and territories over the past 28 years. Methods We used data for age-specific mortality rates, years of life lost (YLLs) due to premature mortality, and years lived with disability (YLDs) from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 to calculate HALE and DALYs from 1990 to 2017. We calculated HALE using age-specific mortality rates and YLDs per capita for each location, age, sex, and year. We calculated DALYs for 359 causes as the sum of YLLs and YLDs. We assessed how observed HALE and DALYs differed by country and sex from expected trends based on Sociodemographic Index (SDI). We also analysed HALE by decomposing years of life gained into years spent in good health and in poor health, between 1990 and 2017, and extra years lived by females compared with males. Findings Globally, from 1990 to 2017, life expectancy at birth increased by 7.4 years (95% uncertainty interval 74-7.8), from 65.6 years (65.3-65- 8) in 1990 to 73.0 years (72.7-73.3) in 2017. The increase in years of life varied from 5.1 years (5.0-5.3) in high SDI countries to 12.0 years (11.3-12.8) in low SDI countries. Of the additional years of life expected at birth, 26.3% (20.1-33.1) were expected to be spent in poor health in high SDI countries compared with 11.7% (8.8-15.1) in low-middle SDI countries. HALE at birth increased by 6.3 years (5.9-6.7), from 57.0 years (54.6-59.1) in 1990 to 63.3 years (60.5-65.7) in 2017. The increase varied from 3.8 years (3.4-4.1) in high SDI countries to 10.5 years (9.8-11.2) in low SDI countries. Even larger variations in HALE than these were observed between countries, ranging from 1.0 year (0.4-1.7) in Saint Vincent and the Grenadines (62.4 years [59.9-64.7] in 1990 to 63.5 years [60.9-65.8] in 2017) to 23.7 years (21.9-25.6) in Eritrea (30.7 years [28.9-32.2] in 1990 to 54.4 years [51.5-57.1] in 2017). In most countries, the increase in HALE was smaller than the increase in overall life expectancy, indicating more years lived in poor health. In 180 of 195 countries and territories, females were expected to live longer than males in 2017, with extra years lived varying from 1.4 years (0.6-2.3) in Algeria to 11.9 years (10.9-12.9) in Ukraine. Of the extra years gained, the proportion spent in poor health varied largely across countries, with less than 20% of additional years spent in poor health in Bosnia and Herzegovina, Burundi, and Slovakia, whereas in Bahrain all the extra years were spent in poor health. In 2017, the highest estimate of HALE at birth was in Singapore for both females (75.8 years [72.4-78.7]) and males (72.6 years [69 " 8-75.0]) and the lowest estimates were in Central African Republic (47.0 years [43.7-50.2] for females and 42.8 years [40.1-45.6] for males). Globally, in 2017, the five leading causes of DALYs were neonatal disorders, ischaemic heart disease, stroke, lower respiratory infections, and chronic obstructive pulmonary disease. Between 1990 and 2017, age-standardised DALY rates decreased by 41.3% (38.8-43.5) for communicable diseases and by 49"8% (47.9-51.6) for neonatal disorders. For non-communicable diseases, global DALYs increased by 40.1% (36.8-43.0), although age-standardised DALY rates decreased by 18.1% (16.0-20.2). Interpretation With increasing life expectancy in most countries, the question of whether the additional years of life gained are spent in good health or poor health has been increasingly relevant because of the potential policy implications, such as health-care provisions and extending retirement ages. In some locations, a large proportion of those additional years are spent in poor health. Large inequalities in HALE and disease burden exist across countries in different SDI quintiles and between sexes. The burden of disabling conditions has serious implications for health system planning and health-related expenditures. Despite the progress made in reducing the burden of communicable diseases and neonatal disorders in low S DI countries, the speed of this progress could be increased by scaling up proven interventions. The global trends among non-communicable diseases indicate that more effort is needed to maximise HALE, such as risk prevention and attention to upstream determinants of health. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
8. A retrospective study of patients with blood culture-confirmed typhoid fever in Fiji during 2014-2015: epidemiology, clinical features, treatment and outcome
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Getahun, A, Parry, CM, Crump, JA, Rosa, V, Jenney, A, Naidu, R, Mulholland, K, Strugnell, RA, Getahun, A, Parry, CM, Crump, JA, Rosa, V, Jenney, A, Naidu, R, Mulholland, K, and Strugnell, RA
- Abstract
BACKGROUND: Typhoid fever is endemic in Fiji. We sought to describe the epidemiology, clinical features and case fatality risk of blood culture-confirmed typhoid fever from January 2014 through December 2015. METHODS: Blood culture-positive patients were identified from a typhoid surveillance line list. A standardised case investigation form was used to record data from patients' medical records. RESULTS: Of 542 patients, 518 (95.6%) were indigenous Fijians (iTaukei) and 285 (52.6%) were male. The median (IQR) age was 25 (16-38) y. Mean (SD) time from the onset of illness to admission was 11.1 (6.9) d. Of 365 patients with clinical information, 346 (96.9%) had fever, 239 (66.9%) diarrhoea, 113 (33.5%) vomiting, and 72 (30.2%) abdominal pain. There were 40 (11.0%) patients with complications, including 17 (4.7%) with shock, and 11 (3.0%) with hepatitis. Nine patients died for a case fatality risk of 1.7%. Of the 544 Salmonella Typhi isolates tested, none were resistant to first line antimicrobials; 3(0.8%) were resistant to ciprofloxacin and 5(1.4%) to nalidixic acid. CONCLUSIONS: In Fiji, most blood culture-confirmed typhoid fever cases were in young adults. Common clinical manifestations were fever and gastrointestinal symptoms. Further studies are required to elucidate the factors associated with complications and death.
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- 2019
9. The global burden of typhoid and paratyphoid fevers: a systematic analysis for the Global Burden of Disease Study 2017
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Stanaway, JD, Reiner, RC, Blacker, BF, Goldberg, EM, Khalil, IA, Troeger, CE, Andrews, JR, Bhutta, ZA, Crump, JA, Im, J, Marks, F, Mintz, E, Park, SE, Zaidi, AKM, Abebe, Z, Abejie, AN, Adedeji, IA, Ali, BA, Amare, AT, Atalay, HT, Avokpaho, EFGA, Bacha, U, Barac, A, Bedi, N, Berhane, A, Browne, AJ, Chirinos, JL, Chitheer, A, Dolecek, C, Zaki, MES, Eshrati, B, Foreman, KJ, Gemechu, A, Gupta, R, Hailu, GB, Henok, A, Hibstu, DT, Chi, LH, Ilesanmi, OS, Iyer, VJ, Kahsay, A, Kasaeian, A, Kassa, TD, Khan, EA, Khang, Y-H, El Razek, HMA, Melku, M, Mengistu, DT, Mohammad, KA, Mohammed, S, Mokdad, AH, Nachega, JB, Naheed, A, Cuong, TN, Huong, LTN, Long, HN, Nam, BN, Trang, HN, Nirayo, YL, Pangestu, T, Patton, GC, Qorbani, M, Rai, RK, Rana, SM, Ranabhat, CL, Roba, KT, Roberts, NLS, Rubino, S, Safiri, S, Sartorius, B, Sawhney, M, Shiferaw, MS, Smith, DL, Sykes, BL, Bach, XT, Tung, TT, Ukwaja, KN, Giang, TV, Linh, GV, Weldegebreal, F, Yenit, MK, Murray, CJL, Hay, SI, Stanaway, JD, Reiner, RC, Blacker, BF, Goldberg, EM, Khalil, IA, Troeger, CE, Andrews, JR, Bhutta, ZA, Crump, JA, Im, J, Marks, F, Mintz, E, Park, SE, Zaidi, AKM, Abebe, Z, Abejie, AN, Adedeji, IA, Ali, BA, Amare, AT, Atalay, HT, Avokpaho, EFGA, Bacha, U, Barac, A, Bedi, N, Berhane, A, Browne, AJ, Chirinos, JL, Chitheer, A, Dolecek, C, Zaki, MES, Eshrati, B, Foreman, KJ, Gemechu, A, Gupta, R, Hailu, GB, Henok, A, Hibstu, DT, Chi, LH, Ilesanmi, OS, Iyer, VJ, Kahsay, A, Kasaeian, A, Kassa, TD, Khan, EA, Khang, Y-H, El Razek, HMA, Melku, M, Mengistu, DT, Mohammad, KA, Mohammed, S, Mokdad, AH, Nachega, JB, Naheed, A, Cuong, TN, Huong, LTN, Long, HN, Nam, BN, Trang, HN, Nirayo, YL, Pangestu, T, Patton, GC, Qorbani, M, Rai, RK, Rana, SM, Ranabhat, CL, Roba, KT, Roberts, NLS, Rubino, S, Safiri, S, Sartorius, B, Sawhney, M, Shiferaw, MS, Smith, DL, Sykes, BL, Bach, XT, Tung, TT, Ukwaja, KN, Giang, TV, Linh, GV, Weldegebreal, F, Yenit, MK, Murray, CJL, and Hay, SI
- Abstract
BACKGROUND: Efforts to quantify the global burden of enteric fever are valuable for understanding the health lost and the large-scale spatial distribution of the disease. We present the estimates of typhoid and paratyphoid fever burden from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017, and the approach taken to produce them. METHODS: For this systematic analysis we broke down the relative contributions of typhoid and paratyphoid fevers by country, year, and age, and analysed trends in incidence and mortality. We modelled the combined incidence of typhoid and paratyphoid fevers and split these total cases proportionally between typhoid and paratyphoid fevers using aetiological proportion models. We estimated deaths using vital registration data for countries with sufficiently high data completeness and using a natural history approach for other locations. We also estimated disability-adjusted life-years (DALYs) for typhoid and paratyphoid fevers. FINDINGS: Globally, 14·3 million (95% uncertainty interval [UI] 12·5-16·3) cases of typhoid and paratyphoid fevers occurred in 2017, a 44·6% (42·2-47·0) decline from 25·9 million (22·0-29·9) in 1990. Age-standardised incidence rates declined by 54·9% (53·4-56·5), from 439·2 (376·7-507·7) per 100 000 person-years in 1990, to 197·8 (172·0-226·2) per 100 000 person-years in 2017. In 2017, Salmonella enterica serotype Typhi caused 76·3% (71·8-80·5) of cases of enteric fever. We estimated a global case fatality of 0·95% (0·54-1·53) in 2017, with higher case fatality estimates among children and older adults, and among those living in lower-income countries. We therefore estimated 135·9 thousand (76·9-218·9) deaths from typhoid and paratyphoid fever globally in 2017, a 41·0% (33·6-48·3) decline from 230·5 thousand (131·2-372·6) in 1990. Overall, typhoid and paratyphoid fevers were responsible for 9·8 million (5·6-15·8) DALYs in 2017, down 43·0% (35·5-50·6) from 17·2 million (9·9-27·8) DALYs in 1990. I
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- 2019
10. Increasing incidence of invasive nontyphoidal Salmonella infections in Queensland, Australia, 2007-2016
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Darton, TC, Parisi, A, Crump, JA, Stafford, R, Glass, K, Howden, BP, Kirk, MD, Darton, TC, Parisi, A, Crump, JA, Stafford, R, Glass, K, Howden, BP, and Kirk, MD
- Abstract
Nontyphoidal Salmonella is a major contributor to the global burden of foodborne disease, with invasive infections contributing substantially to illnesses and deaths. We analyzed notifiable disease surveillance data for invasive nontyphoidal Salmonella disease (iNTS) in Queensland, Australia. We used Poisson regression to estimate incidence rate ratios by gender, age group, and geographical area over 2007-2016. There were 995 iNTS cases, with 945 (92%) confirmed by blood culture. Salmonella Virchow accounted for 254 (25%) of 1,001 unique iNTS isolates. Invasive NTS disease notification rates peaked among infants, during the summer months, and in outback Queensland where the notification rate (95% CI) was 17.3 (14.5-20.1) cases per 100,000 population. Overall, there was a 6,5% annual increase (p<0.001) in iNTS disease incidence. In conclusion, high iNTS rates among males, infants, and the elderly require investigation of household level risk factors for NTS infection. Controlling Salmonella Virchow infections is a public health priority.
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- 2019
11. Environmental Foundations of Typhoid Fever in the Fijian Residential Setting
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Jenkins, AP, Jupiter, SD, Jenney, A, Rosa, V, Naucukidi, A, Prasad, N, Vosaki, G, Mulholland, K, Strugnell, R, Kama, M, Crump, JA, Horwitz, P, Jenkins, AP, Jupiter, SD, Jenney, A, Rosa, V, Naucukidi, A, Prasad, N, Vosaki, G, Mulholland, K, Strugnell, R, Kama, M, Crump, JA, and Horwitz, P
- Abstract
Proximal characteristics and conditions in the residential setting deserve greater attention for their potential to influence typhoid transmission. Using a case-control design in Central Division, Republic of Fiji, we examined bacterial (coliform and Escherichia coli) contamination and chemical composition of water and soil as potential vehicles of exposure to Salmonella Typhi, combining observational analysis of residential living conditions, geospatial analysis of household locations, and factor analysis to explore multivariate associations with the risk of developing typhoid fever. Factors positively associated with typhoid infection related to drainage [phosphate (OR 4.235, p = 0.042) and E. coli concentrations (OR 2.248, p = 0.029) in toilet drainage soil, housing [external condition (OR 3.712, p < 0.001)], drinking water contamination (OR 2.732, p = 0.003) and sanitary condition (OR 1.973, p = 0.031). These five factors explained 42.5% of the cumulative variance and were significant in predicting typhoid infection. Our results support the hypothesis that a combination of spatial and biophysical attributes of the residential setting influence the probability of typhoid transmission; in this study, factors associated with poor drainage, flooding, and sanitary condition increase local exposure to contaminated water and soil, and thereby infection. These findings extend testing of causal assumptions beyond the immediate domestic domain, enhance the scope of traditional case control epidemiology and allow greater specificity of interventions at the scale of the residential setting.
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- 2019
12. The phylogeography and incidence of multi-drug resistant typhoid fever in sub-Saharan Africa
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Park, SE, Pham, DT, Boinett, C, Wong, VK, Pak, GD, Panzner, U, Espinoza, LMC, Von Kalckreuth, V, Im, J, Schütt-Gerowitt, H, Crump, JA, Breiman, RF, Adu-Sarkodie, Y, Owusu-Dabo, E, Rakotozandrindrainy, R, Soura, AB, Aseffa, A, Gasmelseed, N, Keddy, KH, May, J, Sow, AG, Aaby, P, Biggs, HM, Hertz, JT, Montgomery, JM, Cosmas, L, Olack, B, Fields, B, Sarpong, N, Razafindrabe, TJL, Raminosoa, TM, Kabore, LP, Sampo, E, Teferi, M, Yeshitela, B, Tayeb, MA, Sooka, A, Meyer, CG, Krumkamp, R, Dekker, DM, Jaeger, A, Poppert, S, Tall, A, Niang, A, Bjerregaard-Andersen, M, Løfberg, SV, Seo, HJ, Jeon, HJ, Deerin, JF, Park, J, Konings, F, Ali, M, Clemens, JD, Hughes, P, Sendagala, JN, Vudriko, T, Downing, R, Ikumapayi, UN, Mackenzie, GA, Obaro, S, Argimon, S, Aanensen, DM, Page, A, Keane, JA, Duchene, S, Dyson, Z, Holt, KE, Dougan, G, Marks, F, Baker, S, Park, Se Eun [0000-0002-1632-3045], Aseffa, Abraham [0000-0002-8028-1150], May, Jürgen [0000-0001-7831-8420], Ali, Mohammad [0000-0003-1410-388X], Dyson, Zoe [0000-0002-8887-3492], Holt, Kathryn E [0000-0003-3949-2471], Marks, Florian [0000-0002-6043-7170], and Apollo - University of Cambridge Repository
- Subjects
Genotype ,Science ,Incidence ,Genetic Variation ,Salmonella typhi ,bacterial infections and mycoses ,complex mixtures ,Article ,Anti-Bacterial Agents ,Phylogeography ,Drug Resistance, Multiple, Bacterial ,Salmonella Infections ,parasitic diseases ,Humans ,lcsh:Q ,Typhoid Fever ,lcsh:Science ,Africa South of the Sahara ,Phylogeny - Abstract
There is paucity of data regarding the geographical distribution, incidence, and phylogenetics of multi-drug resistant (MDR) Salmonella Typhi in sub-Saharan Africa. Here we present a phylogenetic reconstruction of whole genome sequenced 249 contemporaneous S. Typhi isolated between 2008-2015 in 11 sub-Saharan African countries, in context of the 2,057 global S. Typhi genomic framework. Despite the broad genetic diversity, the majority of organisms (225/249; 90%) belong to only three genotypes, 4.3.1 (H58) (99/249; 40%), 3.1.1 (97/249; 39%), and 2.3.2 (29/249; 12%). Genotypes 4.3.1 and 3.1.1 are confined within East and West Africa, respectively. MDR phenotype is found in over 50% of organisms restricted within these dominant genotypes. High incidences of MDR S. Typhi are calculated in locations with a high burden of typhoid, specifically in children aged, Typhoid fever is caused by the bacterium Salmonella Typhi. Here, Park et al. analyse the genomes of 249 S. Typhi isolates from 11 sub-Saharan African countries, identifying genes and plasmids associated with antibiotic resistance and showing that multi-drug resistance is highly pervasive in sub-Saharan Africa.
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- 2018
13. Epidemiology and risk factors for typhoid fever in Central Division, Fiji, 2014-2017: A case-control study
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Feasey, N, Prasad, N, Jenkins, AP, Naucukidi, L, Rosa, V, Sahu-Khan, A, Kama, M, Jenkins, KM, Jenney, AWJ, Jack, SJ, Saha, D, Horwitz, P, Jupiter, SD, Strugnell, RA, Mulholland, EK, Crump, JA, Feasey, N, Prasad, N, Jenkins, AP, Naucukidi, L, Rosa, V, Sahu-Khan, A, Kama, M, Jenkins, KM, Jenney, AWJ, Jack, SJ, Saha, D, Horwitz, P, Jupiter, SD, Strugnell, RA, Mulholland, EK, and Crump, JA
- Abstract
BACKGROUND: Typhoid fever is endemic in Fiji, with high reported annual incidence. We sought to identify the sources and modes of transmission of typhoid fever in Fiji with the aim to inform disease control. METHODOLOGY/PRINCIPAL FINDINGS: We identified and surveyed patients with blood culture-confirmed typhoid fever from January 2014 through January 2017. For each typhoid fever case we matched two controls by age interval, gender, ethnicity, and residential area. Univariable and multivariable analysis were used to evaluate associations between exposures and risk for typhoid fever. We enrolled 175 patients with typhoid fever and 349 controls. Of the cases, the median (range) age was 29 (2-67) years, 86 (49%) were male, and 84 (48%) lived in a rural area. On multivariable analysis, interrupted water availability (odds ratio [OR] = 2.17; 95% confidence interval [CI] 1.18-4.00), drinking surface water in the last 2 weeks (OR = 3.61; 95% CI 1.44-9.06), eating unwashed produce (OR = 2.69; 95% CI 1.48-4.91), and having an unimproved or damaged sanitation facility (OR = 4.30; 95% CI 1.14-16.21) were significantly associated with typhoid fever. Frequent handwashing after defecating (OR = 0.57; 95% CI 0.35-0.93) and using soap for handwashing (OR = 0.61; 95% CI 0.37-0.95) were independently associated with a lower odds of typhoid fever. CONCLUSIONS: Poor sanitation facilities appear to be a major source of Salmonella Typhi in Fiji, with transmission by drinking contaminated surface water and consuming unwashed produce. Improved sanitation facilities and protection of surface water sources and produce from contamination by human feces are likely to contribute to typhoid control in Fiji.
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- 2018
14. Global, regional, and national incidence, prevalence, and years lived with disability for 301 acute and chronic diseases and injuries in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013
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Vos, T, Barber, Rm, Bell, B, Bertozzi Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie, E, Liang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu, Ozgoren, A, Abd Allah, F, Abdel, Aziz, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu Raddad, Lj, Abu Rmeileh, Nm, Aburto, Tc, Achoki, T, Ackerman, In, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Khabouri, Al, Alam, Ss, Alasfoor, D, Albittar, Mi, Alegretti, Ma, Aleman, Av, Alemu, Za, Alfonso Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis, Guzman, Ameli, N, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, Vs, Artaman, A, Asghar, Rj, Assadi, R, Atkins, Ls, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker Collo, Sl, Barquera, S, Barregard, L, Barrero, Lh, Basu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene, Tj, Bhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin, Abdulhak, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora, Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown, J, Brugha, Ts, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos, Nonato, Campuzano, Ir, Carapetis, Jc, Carpenter, Do, Caso, V, Castaneda Orjuela, Ca, Catala Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, Ss, Cirillo, Massimo, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper, Lt, Cooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, La, De, Cruz, Gongora, De, V, Vega, La, De, Sf, Leo, D, Del, Pozo, Cruz, Dellavalle, Rp, Deribe, K, Derrett, S, Des, Jarlais, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad, Sm, Fernandes, Jg, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia, Guerra, Geleijnse, Fa, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez, De, Cosio, T, Gosselin, Ra, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi Nejad, N, Hagan, H, Halasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia, Pi, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang, Jj, Huang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang, Y, Jonas, Jb, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, Ds, Kemp, Ah, Kengne, Ap, Khader, Ys, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto, M, Knibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate, Defo, Kucuk, B, Bicer, B, Kuipers, Ej, Kulkarni, Vs, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett, Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez Olmedo, N, Lortet Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay, Mt, Majdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason Jones, Aj, Matzopoulos, Rg, Mayosi, Bm, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt, Te, Mohamed, Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori, R, Moschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, Ks, Naghavi, P, Nahas, Z, Naheed, A, Naidoo, Ks, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni, Fn, Nhung, Nt, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Ih, Oh, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian, Jd, Panelo, Ci, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, Ls, Pellegrini, Ca, Pereira, Dm, Perez Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk, Gv, Polinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, D, Prasad, Nm, Qato, D, Quistberg, Da, Rafay, A, Rahimi, K, Rahimi Movaghar, V, Rahman, Su, Raju, M, Rakovac, I, Rana, Sm, Razavi, H, Refaat, A, Rehm, J, Remuzzi, G, Resnikoff, S, Ribeiro, Al, Riccio, Pm, Richardson, L, Richardus, Jh, Riederer, Am, Robinson, M, Roca, A, Rodriguez, A, Rojas Rueda, D, Ronfani, L, Rothenbacher, D, Roy, N, Ruhago, Gm, Sabin, N, Sacco, Rl, Ksoreide, K, Saha, S, Sahathevan, R, Sahraian, Ma, Sampson, U, Sanabria, Jr, Sanchez Riera, L, Santos, Is, Satpathy, M, Saunders, Je, Sawhney, M, Saylan, Mi, Scarborough, P, Schoettker, B, Schneider, Ij, Schwebel, Dc, Scott, Jg, Seedat, S, Sepanlou, Sg, Serdar, B, Servan Mori, Ee, Shackelford, K, Shaheen, A, Shahraz, S, Shamah, Levy, T, Shangguan, S, She, J, Sheikhbahaei, S, Shepard, Ds, Shi, P, Shibuya, K, Shinohara, Y, Shiri, R, Shishani, K, Shiue, I, Shrime, Mg, Sigfusdottir, Id, Silberberg, Dh, Simard, Ep, Sindi, S, Singh, Ja, Singh, L, Skirbekk, V, Sliwa, K, Soljak, M, Soneji, S, Soshnikov, Ss, Speyer, P, Sposato, La, Sreeramareddy, Ct, Stoeckl, H, Stathopoulou, Vk, Steckling, N, Stein, Mb, Stein, Dj, Steiner, Tj, Stewart, A, Stork, E, Stovner, Lj, Stroumpoulis, K, Sturua, L, Sunguya, Bf, Swaroop, M, Sykes, Bl, Tabb, Km, Takahashi, K, Tan, F, Tandon, N, Tanne, D, Tanner, M, Tavakkoli, M, Taylor, Hr, Ao, Te, Temesgen, Am, Ten, Have, M, Tenkorang, Ey, Terkawi, As, Theadom, Am, Thomas, E, Thorne Lyman, Al, Thrift, Ag, Tleyjeh, Im, Tonelli, M, Topouzis, F, Towbin, Ja, Toyoshima, H, Traebert, J, Tran, Bx, Trasande, L, Trillini, M, Truelsen, T, Trujillo, U, Tsilimbaris, M, Tuzcu, Em, Ukwaja, Kn, Undurraga, Ea, Uzun, Sb, Van, Brakel, Van, Wh, Vijver, De, Van, S, Dingenen, R, Van, Gool, Varakin, Yy, Vasankari, Tj, Vavilala, Ms, Veerman, Lj, Velasquez, Melendez, G, Venketasubramanian, N, Vijayakumar, L, Villalpando, S, Violante, Fs, Vlassov, Vv, Waller, S, Wallin, Mt, Wan, X, Wang, L, Wang, J, Wang, Y, Warouw, Ts, Weichenthal, S, Weiderpass, E, Weintraub, Rg, Werdecker, A, Wessells, Kr, Westerman, R, Wilkinson, Jd, Williams, Hc, Williams, Tn, Woldeyohannes, Sm, Wolfe, Cd, Wong, Jq, Wong, H, Woolf, Ad, Wright, Jl, Wurtz, B, Xu, G, Yang, G, Yano, Y, Yenesew, Ma, Yentur, Gk, Yip, P, Yonemoto, N, Yoon, Sj, Younis, M, Yu, C, Kim, Ky, Zaki, Mel, Zhang, Y, Zhao, Z, Zhao, Y, Zhu, J, Zonies, D, Zunt, Jr, Salomon, Ja, Murray, C. J., Vos, T, Barber, Rm, Bell, B, Bertozzi-Villa, A, Biryukov, S, Bolliger, I, Charlson, F, Davis, A, Degenhardt, L, Dicker, D, Duan, L, Erskine, H, Feigin, Vl, Ferrari, Aj, Fitzmaurice, C, Fleming, T, Graetz, N, Guinovart, C, Haagsma, J, Hansen, Gm, Hanson, Sw, Heuton, Kr, Higashi, H, Kassebaum, N, Kyu, H, Laurie ELiang, X, Lofgren, K, Lozano, R, Macintyre, Mf, Moradi-Lakeh, M, Naghavi, M, Nguyen, G, Odell, S, Ortblad, K, Roberts, Da, Roth, Ga, Sandar, L, Serina, Pt, Stanaway, Jd, Steiner, C, Thomas, B, Vollset, Se, Whiteford, H, Wolock, Tm, Ye, P, Zhou, M, Ãvila, Ma, Aasvang, Gm, Abbafati, C, Abbasoglu Ozgoren, A, Abd-Allah, F, Abdel Aziz MI, Abera, Sf, Aboyans, V, Abraham, Jp, Abraham, B, Abubakar, I, Abu-Raddad, Lj, Abu-Rmeileh, Nm, Aburto, Tc, Achoki TAckerman IN, Adelekan, A, Ademi, Z, Adou, Ak, Adsuar, Jc, Arnlov, J, Agardh, Ee, Al Khabouri MJ, Alam, S, Alasfoor, D, Albittar, Mi, Alegretti MAAleman AV, Alemu, Za, Alfonso-Cristancho, R, Alhabib, S, Ali, R, Alla, F, Allebeck, P, Allen, Pj, Almazroa, Ma, Alsharif, U, Alvarez, E, Alvis-Guzman NAmeli, O, Amini, H, Ammar, W, Anderson, Bo, Anderson, Hr, Antonio, Ca, Anwari, P, Apfel, H, Arsenijevic, V, Artaman, A, Asghar, Rj, Assadi, R, Atkins, L, Atkinson, C, Badawi, A, Bahit, Mc, Bakfalouni, T, Balakrishnan, K, Balalla, S, Banerjee, A, Barker-Collo, Sl, Barquera, S, Barregard, L, Barrero LHBasu, S, Basu, A, Baxter, A, Beardsley, J, Bedi, N, Beghi, E, Bekele, T, Bell, Ml, Benjet, C, Bennett, Da, Bensenor, Im, Benzian, H, Bernabe, E, Beyene TJBhala, N, Bhalla, A, Bhutta, Z, Bienhoff, K, Bikbov, B, Bin Abdulhak, A, Blore, Jd, Blyth, Fm, Bohensky, Ma, Bora Basara, B, Borges, G, Bornstein, Nm, Bose, D, Boufous, S, Bourne, Rr, Boyers, Ln, Brainin, M, Brauer, M, Brayne, Ce, Brazinova, A, Breitborde, Nj, Brenner, H, Briggs, Ad, Brooks, Pm, Brown JBrugha TS, Buchbinder, R, Buckle, Gc, Bukhman, G, Bulloch, Ag, Burch, M, Burnett, R, Cardenas, R, Cabral, Nl, Campos Nonato IR, Campuzano JCCarapetis JR, Carpenter, Do, Caso, V, Castaneda-Orjuela, Ca, Catala-Lopez, F, Chadha, Vk, Chang, Jc, Chen, H, Chen, W, Chiang, Pp, Chimed-Ochir, O, Chowdhury, R, Christensen, H, Christophi, Ca, Chugh, S, Cirillo, M, Coggeshall, M, Cohen, A, Colistro, V, Colquhoun, Sm, Contreras, Ag, Cooper LTCooper, C, Cooperrider, K, Coresh, J, Cortinovis, M, Criqui, Mh, Crump, Ja, Cuevas-Nasu, L, Dandona, R, Dandona, L, Dansereau, E, Dantes, Hg, Dargan, Pi, Davey, G, Davitoiu, Dv, Dayama, A, De la Cruz-Gongora, V, de la Vega SF, De Leo, D, del Pozo-Cruz, B, Dellavalle, Rp, Deribe, K, Derrett, S, Des Jarlais DC, Dessalegn, M, Deveber, Ga, Dharmaratne, Sd, Diaz-Torne, C, Ding, El, Dokova, K, Dorsey, Er, Driscoll, Tr, Duber, H, Durrani, Am, Edmond, Km, Ellenbogen, Rg, Endres, M, Ermakov, Sp, Eshrati, B, Esteghamati, A, Estep, K, Fahimi, S, Farzadfar, F, Fay, Df, Felson, Dt, Fereshtehnejad SMFernandes JG, Ferri, Cp, Flaxman, A, Foigt, N, Foreman, Kj, Fowkes, Fg, Franklin, Rc, Furst, T, Futran, Nd, Gabbe, Bj, Gankpe, Fg, Garcia-Guerra FAGeleijnse JM, Gessner, Bd, Gibney, Kb, Gillum, Rf, Ginawi, Ia, Giroud, M, Giussani, G, Goenka, S, Goginashvili, K, Gona, P, Gonzalez de Cosio TGosselin RA, Gotay, Cc, Goto, A, Gouda, Hn, Guerrant, Rl, Gugnani, Hc, Gunnell, D, Gupta, R, Gutierrez, Ra, Hafezi-Nejad, N, Hagan HHalasa, Y, Hamadeh, Rr, Hamavid, H, Hammami, M, Hankey, Gj, Hao, Y, Harb, Hl, Haro, Jm, Havmoeller, R, Hay, Rj, Hay, S, Hedayati, Mt, Heredia Pi IB, Heydarpour, P, Hijar, M, Hoek, Hw, Hoffman, Hj, Hornberger, Jc, Hosgood, Hd, Hossain, M, Hotez, Pj, Hoy, Dg, Hsairi, M, Hu, H, Hu, G, Huang JJHuang, C, Huiart, L, Husseini, A, Iannarone, M, Iburg, Km, Innos, K, Inoue, M, Jacobsen, Kh, Jassal, Sk, Jeemon, P, Jensen, Pn, Jha, V, Jiang, G, Jiang YJonas JB, Joseph, J, Juel, K, Kan, H, Karch, A, Karimkhani, C, Karthikeyan, G, Katz, R, Kaul, A, Kawakami, N, Kazi, D, Kemp, Ah, Kengne, Ap, Khader, Y, Khalifa, Se, Khan, Ea, Khan, G, Khang, Yh, Khonelidze, I, Kieling, C, Kim, D, Kim, S, Kimokoti, Rw, Kinfu, Y, Kinge, Jm, Kissela, Bm, Kivipelto MKnibbs, L, Knudsen, Ak, Kokubo, Y, Kosen, S, Kramer, A, Kravchenko, M, Krishnamurthi, Rv, Krishnaswami, S, Kuate Defo, B, Kucuk Bicer, B, Kuipers EJKulkarni VS, Kumar, K, Kumar, Ga, Kwan, Gf, Lai, T, Lalloo, R, Lam, H, Lan, Q, Lansingh, Vc, Larson, H, Larsson, A, Lawrynowicz, Ae, Leasher, Jl, Lee, Jt, Leigh, J, Leung, R, Levi, M, Li, B, Li, Y, Liang, J, Lim, S, Lin, Hh, Lind, M, Lindsay, Mp, Lipshultz, Se, Liu, S, Lloyd, Bk, Lockett Ohno, S, Logroscino, G, Looker, Kj, Lopez, Ad, Lopez-Olmedo, N, Lortet-Tieulent, J, Lotufo, Pa, Low, N, Lucas, Rm, Lunevicius, R, Lyons, Ra, Ma, J, Ma, S, Mackay MTMajdan, M, Malekzadeh, R, Mapoma, Cc, Marcenes, W, March, Lm, Margono, C, Marks, Gb, Marzan, Mb, Masci, Jr, Mason-Jones, Aj, Matzopoulos RGMayosi BM, Mazorodze, Tt, Mcgill, Nw, Mcgrath, Jj, Mckee, M, Mclain, A, Mcmahon, Bj, Meaney, Pa, Mehndiratta, Mm, Mejia-Rodriguez, F, Mekonnen, W, Melaku, Ya, Meltzer, M, Memish, Za, Mensah, G, Meretoja, A, Mhimbira, Fa, Micha, R, Miller, Tr, Mills, Ej, Mitchell, Pb, Mock, Cn, Moffitt TEMohamed Ibrahim, N, Mohammad, Ka, Mokdad, Ah, Mola, Gl, Monasta, L, Montico, M, Montine, Tj, Moore, Ar, Moran, Ae, Morawska, L, Mori RMoschandreas, J, Moturi, Wn, Moyer, M, Mozaffarian, D, Mueller, Uo, Mukaigawara, M, Murdoch, Me, Murray, J, Murthy, K, Naghavi, P, Nahas ZNaheed, A, Naidoo, K, Naldi, L, Nand, D, Nangia, V, Narayan, Km, Nash, D, Nejjari, C, Neupane, Sp, Newman, Lm, Newton, Cr, Ng, M, Ngalesoni FNNhung NT, Nisar, Mi, Nolte, S, Norheim, Of, Norman, Re, Norrving, B, Nyakarahuka, L, Oh, Ih, Ohkubo, T, Omer, Sb, Opio, Jn, Ortiz, A, Pandian JDPanelo CI, Papachristou, C, Park, Ek, Parry, Cd, Caicedo, Aj, Patten, Sb, Paul, Vk, Pavlin, Bi, Pearce, N, Pedraza, L, Pellegrini, Ca, Pereira, Dm, Perez-Ruiz, Fp, Perico, N, Pervaiz, A, Pesudovs, K, Peterson, Cb, Petzold, M, Phillips, Mr, Phillips, D, Phillips, B, Piel, Fb, Plass, D, Poenaru, D, Polanczyk GVPolinder, S, Pope, Ca, Popova, S, Poulton, Rg, Pourmalek, F, Prabhakaran, D, Prasad, Nm, Qato, D, Quistberg, Da, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, Su, Raju, M, Rakovac, I, Rana, Sm, Razavi, H, Refaat, A, Rehm, J, Remuzzi, G, Resnikoff, S, Ribeiro, Al, Riccio, Pm, Richardson, L, Richardus, Jh, Riederer, Am, Robinson, M, Roca, A, Rodriguez, A, Rojas-Rueda, D, Ronfani, L, Rothenbacher, D, Roy, N, Ruhago, Gm, Sabin, N, Sacco, Rl, Ksoreide, K, Saha, S, Sahathevan, R, Sahraian, Ma, Sampson, U, Sanabria, Jr, Sanchez-Riera, L, Santos, I, Satpathy, M, Saunders, Je, Sawhney, M, Saylan MIScarborough, P, Schoettker, B, Schneider, Ij, Schwebel, Dc, Scott, Jg, Seedat, S, Sepanlou, Sg, Serdar, B, Servan-Mori, Ee, Shackelford, K, Shaheen AShahraz, S, Shamah Levy, T, Shangguan, S, She, J, Sheikhbahaei, S, Shepard, D, Shi, P, Shibuya, K, Shinohara, Y, Shiri, R, Shishani, K, Shiue, I, Shrime, Mg, Sigfusdottir, Id, Silberberg, Dh, Simard, Ep, Sindi, S, Singh, Ja, Singh, L, Skirbekk, V, Sliwa, K, Soljak, M, Soneji, S, Soshnikov, S, Speyer PSposato LA, Sreeramareddy, Ct, Stoeckl, H, Stathopoulou, Vk, Steckling, N, Stein, Mb, Stein, Dj, Steiner, Tj, Stewart, A, Stork, E, Stovner LJStroumpoulis, K, Sturua, L, Sunguya, Bf, Swaroop, M, Sykes, Bl, Tabb, Km, Takahashi, K, Tan, F, Tandon, N, Tanne, D, Tanner, M, Tavakkoli, M, Taylor, Hr, Te Ao BJ, Temesgen, Am, Ten Have, M, Tenkorang, Ey, Terkawi, A, Theadom, Am, Thomas, E, Thorne-Lyman, Al, Thrift, Ag, Tleyjeh, Im, Tonelli, M, Topouzis, F, Towbin, Ja, Toyoshima, H, Traebert, J, Tran, Bx, Trasande, L, Trillini, M, Truelsen, T, Trujillo, U, Tsilimbaris, M, Tuzcu, Em, Ukwaja KNUndurraga EA, Uzun, Sb, van Brakel WH, van de Vijver, S, Van Dingenen, R, van Gool CH, Varakin, Yy, Vasankari, Tj, Vavilala, M, Veerman LJVelasquez-Melendez, G, Venketasubramanian, N, Vijayakumar, L, Villalpando, S, Violante, F, Vlassov, Vv, Waller, S, Wallin, Mt, Wan, X, Wang, L, Wang, J, Wang, Y, Warouw, T, Weichenthal, S, Weiderpass, E, Weintraub, Rg, Werdecker, A, Wessells, Kr, Westerman, R, Wilkinson, Jd, Williams HCWilliams TN, Woldeyohannes, Sm, Wolfe, Cd, Wong, Jq, Wong, H, Woolf, Ad, Wright, Jl, Wurtz, B, Xu, G, Yang, G, Yano, Y, Yenesew, Ma, Yentur GKYip, P, Yonemoto, N, Yoon, Sj, Younis, M, Yu, C, Kim, Ky, Zaki Mel, S, Zhang, Y, Zhao, Z, Zhao, Y, Zhu, J, Zonies, D, Zunt, Jr, Salomon, Ja, Murray, Cj., Vos, Theo, Barber, Ryan M., Bell, Brad, Bertozzi-Villa, Amelia, Biryukov, Stan, Bolliger, Ian, Charlson, Fiona, Davis, Adrian, Degenhardt, Louisa, Dicker, Daniel, Duan, Leilei, Erskine, Holly, Feigin, Valery L., Ferrari, Alize J., Fitzmaurice, Christina, Fleming, Thoma, Graetz, Nichola, Guinovart, Caterina, Haagsma, Juanita, Hansen, Gillian M., Hanson, Sarah Wulf, Heuton, Kyle R., Higashi, Hideki, Kassebaum, Nichola, Kyu, Hmwe, Laurie, Evan, Liang, Xiofeng, Lofgren, Katherine, Lozano, Rafael, Macintyre, Michael F., Moradi-Lakeh, Maziar, Naghavi, Mohsen, Nguyen, Grant, Odell, Shaun, Ortblad, Katrina, Roberts, David Allen, Roth, Gregory A., Sandar, Logan, Serina, Peter T., Stanaway, Jeffrey D., Steiner, Caitlyn, Thomas, Bernadette, Vollset, Stein Emil, Whiteford, Harvey, Wolock, Timothy M., Ye, Pengpeng, Zhou, Maigeng, Ãvila, Marco A., Aasvang, Gunn Marit, Abbafati, Cristiana, Ozgoren, Ayse Abbasoglu, Abd-Allah, Foad, Aziz, Muna I. 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Arsic, Artaman, Al, Asghar, Rana J., Assadi, Reza, Atkins, Lydia S., Atkinson, Charle, Badawi, Alaa, Bahit, Maria C., Bakfalouni, Talal, Balakrishnan, Kalpana, Balalla, Shivanthi, Banerjee, Amitava, Barker-Collo, Suzanne L., Barquera, Simon, Barregard, Lar, Barrero, Lope H., Basu, Sanjay, Basu, Arindam, Baxter, Amanda, Beardsley, Justin, Bedi, Neeraj, Beghi, Ettore, Bekele, Tolesa, Bell, Michelle L., Benjet, Corina, Bennett, Derrick A., Bensenor, Isabela M., Benzian, Habib, Bernabe, Eduardo, Beyene, Tariku J., Bhala, Neeraj, Bhalla, Ashish, Bhutta, Zulfiqar, Bienhoff, Kelly, Bikbov, Bori, Abdulhak, Aref Bin, Blore, Jed D., Blyth, Fiona M., Bohensky, Megan A., Basara, Berrak Bora, Borges, Guilherme, Bornstein, Natan M., Bose, Dipan, Boufous, Soufiane, Bourne, Rupert R., Boyers, Lindsay N., Brainin, Michael, Brauer, Michael, Brayne, Carol E.G., Brazinova, Alexandra, Breitborde, Nicholas J.K., Brenner, Hermann, Briggs, Adam D.M., Brooks, Peter M., Brown, Jonathan, Brugha, Traolach S., Buchbinder, Rachelle, Buckle, Geoffrey C., Bukhman, Gene, Bulloch, Andrew G., Burch, Michael, Burnett, Richard, Cardenas, Rosario, Cabral, Norberto L., Campos-Nonato, Ismael R., Campuzano, Julio C., Carapetis, Jonathan R., Carpenter, David O., Caso, Valeria, Castaneda-Orjuela, Carlos A., Catala-Lopez, Ferran, Chadha, Vineet K., Chang, Jung-Chen, Chen, Honglei, Chen, Wanqing, Chiang, Peggy P., Chimed-Ochir, Odgerel, Chowdhury, Rajiv, Christensen, Hanne, Christophi, Costas A., Chugh, Sumeet S., Cirillo, Massimo, Coggeshall, Megan, Cohen, Aaron, Colistro, Valentina, Colquhoun, Samantha M., Contreras, Alejandra G., Cooper, Leslie T., Cooper, Cyru, Cooperrider, Kimberly, Coresh, Josef, Cortinovis, Monica, Criqui, Michael H., Crump, John A., Cuevas-Nasu, Lucia, Dandona, Rakhi, Dandona, Lalit, Dansereau, Emily, Dantes, Hector G., Dargan, Paul I., Davey, Gail, Davitoiu, Dragos V., Dayama, Anand, De La Cruz-Gongora, Vanessa, De La Vega, Shelley F., De Leo, Diego, Del Pozo-Cruz, Borja, Dellavalle, Robert P., Deribe, Kebede, Derrett, Sarah, Des Jarlais, Don C., Dessalegn, Muluken, Deveber, Gabrielle A., Dharmaratne, Samath D., Diaz-Torne, Cesar, Ding, Eric L., Dokova, Klara, Dorsey, E.R., Driscoll, Tim R., Duber, Herbert, Durrani, Adnan M., Edmond, Karen M., Ellenbogen, Richard G., Endres, Matthia, Ermakov, Sergey P., Eshrati, Babak, Esteghamati, Alireza, Estep, Kara, Fahimi, Saman, Farzadfar, Farshad, Fay, Derek F.J., Felson, David T., Fereshtehnejad, Seyed-Mohammad, Fernandes, Jefferson G., Ferri, Cluesa P., Flaxman, Abraham, Foigt, Nataliya, Foreman, Kyle J., Fowkes, F Gerry R., Franklin, Richard C., Furst, Thoma, Futran, Neal D., Gabbe, Belinda J., Gankpe, Fortune G., Garcia-Guerra, Francisco A., Geleijnse, Johanna M., Gessner, Bradford D., Gibney, Katherine B., Gillum, Richard F., Ginawi, Ibrahim A., Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goginashvili, Ketevan, Gona, Philimon, De Cosio, Teresita Gonzalez, Gosselin, Richard A., Gotay, Carolyn C., Goto, Atsushi, Gouda, Hebe N., Guerrant, Richard L., Gugnani, Harish C., Gunnell, David, Gupta, Rajeev, Gupta, Rahul, Gutierrez, Reyna A., Hafezi-Nejad, Nima, Hagan, Holly, Halasa, Yara, Hamadeh, Randah R., Hamavid, Hannah, Hammami, Mouhanad, Hankey, Graeme J., Hao, Yuantao, Harb, Hilda L., Haro, Josep Maria, Havmoeller, Rasmu, Hay, Roderick J., Hay, Simon, Hedayati, Mohammad T., Pi, Ileana B. Heredia, Heydarpour, Pouria, Hijar, Martha, Hoek, Hans W., Hoffman, Howard J., Hornberger, John C., Hosgood, H. Dean, Hossain, Mazeda, Hotez, Peter J., Hoy, Damian G., Hsairi, Mohamed, Hu, Howard, Hu, Guoqing, Huang, John J., Huang, Cheng, Huiart, Laetitia, Husseini, Abdullatif, Iannarone, Marissa, Iburg, Kim M., Innos, Kaire, Inoue, Manami, Jacobsen, Kathryn H., Jassal, Simerjot K., Jeemon, Panniyammakal, Jensen, Paul N., Jha, Vivekanand, Jiang, Guohong, Jiang, Ying, Jonas, Jost B., Joseph, Jonathan, Juel, Knud, Kan, Haidong, Karch, Andre, Karimkhani, Chante, Karthikeyan, Ganesan, Katz, Ronit, Kaul, Anil, Kawakami, Norito, Kazi, Dhruv S., Kemp, Andrew H., Kengne, Andre P., Khader, Yousef S., Khalifa, Shams Eldin A.H., Khan, Ejaz A., Khan, Gulfaraz, Khang, Young-Ho, Khonelidze, Irma, Kieling, Christian, Kim, Daniel, Kim, Sungroul, Kimokoti, Ruth W., Kinfu, Yohanne, Kinge, Jonas M., Kissela, Brett M., Kivipelto, Miia, Knibbs, Luke, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kosen, Soewarta, Kramer, Alexander, Kravchenko, Michael, Krishnamurthi, Rita V., Krishnaswami, Sanjay, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kuipers, Ernst J., Kulkarni, Veena S., Kumar, Kaushalendra, Kumar, G Anil, Kwan, Gene F., Lai, Taavi, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lansingh, Van C., Larson, Heidi, Larsson, Ander, Lawrynowicz, Alicia E.B., Leasher, Janet L., Lee, Jong-Tae, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Bin, Li, Yichong, Li, Yongmei, Liang, Juan, Lim, Stephen, Lin, Hsien-Ho, Lind, Margaret, Lindsay, M Patrice, Lipshultz, Steven E., Liu, Shiwei, Lloyd, Belinda K., Ohno, Summer Lockett, Logroscino, Giancarlo, Looker, Katharine J., Lopez, Alan D., Lopez-Olmedo, Nancy, Lortet-Tieulent, Joannie, Lotufo, Paulo A., Low, Nicola, Lucas, Robyn M., Lunevicius, Raimunda, Lyons, Ronan A., Ma, Jixiang, Ma, Stefan, Mackay, Mark T., Majdan, Marek, Malekzadeh, Reza, Mapoma, Christopher C., Marcenes, Wagner, March, Lyn M., Margono, Chri, Marks, Guy B., Marzan, Melvin B., Masci, Joseph R., Mason-Jones, Amanda J., Matzopoulos, Richard G., Mayosi, Bongani M., Mazorodze, Tasara T., Mcgill, Neil W., Mcgrath, John J., Mckee, Martin, Mclain, Abby, Mcmahon, Brian J., Meaney, Peter A., Mehndiratta, Man Mohan, Mejia-Rodriguez, Fabiola, Mekonnen, Wubegzier, Melaku, Yohannes A., Meltzer, Michele, Memish, Ziad A., Mensah, George, Meretoja, Atte, Mhimbira, Francis A., Micha, Renata, Miller, Ted R., Mills, Edward J., Mitchell, Philip B., Mock, Charles N., Moffitt, Terrie E., Ibrahim, Norlinah Mohamed, Mohammad, Karzan A., Mokdad, Ali H., Mola, Glen L., Monasta, Lorenzo, Montico, Marcella, Montine, Thomas J., Moore, Ami R., Moran, Andrew E., Morawska, Lidia, Mori, Rintaro, Moschandreas, Joanna, Moturi, Wilkister N., Moyer, Madeline, Mozaffarian, Dariush, Mueller, Ulrich O., Mukaigawara, Mitsuru, Murdoch, Michele E., Murray, Joseph, Murthy, Kinnari S., Naghavi, Paria, Nahas, Ziad, Naheed, Aliya, Naidoo, Kovin S., Naldi, Luigi, Nand, Devina, Nangia, Vinay, Narayan, K.M. Venkat, Nash, Deni, Nejjari, Chakib, Neupane, Sudan P., Newman, Lori M., Newton, Charles R., Ng, Marie, Ngalesoni, Frida N., Nhung, Nguyen T., Nisar, Muhammad I., Nolte, Sandra, Norheim, Ole F., Norman, Rosana E., Norrving, Bo, Nyakarahuka, Luke, Oh, In Hwan, Ohkubo, Takayoshi, Omer, Saad B., Opio, John Nelson, Ortiz, Alberto, Pandian, Jeyaraj D., Panelo, Carlo Irwin A., Papachristou, Christina, Park, Eun-Kee, Parry, Charles D., Caicedo, Angel J. Paternina, Patten, Scott B., Paul, Vinod K., Pavlin, Boris I., Pearce, Neil, Pedraza, Lilia S., Pellegrini, Carlos A., Pereira, David M., Perez-Ruiz, Fernando P., Perico, Norberto, Pervaiz, Aslam, Pesudovs, Konrad, Peterson, Carrie B., Petzold, Max, Phillips, Michael R., Phillips, David, Phillips, Bryan, Piel, Frederic B., Plass, Dietrich, Poenaru, Dan, Polanczyk, Guilherme V., Polinder, Suzanne, Pope, C.A., Popova, Svetlana, Poulton, Richie G., Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M., Qato, Dima, Quistberg, D.A., Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Sajjad Ur, Raju, Murugesan, Rakovac, Ivo, Rana, Saleem M., Razavi, Homie, Refaat, Amany, Rehm, Jurgen, Remuzzi, Giuseppe, Resnikoff, Serge, Ribeiro, Antonio L., Riccio, Patricia M., Richardson, Lee, Richardus, Jan Hendrik, Riederer, Anne M., Robinson, Margot, Roca, Anna, Rodriguez, Alina, Rojas-Rueda, David, Ronfani, Luca, Rothenbacher, Dietrich, Roy, Nobhojit, Ruhago, George M., Sabin, Nsanzimana, Sacco, Ralph L., Ksoreide, Kjetil, Saha, Sukanta, Sahathevan, Ramesh, Sahraian, Mohammad Ali, Sampson, Uchechukwu, Sanabria, Juan R., Sanchez-Riera, Lidia, Santos, Itamar S., Satpathy, Maheswar, Saunders, James E., Sawhney, Monika, Saylan, Mete I., Scarborough, Peter, Schoettker, Ben, Schneider, Ione J.C., Schwebel, David C., Scott, James G., Seedat, Soraya, Sepanlou, Sadaf G., Serdar, Berrin, Servan-Mori, Edson E., Shackelford, Katya, Shaheen, Amira, Shahraz, Saeid, Levy, Teresa Shamah, Shangguan, Siyi, She, Jun, Sheikhbahaei, Sara, Shepard, Donald S., Shi, Peilin, Shibuya, Kenji, Shinohara, Yukito, Shiri, Rahman, Shishani, Kawkab, Shiue, Ivy, Shrime, Mark G., Sigfusdottir, Inga D., Silberberg, Donald H., Simard, Edgar P., Sindi, Shireen, Singh, Jasvinder A., Singh, Lavanya, Skirbekk, Vegard, Sliwa, Karen, Soljak, Michael, Soneji, Samir, Soshnikov, Sergey S., Speyer, Peter, Sposato, Luciano A., Sreeramareddy, Chandrashekhar T., Stoeckl, Heidi, Stathopoulou, Vasiliki Kalliopi, Steckling, Nadine, Stein, Murray B., Stein, Dan J., Steiner, Timothy J., Stewart, Andrea, Stork, Eden, Stovner, Lars J., Stroumpoulis, Konstantino, Sturua, Lela, Sunguya, Bruno F., Swaroop, Mamta, Sykes, Bryan L., Tabb, Karen M., Takahashi, Ken, Tan, Feng, Tandon, Nikhil, Tanne, David, Tanner, Marcel, Tavakkoli, Mohammad, Taylor, Hugh R., Te Ao, Braden J., Temesgen, Awoke Misganaw, Have, Margreet Ten, Tenkorang, Eric Yeboah, Terkawi, Abdullah Sulieman, Theadom, Alice M., Thomas, Elissa, Thorne-Lyman, Andrew L., Thrift, Amanda G., Tleyjeh, Imad M., Tonelli, Marcello, Topouzis, Foti, Towbin, Jeffrey A., Toyoshima, Hideaki, Traebert, Jefferson, Tran, Bach X., Trasande, Leonardo, Trillini, Matia, Truelsen, Thoma, Trujillo, Ulise, Tsilimbaris, Miltiadi, Tuzcu, Emin M., Ukwaja, Kingsley N., Undurraga, Eduardo A., Uzun, Selen B., Van Brakel, Wim H., Van De Vijver, Steven, Dingenen, Rita Van, Van Gool, Coen H., Varakin, Yuri Y., Vasankari, Tommi J., Vavilala, Monica S., Veerman, Lennert J., Velasquez-Melendez, Gustavo, Venketasubramanian, Narayanaswamy, Vijayakumar, Lakshmi, Villalpando, Salvador, Violante, Francesco S., Vlassov, Vasiliy V., Waller, Stephen, Wallin, Mitchell T., Wan, Xia, Wang, Linhong, Wang, Jianli, Wang, Yanping, Warouw, Tati S., Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G., Werdecker, Andrea, Wessells, K. Ryan, Westerman, Ronny, Wilkinson, James D., Williams, Hywel C., Williams, Thomas N., Woldeyohannes, Solomon M., Wolfe, Charles D.A., Wong, John Q., Wong, Haidong, Woolf, Anthony D., Wright, Jonathan L., Wurtz, Brittany, Xu, Gelin, Yang, Gonghuan, Yano, Yuichiro, Yenesew, Muluken A., Yentur, Gokalp K., Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa, Yu, Chuanhua, Kim, Kim Yun, Zaki, Maysaa El Sayed, Zhang, Yong, Zhao, Zheng, Zhao, Yong, Zhu, Jun, Zonies, David, Zunt, Joseph R., Salomon, Joshua A., Murray, Christopher J.L., Cell biology, Gastroenterology & Hepatology, Epidemiology, Health Technology Assessment (HTA), and Public Health
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Male ,Gerontology ,Nutrition and Disease ,Epidemiology ,years lived with disability, Global burden of disease, acute and chronic diseases, countries ,Prevalence ,Disease ,Global Health ,Medical and Health Sciences ,Conduct disorder ,Otitis-media ,Cost of Illness ,Residence Characteristics ,Voeding en Ziekte ,80 and over ,Global health ,2.2 Factors relating to the physical environment ,2.1 Biological and endogenous factors ,countries ,Aetiology ,Child ,Aged, 80 and over ,Medicine(all) ,education.field_of_study ,ATTENTION-DEFICIT/HYPERACTIVITY DISORDER ,Incidence ,Mortality rate ,Incidence (epidemiology) ,Pain Research ,Neglected Diseases ,Alcohol dependence ,General Medicine ,Middle Aged ,Global burden of disease ,Global Burden of Disease Study 2013 Collaborators ,Mental Health ,Infectious Diseases ,Attention deficit/Hyperactivity disorder ,Burden of Illness ,Child, Preschool ,Acute Disease ,Female ,Life Sciences & Biomedicine ,Adult ,medicine.medical_specialty ,Adolescent ,GBD 2013 ,Population ,acute and chronic diseases ,Young Adult ,Mental-disorders ,Age Distribution ,Medicine, General & Internal ,Weights ,General & Internal Medicine ,medicine ,Humans ,Life Science ,Disabled Persons ,Sex Distribution ,Preschool ,education ,Developing Countries ,VLAG ,Aged ,Science & Technology ,business.industry ,Developed Countries ,Cutaneous Leishmaniasis ,Infant, Newborn ,Infant ,Health outcomes ,Newborn ,medicine.disease ,Comorbidity ,Brain Disorders ,years lived with disability ,Good Health and Well Being ,Disease, injury, incidence, prevalence, YLDs, GBD 2010 ,Chronic Disease ,Wounds and Injuries ,business ,2.4 Surveillance and distribution ,Iron-deficiency ,Demography - Abstract
Summary Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation. Background Up-to-date evidence about levels and trends in disease and injury incidence, prevalence, and years lived with disability (YLDs) is an essential input into global, regional, and national health policies. In the Global Burden of Disease Study 2013 (GBD 2013), we estimated these quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013. Methods Estimates were calculated for disease and injury incidence, prevalence, and YLDs using GBD 2010 methods with some important refinements. Results for incidence of acute disorders and prevalence of chronic disorders are new additions to the analysis. Key improvements include expansion to the cause and sequelae list, updated systematic reviews, use of detailed injury codes, improvements to the Bayesian meta-regression method (DisMod-MR), and use of severity splits for various causes. An index of data representativeness, showing data availability, was calculated for each cause and impairment during three periods globally and at the country level for 2013. In total, 35 620 distinct sources of data were used and documented to calculated estimates for 301 diseases and injuries and 2337 sequelae. The comorbidity simulation provides estimates for the number of sequelae, concurrently, by individuals by country, year, age, and sex. Disability weights were updated with the addition of new population-based survey data from four countries. Findings Disease and injury were highly prevalent; only a small fraction of individuals had no sequelae. Comorbidity rose substantially with age and in absolute terms from 1990 to 2013. Incidence of acute sequelae were predominantly infectious diseases and short-term injuries, with over 2 billion cases of upper respiratory infections and diarrhoeal disease episodes in 2013, with the notable exception of tooth pain due to permanent caries with more than 200 million incident cases in 2013. Conversely, leading chronic sequelae were largely attributable to non-communicable diseases, with prevalence estimates for asymptomatic permanent caries and tension-type headache of 2·4 billion and 1·6 billion, respectively. The distribution of the number of sequelae in populations varied widely across regions, with an expected relation between age and disease prevalence. YLDs for both sexes increased from 537·6 million in 1990 to 764·8 million in 2013 due to population growth and ageing, whereas the age-standardised rate decreased little from 114·87 per 1000 people to 110·31 per 1000 people between 1990 and 2013. Leading causes of YLDs included low back pain and major depressive disorder among the top ten causes of YLDs in every country. YLD rates per person, by major cause groups, indicated the main drivers of increases were due to musculoskeletal, mental, and substance use disorders, neurological disorders, and chronic respiratory diseases; however HIV/AIDS was a notable driver of increasing YLDs in sub-Saharan Africa. Also, the proportion of disability-adjusted life years due to YLDs increased globally from 21·1% in 1990 to 31·2% in 2013. Interpretation Ageing of the world's population is leading to a substantial increase in the numbers of individuals with sequelae of diseases and injuries. Rates of YLDs are declining much more slowly than mortality rates. The non-fatal dimensions of disease and injury will require more and more attention from health systems. The transition to non-fatal outcomes as the dominant source of burden of disease is occurring rapidly outside of sub-Saharan Africa. Our results can guide future health initiatives through examination of epidemiological trends and a better understanding of variation across countries. Funding Bill & Melinda Gates Foundation.
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- 2015
15. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015
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Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Murray, CJL, Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, 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MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, and Murray, CJL
- Published
- 2017
16. Global, regional, and national under-5 mortality, adult mortality, age-specific mortality, and life expectancy, 1970-2016: a systematic analysis for the Global Burden of Disease Study 2016
- Author
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Wang, H, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abera, SF, Abraha, HN, Abu-Raddad, LJ, Abu-Rmeileh, NME, Adedeji, IA, Adedoyin, RA, Adetifa, IMO, Adetokunboh, O, Afshin, A, Aggarwal, R, Agrawal, A, Agrawal, S, Kiadaliri, AA, Ahmed, MB, Aichour, AN, Aichour, I, Aichour, MTE, Aiyar, S, Akanda, S, Akinyemiju, TF, Akseer, N, Al-Eyadhy, A, Al Lami, FH, Alabed, S, Alahdab, F, Al-Aly, Z, Alam, K, Alam, N, Alasfoor, D, Aldridge, RW, Alene, KA, Alhabib, S, Ali, R, Alizadeh-Navaei, R, Aljunid, SM, Alkaabi, JM, Alkerwi, A, Alla, F, Allam, SD, Allebeck, P, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Ameh, EA, Amini, E, Ammar, W, Amoako, YA, Anber, N, Andrei, CL, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Anwari, P, Arnlov, J, Arora, M, Al, A, Aryal, KK, Asayesh, H, Asgedom, SW, Asghar, RJ, Assadi, R, Atey, TM, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Babalola, TK, Bacha, U, Badawi, A, Balakrishnan, 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S, Rezai, MS, Ribeiro, AL, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, A, Rubagotti, E, Ruhago, GM, Saadat, S, Sabde, YD, Sachdev, PS, Sadat, N, Safdarian, M, Safiri, SSS, Sagar, R, Sahathevan, R, Sahebkar, A, Sahraian, MA, Salama, J, Salamati, P, Salomon, JA, Salvi, SS, Samy, AM, Sanabria, JR, Sanchez-Nino, MD, Santos, IS, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Sawhney, M, Saxena, S, Saylan, MI, Schmidt, MI, Schneider, IJC, Schutte, AE, Schwebel, DC, Schwendicke, F, Seedat, S, Seid, AM, Sepanlou, SG, Servan-Mori, EE, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shamsipour, M, Shamsizadeh, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Shen, J, Shetty, BP, Shi, P, Shibuya, K, Shigematsu, M, Shiri, R, Shiue, I, Shrime, MG, Sigfusdottir, ID, Silberberg, DH, Silpakit, N, Silva, DAS, Silva, JP, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, PK, Singh, V, Sinha, DN, Skiadaresi, E, Sligar, A, Smith, DL, Sobaih, BHA, Sobngwi, E, Soneji, S, Soriano, JB, Sreeramareddy, CT, Srinivasan, V, Stathopoulou, V, Steel, N, Stein, DJ, Steiner, C, Stockl, H, Stokes, MA, Strong, M, Sufiyan, MB, Suliankatchi, RA, Sunguya, BF, Sur, PJ, Swaminathan, S, Sykes, BL, Szoeke, CEI, Tabares-Seisdedos, R, Tadakamadla, SK, Tadese, F, Tandon, N, Tanne, D, Tarajia, M, Tavakkoli, M, Taveira, N, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Temsah, M-H, Terkawi, AS, Tesema, CL, Tesssema, B, Theis, A, Thomas, N, Thompson, AH, Thomson, AJ, Thrift, AG, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Topouzis, F, Tortajada, M, Tran, BX, Trujillo, TTU, Tsilimparis, N, Tuem, KB, Tuzcu, EM, Tyrovolas, S, Ukwaja, KN, Undurraga, EA, Uthman, OA, Uzochukwu, BSC, van Boven, JFM, Varakin, YY, Varughese, S, Vasankari, T, Vasconcelos, AMN, Venketasubramanian, N, Vidavalur, R, Violante, FS, Vishnu, A, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Waid, JL, Wakayo, T, Wang, Y-P, Weichenthal, S, Weiderpass, E, Weintraub, RG, Werdecker, A, Wesana, J, Wijeratne, T, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Workicho, A, Workie, SB, Xavier, D, Xu, G, Yaghoubi, M, Yakob, B, Yalew, AZ, Yan, LL, Yano, Y, Yaseri, M, Ye, P, Yimam, HH, Yip, P, Yirsaw, BD, Yonemoto, N, Yoon, S-J, Yotebieng, M, Younis, MZ, Zaidi, Z, Zaki, MES, Zeeb, H, Zenebe, ZM, Zerfu, TA, Zhang, AL, Zhang, X, Zodpey, S, Zuhlke, LJ, Lopez, AD, and Murray, CJL
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- 2017
17. Mycobacterium tuberculosis bacteremia in adults and children: A systematic review and meta-analysis
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Pavlinac, PB, Lokken, EM, Walson, JL, Richardson, BA, Crump, JA, and John-Stewart, GC
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Adult ,Aged, 80 and over ,Adolescent ,Coinfection ,Infant ,Bacteremia ,HIV Infections ,Mycobacterium tuberculosis ,Middle Aged ,Article ,Young Adult ,Age Distribution ,Child, Preschool ,Prevalence ,Humans ,Tuberculosis ,Child ,Aged - Abstract
SETTINGp: Among human immunodeficiency virus (HIV) infected adults living in tuberculosis (TB) endemic settings, Mycobacterium tuberculosis is a common cause of bloodstream infections. Although young children have an increased propensity for M. tuberculosis dissemination, M. tuberculosis bacteremia is infrequently described in children.To determine the prevalence of M. tuberculosis bacteremia in adult and pediatric patients and to examine sources of heterogeneity between estimates.Systematic review and meta-analysis.Of 1077 reviewed abstracts, 27 publications met the inclusion criteria, yielding 29 independent M. tuberculosis bacteremia prevalence estimates: 22 in adults, 6 in children, and 1 not stratified by age group. The random effects pooled M. tuberculosis bacteremia prevalence in adults was 13.5% (95%CI 10.8-16.2) and 0.4% (95%CI 0-0.9) in children (P for difference = 0.004). Restricting analyses to HIV-infected participants, pooled M. tuberculosis bacteremia prevalence from 21 adult studies was 15.5% (95%CI 12.5-18.5) and 0.8% (95%CI 0-1.8) in three pediatric studies (P = 0.001). Inclusion of pre-determined study-level confounders did not account for observed differences in M. tuberculosis bacteremia prevalence between age groups.While M. tuberculosis bacteremia appears relatively common in adults, particularly those with HIV infection, bloodstream M. tuberculosis appears to be rare in children.
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- 2016
18. Global and National Burden of Diseases and Injuries Among Children and Adolescents Between 1990 and 2013 Findings From the Global Burden of Disease 2013 Study
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Kyu, HH, Pinho, C, Wagner, JA, Brown, JC, Bertozzi-Villa, A, Charlson, FJ, Coffeng, LE, Dandona, L, Erskine, HE, Ferrari, AJ, Fitzmaurice, C, Fleming, TD, Forouzanfar, MH, Graetz, N, Guinovart, C, Haagsma, J, Higashi, H, Kassebaum, NJ, Larson, HJ, Lim, SS, Mokdad, AH, Moradi-Lakeh, M, Odell, SV, Roth, GA, Serina, PT, Stanaway, JD, Misganaw, A, Whiteford, HA, Wolock, TM, Hanson, SW, Abd-Allah, F, Abera, SF, Abu-Raddad, LJ, AlBuhairan, FS, Amare, AT, Antonio, CAT, Artaman, A, Barker-Collo, SL, Barrero, LH, Benjet, C, Bensenor, IM, Bhutta, ZA, Bikbov, B, Brazinova, A, Campos-Nonato, I, Castaneda-Orjuela, CA, Catala-Lopez, F, Chowdhury, R, Cooper, C, Crump, JA, Dandona, R, Degenhardt, L, Dellavalle, RP, Dharmaratne, SD, Faraon, EJA, Feigin, VL, Fuerst, T, Geleijnse, JM, Gessner, BD, Gibney, KB, Goto, A, Gunnell, D, Hankey, GJ, Hay, RJ, Hornberger, JC, Hosgood, HD, Hu, G, Jacobsen, KH, Jayaraman, SP, Jeemon, P, Jonas, JB, Karch, A, Kim, D, Kim, S, Kokubo, Y, Defo, BK, Bicer, BK, Kumar, GA, Larsson, A, Leasher, JL, Leung, R, Li, Y, Lipshultz, SE, Lopez, AD, Lotufo, PA, Lunevicius, R, Lyons, RA, Majdan, M, Malekzadeh, R, Mashal, T, Mason-Jones, AJ, Melaku, YA, Memish, ZA, Mendoza, W, Miller, TR, Mock, CN, Murray, J, Nolte, S, Oh, I-H, Olusanya, BO, Ortblad, KF, Park, E-K, Paternina Caicedo, AJ, Patten, SB, Patton, GC, Pereira, DM, Perico, N, Piel, FB, Polinder, S, Popova, S, Pourmalek, F, Quistberg, DA, Remuzzi, G, Rodriguez, A, Rojas-Rueda, D, Rothenbacher, D, Rothstein, DH, Sanabria, J, Santos, IS, Schwebel, DC, Sepanlou, SG, Shaheen, A, Shiri, R, Shiue, I, Skirbekk, V, Sliwa, K, Sreeramareddy, CT, Stein, DJ, Steiner, TJ, Stovner, LJ, Sykes, BL, Tabb, KM, Terkawi, AS, Thomson, AJ, Thorne-Lyman, AL, Towbin, JA, Ukwaja, KN, Vasankari, T, Venketasubramanian, N, Vlassov, VV, Vollset, SE, Weiderpass, E, Weintraub, RG, Werdecker, A, Wilkinson, JD, Woldeyohannes, SM, Wolfe, CDA, Yano, Y, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaki, MES, Naghavi, M, Murray, CJL, Vos, T, Kyu, HH, Pinho, C, Wagner, JA, Brown, JC, Bertozzi-Villa, A, Charlson, FJ, Coffeng, LE, Dandona, L, Erskine, HE, Ferrari, AJ, Fitzmaurice, C, Fleming, TD, Forouzanfar, MH, Graetz, N, Guinovart, C, Haagsma, J, Higashi, H, Kassebaum, NJ, Larson, HJ, Lim, SS, Mokdad, AH, Moradi-Lakeh, M, Odell, SV, Roth, GA, Serina, PT, Stanaway, JD, Misganaw, A, Whiteford, HA, Wolock, TM, Hanson, SW, Abd-Allah, F, Abera, SF, Abu-Raddad, LJ, AlBuhairan, FS, Amare, AT, Antonio, CAT, Artaman, A, Barker-Collo, SL, Barrero, LH, Benjet, C, Bensenor, IM, Bhutta, ZA, Bikbov, B, Brazinova, A, Campos-Nonato, I, Castaneda-Orjuela, CA, Catala-Lopez, F, Chowdhury, R, Cooper, C, Crump, JA, Dandona, R, Degenhardt, L, Dellavalle, RP, Dharmaratne, SD, Faraon, EJA, Feigin, VL, Fuerst, T, Geleijnse, JM, Gessner, BD, Gibney, KB, Goto, A, Gunnell, D, Hankey, GJ, Hay, RJ, Hornberger, JC, Hosgood, HD, Hu, G, Jacobsen, KH, Jayaraman, SP, Jeemon, P, Jonas, JB, Karch, A, Kim, D, Kim, S, Kokubo, Y, Defo, BK, Bicer, BK, Kumar, GA, Larsson, A, Leasher, JL, Leung, R, Li, Y, Lipshultz, SE, Lopez, AD, Lotufo, PA, Lunevicius, R, Lyons, RA, Majdan, M, Malekzadeh, R, Mashal, T, Mason-Jones, AJ, Melaku, YA, Memish, ZA, Mendoza, W, Miller, TR, Mock, CN, Murray, J, Nolte, S, Oh, I-H, Olusanya, BO, Ortblad, KF, Park, E-K, Paternina Caicedo, AJ, Patten, SB, Patton, GC, Pereira, DM, Perico, N, Piel, FB, Polinder, S, Popova, S, Pourmalek, F, Quistberg, DA, Remuzzi, G, Rodriguez, A, Rojas-Rueda, D, Rothenbacher, D, Rothstein, DH, Sanabria, J, Santos, IS, Schwebel, DC, Sepanlou, SG, Shaheen, A, Shiri, R, Shiue, I, Skirbekk, V, Sliwa, K, Sreeramareddy, CT, Stein, DJ, Steiner, TJ, Stovner, LJ, Sykes, BL, Tabb, KM, Terkawi, AS, Thomson, AJ, Thorne-Lyman, AL, Towbin, JA, Ukwaja, KN, Vasankari, T, Venketasubramanian, N, Vlassov, VV, Vollset, SE, Weiderpass, E, Weintraub, RG, Werdecker, A, Wilkinson, JD, Woldeyohannes, SM, Wolfe, CDA, Yano, Y, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaki, MES, Naghavi, M, Murray, CJL, and Vos, T
- Abstract
IMPORTANCE: The literature focuses on mortality among children younger than 5 years. Comparable information on nonfatal health outcomes among these children and the fatal and nonfatal burden of diseases and injuries among older children and adolescents is scarce. OBJECTIVE: To determine levels and trends in the fatal and nonfatal burden of diseases and injuries among younger children (aged <5 years), older children (aged 5-9 years), and adolescents (aged 10-19 years) between 1990 and 2013 in 188 countries from the Global Burden of Disease (GBD) 2013 study. EVIDENCE REVIEW: Data from vital registration, verbal autopsy studies, maternal and child death surveillance, and other sources covering 14,244 site-years (ie, years of cause of death data by geography) from 1980 through 2013 were used to estimate cause-specific mortality. Data from 35,620 epidemiological sources were used to estimate the prevalence of the diseases and sequelae in the GBD 2013 study. Cause-specific mortality for most causes was estimated using the Cause of Death Ensemble Model strategy. For some infectious diseases (eg, HIV infection/AIDS, measles, hepatitis B) where the disease process is complex or the cause of death data were insufficient or unavailable, we used natural history models. For most nonfatal health outcomes, DisMod-MR 2.0, a Bayesian metaregression tool, was used to meta-analyze the epidemiological data to generate prevalence estimates. FINDINGS: Of the 7.7 (95% uncertainty interval [UI], 7.4-8.1) million deaths among children and adolescents globally in 2013, 6.28 million occurred among younger children, 0.48 million among older children, and 0.97 million among adolescents. In 2013, the leading causes of death were lower respiratory tract infections among younger children (905.059 deaths; 95% UI, 810,304-998,125), diarrheal diseases among older children (38,325 deaths; 95% UI, 30,365-47,678), and road injuries among adolescents (115,186 deaths; 95% UI, 105,185-124,870). Iron defici
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- 2016
19. Rapid Emergence of Multidrug Resistant, H58-Lineage Salmonella Typhi in Blantyre, Malawi
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Crump, JA, Feasey, NA, Gaskell, K, Wong, V, Msefula, C, Selemani, G, Kumwenda, S, Allain, TJ, Mallewa, J, Kennedy, N, Bennett, A, Nyirongo, JO, Nyondo, PA, Zulu, MD, Parkhill, J, Dougan, G, Gordon, MA, Heyderman, RS, Crump, JA, Feasey, NA, Gaskell, K, Wong, V, Msefula, C, Selemani, G, Kumwenda, S, Allain, TJ, Mallewa, J, Kennedy, N, Bennett, A, Nyirongo, JO, Nyondo, PA, Zulu, MD, Parkhill, J, Dougan, G, Gordon, MA, and Heyderman, RS
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INTRODUCTION: Between 1998 and 2010, S. Typhi was an uncommon cause of bloodstream infection (BSI) in Blantyre, Malawi and it was usually susceptible to first-line antimicrobial therapy. In 2011 an increase in a multidrug resistant (MDR) strain was detected through routine bacteriological surveillance conducted at Queen Elizabeth Central Hospital (QECH). METHODS: Longitudinal trends in culture-confirmed Typhoid admissions at QECH were described between 1998-2014. A retrospective review of patient cases notes was conducted, focusing on clinical presentation, prevalence of HIV and case-fatality. Isolates of S. Typhi were sequenced and the phylogeny of Typhoid in Blantyre was reconstructed and placed in a global context. RESULTS: Between 1998-2010, there were a mean of 14 microbiological diagnoses of Typhoid/year at QECH, of which 6.8% were MDR. This increased to 67 in 2011 and 782 in 2014 at which time 97% were MDR. The disease predominantly affected children and young adults (median age 11 [IQR 6-21] in 2014). The prevalence of HIV in adult patients was 16.7% [8/48], similar to that of the general population (17.8%). Overall, the case fatality rate was 2.5% (3/94). Complications included anaemia, myocarditis, pneumonia and intestinal perforation. 112 isolates were sequenced and the phylogeny demonstrated the introduction and clonal expansion of the H58 lineage of S. Typhi. CONCLUSIONS: Since 2011, there has been a rapid increase in the incidence of multidrug resistant, H58-lineage Typhoid in Blantyre. This is one of a number of reports of the re-emergence of Typhoid in Southern and Eastern Africa. There is an urgent need to understand the reservoirs and transmission of disease and how to arrest this regional increase.
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- 2015
20. Typhoid fever in Fiji: a reversible plague?
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Thompson, CN, Kama, M, Acharya, S, Bera, U, Clemens, J, Crump, JA, Dawainavesi, A, Dougan, G, Edmunds, WJ, Fox, K, Jenkins, K, Khan, MI, Koroivueta, J, Levine, MM, Martin, LB, Nilles, E, Pitzer, VE, Singh, S, Raiwalu, RV, Baker, S, Mulholland, K, Thompson, CN, Kama, M, Acharya, S, Bera, U, Clemens, J, Crump, JA, Dawainavesi, A, Dougan, G, Edmunds, WJ, Fox, K, Jenkins, K, Khan, MI, Koroivueta, J, Levine, MM, Martin, LB, Nilles, E, Pitzer, VE, Singh, S, Raiwalu, RV, Baker, S, and Mulholland, K
- Abstract
The country of Fiji, with a population of approximately 870 000 people, faces a growing burden of several communicable diseases including the bacterial infection typhoid fever. Surveillance data suggest that typhoid has become increasingly common in rural areas of Fiji and is more frequent amongst young adults. Transmission of the organisms that cause typhoid is facilitated by faecal contamination of food or water and may be influenced by local behavioural practices in Fiji. The Fijian Ministry of Health, with support from Australian Aid, hosted a meeting in August 2012 to develop comprehensive control and prevention strategies for typhoid fever in Fiji. International and local specialists were invited to share relevant data and discuss typhoid control options. The resultant recommendations focused on generating a clearer sense of the epidemiology of typhoid in Fiji and exploring the contribution of potential transmission pathways. Additionally, the panel suggested steps such as ensuring that recommended ciprofloxacin doses are appropriate to reduce the potential for relapse and reinfection in clinical cases, encouraging proper hand hygiene of food and drink handlers, working with water and sanitation agencies to review current sanitation practices and considering a vaccination policy targeting epidemiologically relevant populations.
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- 2014
21. Low Sensitivity of T-Cell Based Detection of Tuberculosis among HIV Co-Infected Tanzanian In-Patients
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Seshadri, C, primary, Uiso, LO, additional, Ostermann, J, additional, Diefenthal, H, additional, Shao, HJ, additional, Chu, HY, additional, Asmuth, DM, additional, Thielman, NM, additional, Bartlett, JA, additional, and Crump, JA, additional
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- 2008
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22. Part III. Analysis of data gaps pertaining to enterotoxigenic Escherichia coli infections in low and medium human development index countries, 1984-2005.
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Gupta SK, Keck J, Ram PK, Crump JA, Miller MA, Mintz ED, Gupta, S K, Keck, J, Ram, P K, Crump, J A, Miller, M A, and Mintz, E D
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Enterotoxigenic Escherichia coli (ETEC) is a common cause of profuse watery diarrhoea in the developing world, often leading to severe dehydration or death. We found only 15 population-based studies in low and medium human development index (HDI) countries from 1984 to 2005 that evaluate disease incidence. Reported incidence ranged from 39 to 4460 infections/1000 persons per year. The peak incidence of ETEC appeared to occur between ages 6 and 18 months. A median of 14% (range 2-36%) of diarrhoeal specimens were positive for ETEC in 19 facility- and population-based studies conducted in all age groups and 13% (range 3-39%) in 51 studies conducted in children only. Heat-labile toxin (LT)-ETEC is thought to be less likely to cause disease than heat-stable toxin (ST)-ETEC or LT/ST-ETEC. Because population-based studies involve enhanced clinical management of patients and facility-based studies include only the most severe illnesses, reliable data on complications and mortality from ETEC infections was unavailable. To reduce gaps in the current understanding of ETEC incidence, complications and mortality, large population-based studies combined with facility-based studies covering a majority of the corresponding population are needed, especially in low-HDI countries. Moreover, a standard molecular definition of ETEC infection is needed to be able to compare results across study sites. [ABSTRACT FROM AUTHOR]
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- 2008
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23. Part I. Analysis of data gaps pertaining to Salmonella enterica serotype Typhi infections in low and medium human development index countries, 1984-2005.
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Crump JA, Ram PK, Gupta SK, Miller MA, Mintz ED, Crump, J A, Ram, P K, Gupta, S K, Miller, M A, and Mintz, E D
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There are only 10 contemporary, population-based studies of typhoid fever that evaluate disease incidence using blood culture for confirmation of cases. Reported incidence ranged from 13 to 976/100 000 persons per year. These studies are likely to have been done preferentially in high- incidence sites which makes generalization of data difficult. Only five of these studies reported mortality. Of these the median (range) mortality was 0% (0-1.8%). Since study conditions usually involved enhanced clinical management of patients and the studies were not designed to evaluate mortality as an outcome, their usefulness for generalizing case-fatality rates is uncertain. No contemporary population-based studies reported rates of complications. Hospital-based typhoid fever studies reported median (range) complication rates of 2.8% (0.6-4.9%) for intestinal perforation and case-fatality rates of 2.0% (0-14.8%). Rates of complications other than intestinal perforation were not reported in contemporary hospital-based studies. Hospital-based studies capture information on the most severe illnesses among persons who have access to health-care services limiting their generalizability. Only two studies have informed the current understanding of typhoid fever age distribution curves. Extrapolation from population-based studies suggests that most typhoid fever occurs among young children in Asia. To reduce gaps in the current understanding of typhoid fever incidence, complications, and case-fatality rate, large population-based studies using blood culture confirmation of cases are needed in representative sites, especially in low and medium human development index countries outside Asia. [ABSTRACT FROM AUTHOR]
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- 2008
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24. Cost effectiveness of free HIV voluntary counseling and testing through a community-based AIDS service organization in Northern Tanzania.
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Thielman NM, Chu HY, Osterman J, Itemba DK, Mgonja A, Mtweve S, Bartlett JA, Shao JF, and Crump JA
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Objectives. We evaluated the cost-effectiveness of fee-based and free testing strategies at an HIV voluntary counseling and testing (VCT) program integrated into a community-based AIDS service organization in Moshi, Tanzania.Methods. We waived the usual fee schedule during a 2-week free, advertised VCT campaign; analyzed the number of clients testing per day during prefree, free, and postfree testing periods; and estimated the cost-effectiveness of limited and sustained free testing strategies.Results. The number of clients testing per day increased from 4.1 during the prefree testing interval to 15.0 during the free testing campaign (P<.0001) and remained significantly increased at 7.1 (P<.0001) after resumption of the standard fees. HIV seroprevalence (16.7%) and risk behaviors were unchanged over these intervals. Modeled over 1 year, the costs per infection averted with the standard fee schedule, with a 2-week free VCT campaign, and with sustained free VCT year-round were $170, $105, and $92, respectively, and the costs per disability-adjusted life year gained were $8.72, $5.40, and $4.72, respectively.Conclusions. The provision of free VCT enhances both the number of clients testing per day and its cost-effectiveness in resource-limited settings. [ABSTRACT FROM AUTHOR]
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- 2006
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25. The global burden of typhoid fever.
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Crump JA, Luby SR, and Mintz ED
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Objective: To use new data to make a revised estimate of the global burden of typhoid fever, an accurate understanding of which is necessary to guide public health decisions for disease control and prevention efforts. Methods: Population-based studies using confirmation by blood culture of typhoid fever cases were sought by computer search of the multilingual scientific literature. Where there were no eligible studies, data were extrapolated from neighboring countries and regions. Age-incidence curves were used to model rates measured among narrow age cohorts to the general population. One-way sensitivity analysis was performed to explore the sensitivity of the estimate to the assumptions. The burden of paratyphoid fever was derived by a proportional method. Findings: A total of 22 eligible studies were identified. Regions with high incidence of typhoid fever (>100/100 000 cases/year include south-central Asia and south-east Asia. Regions of medium incidence (10-100/100 000 cases/year) include the rest of Asia, Africa, Latin America and the Caribbean, and Oceania, except for Australia and New Zealand. Europe, North America, and the reset of the developed world have low incidence of typhoid fever (<10/100 000 cases/year). We estimate that typhoid fever caused 21 560 974 illnesses and 216 510 deaths during 2000 and that paratyphoid fever caused 5 412 744 illnesses. Conclusion: New data and improved understanding of typhoid fever epidemiology enabled us to refine the global typhoid burden estimate, which remains considerable. More detailed incidence studies in selected countries and regions, particularly Africa, are needed to further improve the estimate. [ABSTRACT FROM AUTHOR]
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- 2004
26. Salmonella enterica serotype Javiana infections associated with amphibian contact, Mississippi, 2001.
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Srikantiah P, Lay JC, Hand S, Crump JA, Campbell J, Van Duyne MS, Bishop R, Middendor R, Currier M, Mead PS, Mølbak K, Srikantiah, P, Lay, J C, Hand, S, Crump, J A, Campbell, J, Van Duyne, M S, Bishop, R, Middendor, R, and Currier, M
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- 2004
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27. Outbreaks of Escherichia coli O157 infections at multiple county agricultural fairs: a hazard of mixing cattle, concession stands and children.
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Crump JA, Braden CR, Dey ME, Hoekstra RM, Rickelman-Apisa JM, Baldwin DA, De Fijter SJ, Nowicki SF, Koch EM, Bannerman TL, Smith FW, Sarisky JP, Hochberg N, Mead PS, Crump, John A, Braden, Christopher R, Dey, Meghan E, Hoekstra, R Michael, Rickelman-Apisa, Janet M, and Baldwin, David A
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- 2003
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28. An outbreak of Escherichia coli O157:H7 infections among visitors to a dairy farm.
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Crump JA, Sulka AC, Langer AJ, Schaben C, Crielly AS, Gage R, Baysinger M, Moll M, Withers G, Toney DM, Hunter SB, Hoekstra RM, Wong SK, Griffin PM, and Van Gilder TJ
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- 2002
29. Sharing Shigella: risk factors for a multicommunity outbreak of shigellosis.
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Shane AL, Tucker NA, Crump JA, Mintz ED, and Painter JA
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- 2003
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30. Proteolysis in Cotyledon Cells of Phaseolus vulgaris L.: Changes in Multiple Hydrolase Activities Following Germination
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Crump, JA and Murray, DR
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Changes in activity of several hydrolytic enzymes were measured in extracts prepared from the cotyledons following germination of bean seeds (Phaseolus vulgaris cv. Hawkesbury Wonder). Aminopeptidase AP2 (phenanthroline-sensitive leucyl β-naphthylamidase), N-carbobenzoxy-L- tyrosine-p-nitrophenol ester (N-CBZ-L-Tyr-pNP) hydrolase, N-benzoyl-L-tyrosineethyl ester (BTEE) hydrolase and acid phosphatase all increased in activity per cotyledon, reaching maximum values after 4, 6, 10 and 10 days respectively. By comparison, aminopeptidase AP1 (phenanthrolineinsensitive leucyl β-naphthylamidase) showed maximum activity after 2 days and declined immediately. α-N-benzoyl-D,L-arginine-p-nitroanilide hydrolase activity was maintained at a maximum value between days 2 and 10 before declining. Differences in maximum activity per cotyledon, initial presence or absence, and timing of both increase and decrease of N-CBZ-L-Tyr-pNP and BTEE hydrolase activities suggest that at least two enzymes contribute to these activities, and that neither activity indicates the presence of a chymotrypsin-like endopeptidase.
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- 1979
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31. Phylogeographical analysis of the dominant multidrug-resistant H58 clade of Salmonella Typhi identifies inter-and intracontinental transmission events
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Wong, VK, Baker, S, Pickard, DJ, Parkhill, J, Page, AJ, Feasey, NA, Kingsley, RA, Thomson, NR, Keane, JA, Weill, FX, Edwards, DJ, Hawkey, J, Harris, Mather, AE, Cain, AK, Hadfield, J, Hart, PJ, Thieu, NTV, Klemm, EJ, Glinos, DA, Breiman, RF, Watson, CH, Kariuki, S, Gordon, MA, Heyderman, RS, Okoro, C, Jacobs, J, Lunguya, O, Edmunds, WJ, Msefula, C, Chabalgoity, JA, Kama, M, Jenkins, K, Dutta, S, Marks, F, Campos, J, Thompson, C, Obaro, S, Maclennan, CA, Dolecek, C, Keddy, KH, Smith, AM, Parry, CM, Karkey, A, Mulholland, EK, Campbell, JI, Dongol, S, Basnyat, B, Dufour, M, Bandaranayake, D, Naseri, TT, Singh, SP, Hatta, M, Newton, P, Onsare, RS, Isaia, L, Dance, D, Davong, V, Thwaites, G, Wijedoru, L, Crump, JA, De Pinna, E, Nair, S, Nilles, EJ, Thanh, DP, Turner, P, Soeng, S, Valcanis, M, Powling, J, Dimovski, K, Hogg, G, Farrar, J, Holt, KE, and Dougan, G
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3. Good health
32. Derivation and validation of a universal vital assessment (UVA) score: A tool for predicting mortality in adult hospitalised patients in Sub-Saharan Africa
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Moore, CC, Hazard, R, Saulters, KJ, Ainsworth, J, Adakun, SA, Amir, A, Andrews, B, Auma, M, Baker, T, Banura, P, Crump, JA, Grobusch, MP, Huson, MAM, Jacob, ST, Jarrett, Olamide, Kellett, J, Lakhi, S, Majwala, A, Opio, M, Rubach, MP, Rylance, J, Scheld, W Michael, Schieffelin, J, Ssekitoleko, R, Wheeler, I, and Barnes, LE
- Subjects
3. Good health ,Uncategorized - Abstract
Background Critical illness is a leading cause of morbidity and mortality in Sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA. Methods We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009–2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score. results Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27–49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)). conclusion We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies.
33. Derivation and validation of a universal vital assessment (UVA) score: A tool for predicting mortality in adult hospitalised patients in Sub-Saharan Africa
- Author
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Moore, CC, Hazard, R, Saulters, KJ, Ainsworth, J, Adakun, SA, Amir, A, Andrews, B, Auma, M, Baker, T, Banura, P, Crump, JA, Grobusch, MP, Huson, MAM, Jacob, ST, Jarrett, Olamide, Kellett, J, Lakhi, S, Majwala, A, Opio, M, Rubach, MP, Rylance, J, Scheld, W Michael, Schieffelin, J, Ssekitoleko, R, Wheeler, I, and Barnes, LE
- Subjects
3. Good health ,Uncategorized - Abstract
Background Critical illness is a leading cause of morbidity and mortality in Sub-Saharan Africa (SSA). Identifying patients with the highest risk of death could help with resource allocation and clinical decision making. Accordingly, we derived and validated a universal vital assessment (UVA) score for use in SSA. Methods We pooled data from hospital-based cohort studies conducted in six countries in SSA spanning the years 2009–2015. We derived and internally validated a UVA score using decision trees and linear regression and compared its performance with the modified early warning score (MEWS) and the quick sepsis-related organ failure assessment (qSOFA) score. results Of 5573 patients included in the analysis, 2829 (50.8%) were female, the median (IQR) age was 36 (27–49) years, 2122 (38.1%) were HIV-infected and 996 (17.3%) died in-hospital. The UVA score included points for temperature, heart and respiratory rates, systolic blood pressure, oxygen saturation, Glasgow Coma Scale score and HIV serostatus, and had an area under the receiver operating characteristic curve (AUC) of 0.77 (95% CI 0.75 to 0.79), which outperformed MEWS (AUC 0.70 (95% CI 0.67 to 0.71)) and qSOFA (AUC 0.69 (95% CI 0.67 to 0.72)). conclusion We identified predictors of in-hospital mortality irrespective of the underlying condition(s) in a large population of hospitalised patients in SSA and derived and internally validated a UVA score to assist clinicians in risk-stratifying patients for in-hospital mortality. The UVA score could help improve patient triage in resource-limited environments and serve as a standard for mortality risk in future studies.
34. Global, regional, and national age-sex-specific mortality for 282 causes of death in 195 countries and territories, 1980–2017: a systematic analysis for the Global Burden of Disease Study 2017
- Author
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Roth, Gregory A., Collaborotors, G. B. 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Adult ,Male ,Adolescent ,national age-sex-specific mortality ,UNITED-STATES ,Global Health ,Socioeconomic Factor ,Global Burden of Disease ,GBD, causes of death ,Young Adult ,Age Distribution ,Life Expectancy ,General & Internal Medicine ,Cause of Death ,PUBLIC-HEALTH PROBLEM ,mortality ,282 causes global burden of disease ,Sex Distribution ,Child ,Aged ,Aged, 80 and over ,BARRIERS ,DEMENTIA ,Medicine (all) ,Infant, Newborn ,Infant ,11 Medical And Health Sciences ,Middle Aged ,TRENDS ,PREVENTION ,PREVALENCE ,ALZHEIMERS-DISEASE ,INDIVIDUALS ,3121 General medicine, internal medicine and other clinical medicine ,Child, Preschool ,REGISTRATION ,Female ,Human medicine ,Human - Abstract
Background Global development goals increasingly rely on country-specific estimates for benchmarking a nation's progress. To meet this need, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2016 estimated global, regional, national, and, for selected locations, subnational cause-specific mortality beginning in the year 1980. Here we report an update to that study, making use of newly available data and improved methods. GBD 2017 provides a comprehensive assessment of cause-specific mortality for 282 causes in 195 countries and territories from 1980 to 2017. Methods The causes of death database is composed of vital registration (VR), verbal autopsy (VA), registry, survey, police, and surveillance data. GBD 2017 added ten VA studies, 127 country-years of VR data, 502 cancer-registry country-years, and an additional surveillance country-year. Expansions of the GBD cause of death hierarchy resulted in 18 additional causes estimated for GBD 2017. Newly available data led to subnational estimates for five additional countries Ethiopia, Iran, New Zealand, Norway, and Russia. Deaths assigned International Classification of Diseases (ICD) codes for non-specific, implausible, or intermediate causes of death were reassigned to underlying causes by redistribution algorithms that were incorporated into uncertainty estimation. We used statistical modelling tools developed for GBD, including the Cause of Death Ensemble model (CODErn), to generate cause fractions and cause specific death rates for each location, year, age, and sex. Instead of using UN estimates as in previous versions, GBD 2017 independently estimated population size and fertility rate for all locations. Years of life lost (YLLs) were then calculated as the sum of each death multiplied by the standard life expectancy at each age. All rates reported here are age-standardised. Findings At the broadest grouping of causes of death (Level 1), non-communicable diseases (NC Ds) comprised the greatest fraction of deaths, contributing to 73.4% (95% uncertainty interval [UI] 72.5-74.1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional (CMNN) causes accounted for 186% (17.9-19.6), and injuries 8.0% (7.7-8.2). Total numbers of deaths from NCD causes increased from 2007 to 2017 by 22.7% (21.5-23.9), representing an additional 7.61 million (7. 20-8.01) deaths estimated in 2017 versus 2007. The death rate from NCDs decreased globally by 7.9% (7.08.8). The number of deaths for CMNN causes decreased by 222% (20.0-24.0) and the death rate by 31.8% (30.1-33.3). Total deaths from injuries increased by 2.3% (0-5-4-0) between 2007 and 2017, and the death rate from injuries decreased by 13.7% (12.2-15.1) to 57.9 deaths (55.9-59.2) per 100 000 in 2017. Deaths from substance use disorders also increased, rising from 284 000 deaths (268 000-289 000) globally in 2007 to 352 000 (334 000-363 000) in 2017. Between 2007 and 2017, total deaths from conflict and terrorism increased by 118.0% (88.8-148.6). A greater reduction in total deaths and death rates was observed for some CMNN causes among children younger than 5 years than for older adults, such as a 36.4% (32.2-40.6) reduction in deaths from lower respiratory infections for children younger than 5 years compared with a 33.6% (31.2-36.1) increase in adults older than 70 years. Globally, the number of deaths was greater for men than for women at most ages in 2017, except at ages older than 85 years. Trends in global YLLs reflect an epidemiological transition, with decreases in total YLLs from enteric infections, respirator}, infections and tuberculosis, and maternal and neonatal disorders between 1990 and 2017; these were generally greater in magnitude at the lowest levels of the Socio-demographic Index (SDI). At the same time, there were large increases in YLLs from neoplasms and cardiovascular diseases. YLL rates decreased across the five leading Level 2 causes in all SDI quintiles. The leading causes of YLLs in 1990 neonatal disorders, lower respiratory infections, and diarrhoeal diseases were ranked second, fourth, and fifth, in 2017. Meanwhile, estimated YLLs increased for ischaemic heart disease (ranked first in 2017) and stroke (ranked third), even though YLL rates decreased. Population growth contributed to increased total deaths across the 20 leading Level 2 causes of mortality between 2007 and 2017. Decreases in the cause-specific mortality rate reduced the effect of population growth for all but three causes: substance use disorders, neurological disorders, and skin and subcutaneous diseases. Interpretation Improvements in global health have been unevenly distributed among populations. Deaths due to injuries, substance use disorders, armed conflict and terrorism, neoplasms, and cardiovascular disease are expanding threats to global health. For causes of death such as lower respiratory and enteric infections, more rapid progress occurred for children than for the oldest adults, and there is continuing disparity in mortality rates by sex across age groups. Reductions in the death rate of some common diseases are themselves slowing or have ceased, primarily for NCDs, and the death rate for selected causes has increased in the past decade. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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35. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990-2017: a systematic analysis for the Global Burden of Disease Study 2017
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Eduardo A, Unutzer, Jurgen, Updike, Rachel L, Usman, Muhammad Shariq, Uthman, Olalekan A, Vaduganathan, Muthiah, Vaezi, Afsane, Valdez, Pascual R, Varughese, Santosh, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vosoughi, Kia, Vujcic, Isidora S, Wagnew, Fasil Shiferaw, Waheed, Yasir, Waller, Stephen G, Wang, Yafeng, Wang, Yuan-Pang, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, West, T Eoin, Whiteford, Harvey A, Widecka, Justyna, Wijeratne, Tissa, Wilner, Lauren B, Wilson, Shadrach, Winkler, Andrea Sylvia, Wiyeh, Alison B, Wiysonge, Charles Shey, Wolfe, Charles D A, Woolf, Anthony D, Wu, Shouling, Wu, Yun-Chun, Wyper, Grant M A, Xavier, Deni, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Yahyazadeh Jabbari, Seyed Hossein, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeleke, Ayalew Jejaw, Zenebe, Zerihun Menlkalew, Zhang, Kai, Zhao, Zheng, Zhou, Maigeng, Zodpey, Sanjay, Zucker, Inbar, Vos, Theo, and Murray, Christopher J L
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YLDs ,global burden of disease ,General & Internal Medicine ,Medicine (all) ,prevalence ,incidence ,Human medicine ,global burden of disease, YLDs, incidence, prevalence ,GBD, years lived with disability - Abstract
Background The Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017) includes a comprehensive assessment of incidence, prevalence, and years lived with disability (YLDs) for 354 causes in 195 countries and territories from 1990 to 2017. Previous GBD studies have shown how the decline of mortality rates from 1990 to 2016 has led to an increase in life expectancy, an ageing global population, and an expansion of the non-fatal burden of disease and injury. These studies have also shown how a substantial portion of the world's population experiences non-fatal health loss with considerable heterogeneity among different causes, locations, ages, and sexes. Ongoing objectives of the GBD study include increasing the level of estimation detail, improving analytical strategies, and increasing the amount of high-quality data. Methods We estimated incidence and prevalence for 354 diseases and injuries and 3484 sequelae. We used an updated and extensive body of literature studies, survey data, surveillance data, inpatient admission records, outpatient visit records, and health insurance claims, and additionally used results from cause of death models to inform estimates using a total of 68 781 data sources. Newly available clinical data from India, Iran, Japan, Jordan, Nepal, China, Brazil, Norway, and Italy were incorporated, as well as updated claims data from the USA and new claims data from Taiwan (province of China) and Singapore. We used DisMod-MR 2.1, a Bayesian meta-regression tool, as the main method of estimation, ensuring consistency between rates of incidence, prevalence, remission, and cause of death for each condition. YLDs were estimated as the product of a prevalence estimate and a disability weight for health states of each mutually exclusive sequela, adjusted for comorbidity. We updated the Socio-demographic Index (SDI), a summary development indicator of income per capita, years of schooling, and total fertility rate. Additionally, we calculated differences between male and female YLDs to identify divergent trends across sexes. GBD 2017 complies with the Guidelines for Accurate and Transparent Health Estimates Reporting. Findings Globally, for females, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and haemoglobinopathies and haemolytic anaemias in both 1990 and 2017. For males, the causes with the greatest age-standardised prevalence were oral disorders, headache disorders, and tuberculosis including latent tuberculosis infection in both 1990 and 2017. In terms of YLDs, low back pain, headache disorders, and dietary iron deficiency were the leading Level 3 causes of YLD counts in 1990, whereas low back pain, headache disorders, and depressive disorders were the leading causes in 2017 for both sexes combined. All-cause age-standardised YLD rates decreased by 39% (95% uncertainty interval [UI] 3.1-4. 6) from 1990 to 2017; however, the all-age YLD rate increased by 7.2% (6.0-8.4) while the total sum of global YLDs increased from 562 million (421-723) to 853 million (642-1100). The increases for males and females were similar, with increases in all-age YLD rates of 7.9% (6 6-9. 2) for males and 6.5% (5.4-7.7) for females. We found significant differences between males and females in terms of age-standardised prevalence estimates for multiple causes. The causes with the greatest relative differences between sexes in 2017 included substance use disorders (3018 cases [95% UI 2782-3252] per 100 000 in males vs 1400 [1279-1524] per 100 000 in females), transport injuries (3322 [3082-3583] vs 2336 [2154-2535]), and self-hatin and interpersonal violence (3265 [2943-3630] vs 5643 [5057-6302]). Interpretation Global all-cause age-standardised YLD rates have improved only slightly over a period spanning nearly three decades. However, the magnitude of the non-fatal disease burden has expanded globally, with increasing numbers of people who have a wide spectrum of conditions. A subset of conditions has remained globally pervasive since 1990, whereas other conditions have displayed more dynamic trends, with different ages, sexes, and geographies across the globe experiencing varying burdens and trends of health loss. This study emphasises how global improvements in premature mortality for select conditions have led to older populations with complex and potentially expensive diseases, yet also highlights global achievements in certain domains of disease and injury. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
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- 2018
36. Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016
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Arthur, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayalew, Animut Alebel, Ayele, Henok Tadesse, Ayer, Rakesh, Ayuk, Tambe Betrand, Azzopardi, Peter, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Badali, Hamid, Badawi, Alaa, Banach, Maciej, Banerjee, Amitava, Banstola, Amrit, Barber, Ryan M., Barboza, Miguel A., Barker-Collo, Suzanne L., Bärnighausen, Till, Barquera, Simon, Barrero, Lope H., Bassat, Quique, Basu, Sanjay, Baune, Bernhard T., Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bennett, James R., Bensenor, Isabela M., Berhe, Derbew Fikadu, Bernabé, Eduardo, Bernstein, Robert Steven, Beuran, Mircea, Bhalla, Ashish, Bhatt, Paurvi, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A., Biadgo, Belete, Bijani, Ali, Bikbov, Bori, Birungi, Charle, Biryukov, Stan, Bizuneh, Hailemichael, Bolliger, Ian W., Bolt, Kaylin, Bou-Orm, Ibrahim R., Bozorgmehr, Kayvan, Brady, Oliver Jerome, Brazinova, Alexandra, Breitborde, Nicholas J.K., Brenner, Hermann, Britton, Gabrielle, Brugha, Traolach S., Butt, Zahid A., Cahuana-Hurtado, Lucero, Campos-Nonato, Ismael Ricardo, Campuzano, Julio Cesar, Car, Josip, Car, Mate, Cárdenas, Rosario, Carrero, Juan Jesu, Carvalho, Felix, Castañeda-Orjuela, Carlos A., Castillo Rivas, Jacqueline, Catalá-López, Ferrán, Cercy, Kelly, Chalek, Julian, Chang, Hsing-Yi, Chang, Jung-Chen, Chattopadhyay, Aparajita, Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chisumpa, Vesper Hichilombwe, Choi, Jee-Young J., Christensen, Hanne, Christopher, Devasahayam Jesuda, Chung, Sheng-Chia, Ciobanu, Liliana G., Cirillo, Massimo, Colombara, Danny, Conti, Sara, Cooper, Cyru, Cornaby, Leslie, Cortesi, Paolo Angelo, Cortinovis, Monica, Costa Pereira, Alexandre, Cousin, Ewerton, Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Daba, Alemneh Kabeta, Dachew, Berihun Assefa, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dargan, Paul I., Daryani, Ahmad, Daryani, Maryam, Das, Jai, Das, Siddharth Kumar, Das Neves, José, Davis Weaver, Nicole, Davletov, Kairat, De Courten, Barbora, De Leo, Diego, De Neve, Jan-Walter, Dellavalle, Robert P., Demoz, Gebre, Deribe, Kebede, Des Jarlais, Don C., Dey, Subhojit, Dharmaratne, Samath D., Dhimal, Meghnath, Djalalinia, Shirin, Doku, David Teye, Dolan, Kate, Dorsey, E. Ray, Dos Santos, Kadine Priscila Bender, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duncan, Bruce Bartholow, Echko, Michelle, Edessa, Dumessa, Edvardsson, David, Ehrlich, Joshua R., Eldrenkamp, Erika, El-Khatib, Ziad, Endres, Matthia, Endries, Aman Yesuf, Eshrati, Babak, Eskandarieh, Sharareh, Esteghamati, Alireza, Fakhar, Mahdi, Farag, Tamer, Faramarzi, Mahbobeh, Faraon, Emerito Jose Aquino, Faro, André, Farzadfar, Farshad, Fatusi, Adesegun, Fazeli, Mir Sohail, Feigin, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Fereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, João C., Fijabi, Daniel Obadare, Filip, Irina, Fischer, Florian, Fitzmaurice, Christina, Flaxman, Abraham D., Flor, Luisa Sorio, Foigt, Nataliya, Foreman, Kyle J., Frostad, Joseph J., Fürst, Thoma, Futran, Neal D., Gakidou, Emmanuela, Gallus, Silvano, Gambashidze, Ketevan, Gamkrelidze, Amiran, Ganji, Morsaleh, Gebre, Abadi Kahsu, Gebrehiwot, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gelaw, Yalemzewod Assefa, Geleijnse, Johanna M., Geremew, Demeke, Gething, Peter W., Ghadimi, Reza, Ghasemi Falavarjani, Khalil, Ghasemi-Kasman, Maryam, Gill, Paramjit Singh, Giref, Ababi Zergaw, Giroud, Maurice, Gishu, Melkamu Dedefo, Giussani, Giorgia, Godwin, William W., Goli, Sriniva, Gomez-Dantes, Hector, Gona, Philimon N., Goodridge, Amador, Gopalani, Sameer Vali, Goryakin, Yevgeniy, Goulart, Alessandra Carvalho, Grada, Ayman, Griswold, Max, Grosso, Giuseppe, Gugnani, Harish Chander, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Tanush, Gupta, Tarun, Gupta, Vipin, Haagsma, Juanita A., Hachinski, Vladimir, Hafezi-Nejad, Nima, Hailu, Gessessew Bugssa, Hamadeh, Randah Ribhi, Hamidi, Samer, Hankey, Graeme J., Harb, Hilda L., Harewood, Heather C., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hassen, Hamid Yimam, Havmoeller, Rasmu, Hawley, Caitlin, Hay, Simon I., He, Jiawei, Hearps, Stephen J.C., Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henry, Nathaniel J., Herrera Ballesteros, Victor Hugo, Herteliu, Claudiu, Hibstu, Desalegn Tsegaw, Hiluf, Molla Kahssay, Hoek, Hans W., Homaie Rad, Enayatollah, Horita, Nobuyuki, Hosgood, H. Dean, Hosseini, Mostafa, Hosseini, Seyed Reza, Hostiuc, Mihaela, Hostiuc, Sorin, Hoy, Damian G., Hsairi, Mohamed, Htet, Aung Soe, Hu, Guoqing, Huang, John J., Iburg, Kim Moesgaard, Idris, Fachmi, Igumbor, Ehimario Uche, Ikeda, Chad, Ileanu, Bogdan Vasile, Ilesanmi, Olayinka S., Innos, Kaire, Irvani, Seyed Sina Naghibi, Irvine, Caleb M.S., Islami, Farhad, Jacobs, Troy A., Jacobsen, Kathryn H., Jahanmehr, Nader, Jain, Rajesh, Jain, Sudhir Kumar, Jakovljevic, Mihajlo M., Jalu, Moti Tolera, Jamal, Amr A., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jha, Ravi Prakash, Jha, Vivekanand, Józwiak, Jacek, John, Oommen, Johnson, Sarah Charlotte, Jonas, Jost B., Joshua, Vasna, Jürisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Kar, Chittaranjan, Karanikolos, Marina, Karch, André, Karema, Corine Kakizi, Karimi, Seyed M., Kasaeian, Amir, Kassa, Dessalegn Haile, Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kawakami, Norito, Kazanjan, Konstantin, Kebede, Seifu, Keiyoro, Peter Njenga, Kemp, Grant Rodger, Kengne, Andre Pascal, Kereselidze, Maia, Ketema, Ezra Belay, Khader, Yousef Saleh, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Gulfaraz, Khan, Md Nuruzzaman, Khan, Muhammad Ali, Khanal, Mukti Nath, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah Tawfih Abdullah, Khosravi, Ardeshir, Khubchandani, Jagdish, Kibret, Getiye Dejenu, Kiirithio, Daniel Ngari, Kim, Daniel, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohanne, Kinra, Sanjay, Kisa, Adnan, Kissoon, Niranjan, Kochhar, Sonali, Kokubo, Yoshihiro, Kopec, Jacek A., Kosen, Soewarta, Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael, Krishan, Kewal, Krohn, Kristopher J., Kuate Defo, Barthelemy, Kumar, G. Anil, Kumar, Pushpendra, Kutz, Michael, Kuzin, Igor, Kyu, Hmwe H., Lad, Deepesh Pravinkumar, Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lam, Hilton, Lan, Qing, Lang, Justin J., Lansingh, Van C., Lansky, Sonia, Larsson, Ander, Latifi, Arman, Lazarus, Jeffrey Victor, Leasher, Janet L., Lee, Paul H., Legesse, Yirga, Leigh, Jame, Leshargie, Cheru Tesema, Leta, Samson, Leung, Janni, Leung, Ricky, Levi, Miriam, Li, Yongmei, Liang, Juan, Liben, Misgan Legesse, Lim, Lee-Ling, Lim, Stephen S., Lind, Margaret, Linn, Shai, Listl, Stefan, Liu, Patrick Y., Liu, Shiwei, Lodha, Rakesh, Lopez, Alan D., Lorch, Scott A., Lorkowski, Stefan, Lotufo, Paulo A., Lucas, Timothy C.D., Lunevicius, Raimunda, Lurton, Grégoire, Lyons, Ronan A., Maalouf, Fadi, Macarayan, Erlyn Rachelle King, Mackay, Mark T., Maddison, Emilie R., Madotto, Fabiana, Magdy Abd El Razek, Hassan, Magdy Abd El Razek, Mohammed, Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malhotra, Rajesh, Malta, Deborah Carvalho, Mamun, Abdullah A., Manguerra, Helena, Manhertz, Treh, Mansournia, Mohammad Ali, Mantovani, Lorenzo G., Manyazewal, Tsegahun, Mapoma, Chabila C., Margono, Christopher, Martinez-Raga, Jose, Martins, Sheila Cristina Ourique, Martins-Melo, Francisco Rogerlândio, Martopullo, Ira, März, Winfried, Massenburg, Benjamin Ballard, Mathur, Manu Raj, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Colm, McGrath, John J., McKee, Martin, Mehata, Suresh, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Meier, Toni, Mejia-Rodriguez, Fabiola, Meles, Kidanu Gebremariam, Melku, Mulugeta, Memiah, Peter, Memish, Ziad A., Mendoza, Walter, Mengiste, Degu Abate, Mengistu, Desalegn Tadese, Menota, Bereket Gebremichael, Mensah, George A., Meretoja, Atte, Meretoja, Tuomo J., Mezgebe, Haftay Berhane, Miazgowski, Tomasz, Micha, Renata, Milam, Robert, Millear, Anoushka, Miller, Ted R., Mini, G.K., Minnig, Shawn, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke, Mitchell, Philip B., Mlashu, Fitsum Weldegebreal, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammadibakhsh, Roghayeh, Mohammed, Ebrahim, Mohammed, Mohammed A., Mohammed, Shafiu, Mokdad, Ali H., Mola, Glen Liddell D., Molokhia, Mariam, Momeniha, Fatemeh, Monasta, Lorenzo, Montañez Hernandez, Julio Cesar, Moosazadeh, Mahmood, Moradi-Lakeh, Maziar, Moraga, Paula, Morawska, Lidia, Moreno Velasquez, Ilai, Mori, Rintaro, Morrison, Shane D., Moses, Mark, Mousavi, Seyyed Meysam, Mueller, Ulrich O., Murhekar, Manoj, Murthy, Gudlavalleti Venkata Satyanarayana, Murthy, Sriniva, Musa, Jonah, Musa, Kamarul Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nagata, Chie, Nagel, Gabriele, Naghavi, Mohsen, Naheed, Aliya, Naik, Gurudatta A., Naik, Nitish, Najafi, Farid, Naldi, Luigi, Nangia, Vinay, Nansseu, Jobert Richie Njingang, Narayan, K.M. Venkat, Nascimento, Bruno Ramo, Negoi, Ionut, Negoi, Ruxandra Irina, Newton, Charles R., Ngunjiri, Josephine Wanjiku, Nguyen, Grant, Nguyen, Long, Nguyen, Trang Huyen, Nichols, Emma, Ningrum, Dina Nur Anggraini, Nolte, Ellen, Nong, Vuong Minh, Norheim, Ole F., Norrving, Bo, Noubiap, Jean Jacques N., Nyandwi, Alypio, Obermeyer, Carla Makhlouf, Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew Toyin, Olagunju, Tinuke Oluwasefunmi, Olivares, Pedro R., De Oliveira, Patricia Pereira Vasconcelo, Olsen, Helen E., Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin, Opio, John Nelson, Oren, Eyal, Ortega-Altamirano, Doris V., Ortiz, Alberto, Ozdemir, Raziye, Pa, Mahesh, Pain, Amanda W., Palone, Marcos Roberto Tovani, Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj D., Park, Eun-Kee, Parsian, Hadi, Patel, Teja, Pati, Sanghamitra, Patil, Snehal T., Patle, Ajay, Patton, George C., Paturi, Vishnupriya Rao, Paudel, Deepak, De Moares Pedroso, Marcel, Pedroza, Sandra P., Pereira, David M., Perico, Norberto, Peterson, Hannah, Petzold, Max, Peykari, Niloofar, Phillips, Michael Robert, Piel, Frédéric B., Pigott, David M., Pillay, Julian David, Piradov, Michael A., Polinder, Suzanne, Pond, Constance D., Postma, Maarten J., Pourmalek, Farshad, Prakash, Swayam, Prakash, V., Prasad, Narayan, Prasad, Noela Marie, Purcell, Caroline, Qorbani, Mostafa, Quintana, Hedley Knewjen, Radfar, Amir, Rafay, Anwar, Rafiei, Alireza, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Muhammad Aziz, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Raju, Sree Bhushan, Ram, Usha, Rana, Saleem M., Rankin, Zane, Rasella, Davide, Rawaf, David Laith, Rawaf, Salman, Ray, Sarah E., Razo-García, Christian Aspacia, Reddy, Priscilla, Reiner, Robert C., Reis, Cesar, Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M.N., Resnikoff, Serge, Rezaei, Satar, Rezai, Mohammad Sadegh, Ribeiro, Antonio L., Rios Blancas, 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Sd, Aljunid, Sm, Alomari, Ma, Altirkawi, Ka, Amare, At, Amoako, Ya, Andrei, Cl, Antonio, Cat, Araújo, Vem, Aryal, Kk, Asfaw, Et, Asgedom, Sw, Asghar, Rj, Ashebir, Mm, Asseffa, Na, Atey, Tm, Atre, Sr, Avokpaho, Efga, Ayala Quintanilla, Bp, Ayalew, Aa, Ayele, Ht, Ayuk, Tb, Babalola, Tk, Barber, Rm, Barboza, Ma, Barker-Collo, Sl, Barrero, Lh, Baune, Bt, Bekele, Bb, Belachew, Ab, Belay, Sa, Belay, Ya, Bell, Ml, Bello, Ak, Bennett, Da, Bennett, Jr, Bensenor, Im, Berhe, Df, Bhutta, Za, Bolliger, Iw, Bou-Orm, Ir, Brady, Oj, Breitborde, Njk, Butt, Za, Campos-Nonato, Ir, Campuzano, Jc, Carrero, Jj, Castañeda-Orjuela, Ca, Chang, Hy, Chang, Jc, Chiang, Pp, Chisumpa, Vh, Choi, Jj, Christopher, Dj, Chung, Sc, Ciobanu, Lg, Cortesi, Pa, Criqui, Mh, Cromwell, Ea, Crump, Ja, Daba, Ak, Dachew, Ba, Dadi, Af, Dargan, Pi, Das, Sk, De Neve, Jw, Dellavalle, Rp, Des Jarlais, Dc, Dharmaratne, Sd, Doku, Dt, Dorsey, Er, Dos Santos, Kpb, Doyle, Ke, Driscoll, Tr, Duncan, Bb, Ehrlich, Jr, El-Khatib, Zz, Endries, Ay, Faraon, Eja, Feigin, Vl, Feigl, Ab, Fereshtehnejad, Sm, Fernandes, Jc, Fijabi, Do, Flaxman, Ad, Foreman, Kj, Frostad, Jj, Futran, Nd, Gebre, Ak, Gebrehiwot, Tt, Gebremedhin, At, Gelaw, Ya, Geleijnse, Jm, Gething, Pw, Giref, Az, Gishu, Md, Godwin, Ww, Gona, Pn, Gopalani, Sv, Goulart, Ac, Gugnani, Hc, Haagsma, Ja, Hailu, Gb, Hamadeh, Rr, Hankey, Gj, Harb, Hl, Harewood, Hc, Haro, Jm, Hassen, Hy, Hay, Si, Hearps, Sjc, Hegazy, Mi, Henry, Nj, Herrera Ballesteros, Vh, Hibstu, Dt, Hiluf, Mk, Hoek, Hw, Hosgood, Hd, Hosseini, Sr, Hoy, Dg, Huang, Jj, Iburg, Km, Igumbor, Eu, Ileanu, Bv, Irvani, Ssn, Irvine, Cm, Jacobs, Ta, Jacobsen, Kh, Jain, Sk, Jakovljevic, Mb, Jalu, Mt, Jamal, Aa, Jayatilleke, Au, Jha, Rp, Johnson, Sc, Jonas, Jb, Karema, Ck, Karimi, Sm, Kassa, Dh, Kassa, Gm, Kassa, Td, Kassebaum, Nj, Katikireddi, Sv, Keiyoro, Pn, Kemp, Gr, Kengne, Ap, Ketema, Eb, Khafaie, Ma, Khalil, Ia, Khan, Ea, Khan, Mn, Khan, Ma, Khanal, Mn, Khang, Yh, Khater, Mm, Khoja, Ata, Kibret, Gd, Kiirithio, Dn, Kim, Yj, Kimokoti, Rw, Kopec, Ja, Koul, Pa, Krohn, Kj, Kumar, Ga, Kyu, Hh, Lad, Dp, Lal, Dk, Lang, Jj, Lansingh, Vc, Lazarus, Jv, Leasher, Jl, Lee, Ph, Leshargie, Ct, Liben, Ml, Lim, Ll, Lopez, Ad, Lorch, Sa, Lotufo, Pa, Lucas, Tcd, Lyons, Ra, Macarayan, Erk, Mackay, Mt, Maddison, Er, Malta, Dc, Mamun, Aa, Mansournia, Ma, Mantovani, Lg, Mapoma, Cc, Martins, Sco, Martins-Melo, Fr, Massenburg, Bb, Mathur, Mr, Maulik, Pk, Mcgrath, Jj, Mehta, Km, Meles, Kg, Memish, Za, Mengiste, Da, Mengistu, Dt, Menota, Bg, Mensah, Ga, Meretoja, Tj, Mezgebe, Hb, Miller, Tr, Mini, Gk, Mirrakhimov, Em, Mitchell, Pb, Mlashu, Fw, Mohammad, Ka, Mohammed, Ma, Mokdad, Ah, Mola, Gl, Montañez Hernandez, Jc, Morrison, Sd, Mousavi, Sm, Mueller, Uo, Murthy, Gv, Musa, Ki, Naik, Ga, Nansseu, Jrn, Narayan, Kv, Nascimento, Br, Negoi, Ri, Newton, Cr, Ngunjiri, Jw, Nguyen, Th, Ningrum, Dna, Nong, Vm, Norheim, Of, Noubiap, Jjn, Obermeyer, Cm, Ogbo, Fa, Oh, Ih, Olagunju, At, Olagunju, To, Olivares, Pr, Oliveira, Ppv, Olsen, He, Olusanya, Bo, Olusanya, Jo, Opio, Jn, Ortega-Altamirano, Dv, Pain, Aw, Palone, Mrt, Pandian, Jd, Park, Ek, Patil, St, Patton, Gc, Paturi, Vr, Pedroso, Mm, Pedroza, Sp, Pereira, Dm, Phillips, Mr, Piel, Fb, Pigott, Dm, Pillay, Jd, Piradov, Ma, Pond, Cd, Postma, Mj, Prasad, Nm, Quintana, Hk, Rahman, Ma, Rahman, Su, Rai, Rk, Raju, Sb, Rana, Sm, Rawaf, Dl, Ray, Se, Razo-García, Ca, Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Ribeiro, Al, Rios Blancas, Mj, Rivera, Ja, Roth, Ga, Ruhago, Gm, Sabde, Yd, Sahraian, Ma, Saldanha, Rf, Salomon, Ja, Samy, Am, Sanabria, Jr, Sancheti, Pk, Sanchez-Niño, Md, Santric Milicevic, Mm, Sarker, Ar, Saylan, Mi, Schmidt, Mi, Schneider, Ijc, Schumacher, Ae, Schutte, Ae, Schwebel, Dc, Sepanlou, Sg, Servan-Mori, Ee, Shaikh, Ma, Shariful Islam, Sm, Shfare, Mt, Shrime, Mg, Shukla, Sr, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silveira, Dga, Singh, Ja, Singh, Np, Sinha, Dn, Sinke, Ah, Soares Filho, Am, Sobaih, Bha, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Stein, Dj, Stokes, Ma, Sufiyan, Mb, Suliankatchi, Ra, Sunguya, Bf, Sur, Pj, Sykes, Bl, Sylaja, Pn, Tadakamadla, Sk, Tadesse, Ah, Taffere, Gr, Tariku, At, Temsah, Mh, Tesema, Ag, Tesfaye, Dj, Thompson, Mj, To, Qg, Tran, Bx, Tran, Kb, Tripathy, Sp, Tuem, Kb, Ukwaja, Kn, Uthman, Oa, Uzochukwu, Bsc, Valdez, Pr, van Boven, Jfm, Vladimirov, Sk, Vlassov, Vv, Vollset, Se, Wallin, Mt, Walson, Jl, Wang, Yp, Wassie, Mm, Weaver, Mr, Weintraub, Rg, Weldegwergs, Kg, West, Te, White, Rg, Whiteford, Ha, Wolfe, Cd, Wondimkun, Ya, Wyper, Gma, Yan, Ll, Yimer, Nb, Yirsaw, Bd, Yoon, Sj, Younis, Mz, Zaki, Me, Zaman, Sb, Zenebe, Zm, Zimsen, Srm, Zuhlke, Lj, Murray, Cjl, and Lozano, R.
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Peformance ,Coverage ,Dánartíðni ,Lífslíkur ,Life expectancy ,GBD ,Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0–100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best) ,universal health coverage ,Article ,access quality health care ,health care access and quality index ,Nations ,Healthcare Acce ,Cause-specific mortality ,Psychology ,Healthcare Access and Quality Index ,Mælitæki ,States ,Medicine (all) ,Health care ,Þjóðir ,Public Health, Global Health, Social Medicine and Epidemiology ,Quality ,Heilbrigðisþjónusta ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Sálfræði ,Indicator ,Amenable mortality ,Transition ,we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0–100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97·1 (95% UI 95·8–98·1) in Iceland, followed by 96·6 (94·9–97·9) in Norway and 96·1 (94·5–97·3) in the Netherlands, to values as low as 18·6 (13·1–24·4) in the Central African Republic, 19·0 (14·3–23·7) in Somalia, and 23·4 (20·2–26·8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91·5 (89·1–93·6) in Beijing to 48·0 (43·4–53·2) in Tibet (a 43·5-point difference), while India saw a 30·8-point disparity, from 64·8 (59·6–68·8) in Goa to 34·0 (30·3–38·1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4·8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20·9-point to 17·0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17·2-point to 20·4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage hinges upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view—and subsequent provision—of quality health care for all populations ,Trends ,Inequalities - Abstract
Background A key component of achieving universal health coverage is ensuring that all populations have access to quality health care. Examining where gains have occurred or progress has faltered across and within countries is crucial to guiding decisions and strategies for future improvement. We used the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) to assess personal health-care access and quality with the Healthcare Access and Quality (HAQ) Index for 195 countries and territories, as well as subnational locations in seven countries, from 1990 to 2016. Methods Drawing from established methods and updated estimates from GBD 2016, we used 32 causes from which death should not occur in the presence of effective care to approximate personal health-care access and quality by location and over time. To better isolate potential effects of personal health-care access and quality from underlying risk factor patterns, we risk-standardised cause-specific deaths due to non-cancers by location-year, replacing the local joint exposure of environmental and behavioural risks with the global level of exposure. Supported by the expansion of cancer registry data in GBD 2016, we used mortality-to-incidence ratios for cancers instead of risk-standardised death rates to provide a stronger signal of the effects of personal health care and access on cancer survival. We transformed each cause to a scale of 0-100, with 0 as the first percentile (worst) observed between 1990 and 2016, and 100 as the 99th percentile (best); we set these thresholds at the country level, and then applied them to subnational locations. We applied a principal components analysis to construct the HAQ Index using all scaled cause values, providing an overall score of 0-100 of personal health-care access and quality by location over time. We then compared HAQ Index levels and trends by quintiles on the Socio-demographic Index (SDI), a summary measure of overall development. As derived from the broader GBD study and other data sources, we examined relationships between national HAQ Index scores and potential correlates of performance, such as total health spending per capita. Findings In 2016, HAQ Index performance spanned from a high of 97.1 (95% UI 95.8-98.1) in Iceland, followed by 96.6 (94.9-97.9) in Norway and 96.1 (94.5-97.3) in the Netherlands, to values as low as 18.6 (13.1-24.4) in the Central African Republic, 19.0 (14.3-23.7) in Somalia, and 23.4 (20.2-26.8) in Guinea-Bissau. The pace of progress achieved between 1990 and 2016 varied, with markedly faster improvements occurring between 2000 and 2016 for many countries in sub-Saharan Africa and southeast Asia, whereas several countries in Latin America and elsewhere saw progress stagnate after experiencing considerable advances in the HAQ Index between 1990 and 2000. Striking subnational disparities emerged in personal health-care access and quality, with China and India having particularly large gaps between locations with the highest and lowest scores in 2016. In China, performance ranged from 91.5 (89.1-936) in Beijing to 48.0 (43.4-53.2) in Tibet (a 43.5-point difference), while India saw a 30.8-point disparity, from 64.8 (59.6-68.8) in Goa to 34.0 (30.3-38.1) in Assam. Japan recorded the smallest range in subnational HAQ performance in 2016 (a 4.8-point difference), whereas differences between subnational locations with the highest and lowest HAQ Index values were more than two times as high for the USA and three times as high for England. State-level gaps in the HAQ Index in Mexico somewhat narrowed from 1990 to 2016 (from a 20.9-point to 17.0-point difference), whereas in Brazil, disparities slightly increased across states during this time (a 17.2-point to 20.4-point difference). Performance on the HAQ Index showed strong linkages to overall development, with high and high-middle SDI countries generally having higher scores and faster gains for non-communicable diseases. Nonetheless, countries across the development spectrum saw substantial gains in some key health service areas from 2000 to 2016, most notably vaccine-preventable diseases. Overall, national performance on the HAQ Index was positively associated with higher levels of total health spending per capita, as well as health systems inputs, but these relationships were quite heterogeneous, particularly among low-to-middle SDI countries. Interpretation GBD 2016 provides a more detailed understanding of past success and current challenges in improving personal health-care access and quality worldwide. Despite substantial gains since 2000, many low-SDI and middle-SDI countries face considerable challenges unless heightened policy action and investments focus on advancing access to and quality of health care across key health services, especially non-communicable diseases. Stagnating or minimal improvements experienced by several low-middle to high-middle SDI countries could reflect the complexities of re-orienting both primary and secondary health-care services beyond the more limited foci of the Millennium Development Goals. Alongside initiatives to strengthen public health programmes, the pursuit of universal health coverage upon improving both access and quality worldwide, and thus requires adopting a more comprehensive view and subsequent provision of quality health care for all populations., Bill & Melinda Gates Foundation. Barbora de Courten is supported by a National Heart Foundation Future Leader Fellowship (100864). Ai Koyanagi’s work is supported by the Miguel Servet contract financed by the CP13/00150 and PI15/00862 projects, integrated into the National R + D + I and funded by the ISCIII —General Branch Evaluation and Promotion of Health Research—and the European Regional Development Fund (ERDF-FEDER). Alberto Ortiz was supported by Spanish Government (Instituto de Salud Carlos III RETIC REDINREN RD16/0019 FEDER funds). Ashish Awasthi acknowledges funding support from Department of Science and Technology, Government of India through INSPIRE Faculty scheme Boris Bikbov has received funding from the European Union’s Horizon 2020 research and innovation programme under Marie Sklodowska-Curie grant agreement No. 703226. Boris Bikbov acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Panniyammakal Jeemon acknowledges support from the clinical and public health intermediate fellowship from the Wellcome Trust and Department of Biotechnology, India Alliance (2015–20). Job F M van Boven was supported by the Department of Clinical Pharmacy & Pharmacology of the University Medical Center Groningen, University of Groningen, Netherlands. Olanrewaju Oladimeji is an African Research Fellow hosted by Human Sciences Research Council (HSRC), South Africa and he also has honorary affiliations with Walter Sisulu University (WSU), Eastern Cape, South Africa and School of Public Health, University of Namibia (UNAM), Namibia. He is indeed grateful for support from HSRC, WSU and UNAM. EUI is supported in part by the South African National Research Foundation (NRF UID: 86003). Ulrich Mueller acknowledges funding by the German National Cohort Study grant No 01ER1511/D, Gabrielle B Britton is supported by Secretaría Nacional de Ciencia, Tecnología e Innovación and Sistema Nacional de Investigación de Panamá. Giuseppe Remuzzi acknowledges that the work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Behzad Heibati would like to acknowledge Air pollution Research Center, Iran University of Medical Sciences (IUMS), Tehran, Iran. Syed Aljunid acknowledges the National University of Malaysia for providing the approval to participate in this GBD Project. Azeem Majeed and Imperial College London are grateful for support from the Northwest London National Insititute of Health Research (NIHR) Collaboration for Leadership in Applied Health Research & Care. Tambe Ayuk acknowledges the Institute of Medical Research and Medicinal Plant Studies for office space provided. José das Neves was supported in his contribution to this work by a Fellowship from Fundação para a Ciência e a Tecnologia, Portugal (SFRH/BPD/92934/2013). João Fernandes gratefully acknowledges funding from FCT–Fundação para a Ciência e a Tecnologia (grant number UID/Multi/50016/2013). Jan-Walter De Neve was supported by the Alexander von Humboldt Foundation. Kebede Deribe is funded by a Wellcome Trust Intermediate Fellowship in Public Health and Tropical Medicine (201900). Kazem Rahimi was supported by grants from the Oxford Martin School, the NIHR Oxford BRC and the RCUK Global Challenges Research Fund. Laith J Abu-Raddad acknowledges the support of Qatar National Research Fund (NPRP 9-040-3-008) who provided the main funding for generating the data provided to the GBD-IHME effort. Liesl Zuhlke is funded by the national research foundation of South Africa and the Medical Research Council of South Africa. Monica Cortinovis acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group. Chuanhua Yu acknowleges support from the National Natural Science Foundation of China (grant number 81773552 and grant number 81273179) Norberto Perico acknowledges that work related to this paper has been done on behalf of the GBD Genitourinary Disease Expert Group. Charles Shey Wiysonge’s work is supported by the South African Medical Research Council and the National Research Foundation of South Africa (grant numbers 106035 and 108571). John J McGrath is supported by grant APP1056929 from the John Cade Fellowship from the National Health and Medical Research Council and the Danish National Research Foundation (Niels Bohr Professorship). Quique Bassat is an ICREA (Catalan Institution for Research and Advanced Studies) research professor at ISGlobal. Richard G White is funded by the UK MRC and the UK Department for International Development (DFID) under the MRC/DFID Concordat agreement that is also part of the EDCTP2 programme supported by the European Union (MR/P002404/1), the Bill & Melinda Gates Foundation (TB Modelling and Analysis Consortium: OPP1084276/OPP1135288, CORTIS: OPP1137034/OPP1151915, Vaccines: OPP1160830), and UNITAID (4214-LSHTM-Sept15; PO 8477-0-600). Rafael Tabarés-Seisdedos was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI17/00719 from ISCIII-FEDER. Mihajlo Jakovljevic acknowleges contribution from the Serbian Ministry of Education Science and Technological Development of the Republic of Serbia (grant OI 175 014). Shariful Islam is funded by a Senior Fellowship from Institute for Physical Activity and Nutrition, Deakin University and received career transition grants from High Blood Pressure Research Council of Australia. Sonia Saxena is funded by various grants from the NIHR. Stefanos Tyrovolas was supported by the Foundation for Education and European Culture, the Sara Borrell postdoctoral program (reference number CD15/00019 from the Instituto de Salud Carlos III (ISCIII–Spain) and the Fondos Europeo de Desarrollo Regional. Stefanos was awarded with a 6 months visiting fellowship funding at IHME from M-AES (reference no. MV16/00035 from the Instituto de Salud Carlos III). S Vittal Katikreddi was funded by a NHS Research Scotland Senior Clinical Fellowship (SCAF/15/02), the MRC (MC_UU_12017/13 & MC_ UU_12017/15) and the Scottish Government Chief Scientist Office (SPHSU13 & SPHSU15). Traolach S Brugha has received funding from NHS Digital UK to collect data used in this study. The work of Hamid Badali was financially supported by Mazandaran University of Medical Sciences, Sari, Iran. The work of Stefan Lorkowski is funded by the German Federal Ministry of Education and Research (nutriCARD, Grant agreement number 01EA1411A). Mariam Molokhia’s research was supported by the National Institute for Health Research (NIHR) Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London. The views expressed are those of the author(s) and not necessarily those of the NHS, the NIHR or the Department of Health. We also thank the countless individuals who have contributed to GBD 2016 in various capacities.
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- 2018
37. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017
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Dicker, Daniel, Nguyen, Grant, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M, Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Foad, Abdela, Jemal, Abdelalim, Ahmed, Abdel-Rahman, Omar, Abdi, Alireza, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abdurahman, Ahmed Abdulahi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abebo, Teshome Abuka, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen ME, Accrombessi, Manfred Mario Kokou, Acharya, Pawan, Adebayo, Oladimeji M, Adedeji, Isaac Akinkunmi, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adetokunboh, Olatunji O, Adhena, Beyene Meressa, Adhikari, Tara Ballav, Adib, Mina G, Adou, Arsène Kouablan, Adsuar, Jose C, Afarideh, Mohsen, Afshin, Ashkan, Agarwal, Gina, Aggarwal, Rakesh, Aghayan, Sargis Aghasi, Agrawal, Sutapa, Agrawal, Anurag, Ahmadi, Mehdi, Ahmadi, Alireza, Ahmadieh, Hamid, Ahmed, Mohamed Lemine Cheikh brahim, Ahmed, Sayem, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Eddine, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alebel, Animut, Aleman, Alicia V, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Anlay, Degefaye Zelalem, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna K, Asadi-Lari, Mohsen, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Ataro, Zerihun, Atey, Tesfay Mehari Mehari, Athari, Seyyed Shamsadin, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Attia, Engi F, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Awuah, Baffour, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Ayuk, Tambe B, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barquera, Simon, Barrero, Lope H, Basaleem, Huda, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Baune, Bernhard T, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Ezra, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, 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Child mortality ,Alnæmi ,Dánartíðni ,Heilsufar ,GBD ,Börn ,Dauði ,Almennar lyflækningar ,Fullorðnir ,General & Internal Medicine ,parasitic diseases ,Psychology ,age-specific mortality ,Estimating adult mortality ,Medicine (all) ,HIV ,11 Medical And Health Sciences ,General Medicine ,All-cause mortality ,humanities ,Countries ,Death ,mortality, national ,Sálfræði ,Health ,GBD, mortality ,Human medicine ,Trends - Abstract
The content is solely the responsibility of the authors and does not necessarily represent the official views of the funders. Data for this research was provided by MEASURE Evaluation, funded by the United States Agency for International Development (USAID). Views expressed do not necessarily reflect those of USAID, the US Government, or MEASURE Evaluation. The Palestinian Central Bureau of Statistics granted the researchers access to relevant data in accordance with licence no. SLN2014-3-170, after subjecting data to processing aiming to preserve the confidentiality of individual data in accordance with the General Statistics Law-2000. The researchers are solely responsible for the conclusions and inferences drawn upon available data., Background Assessments of age-specific mortality and life expectancy have been done by the UN Population Division, Department of Economics and Social Affairs (UNPOP), the United States Census Bureau, WHO, and as part of previous iterations of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD). Previous iterations of the GBD used population estimates from UNPOP, which were not derived in a way that was internally consistent with the estimates of the numbers of deaths in the GBD. The present iteration of the GBD, GBD 2017, improves on previous assessments and provides timely estimates of the mortality experience of populations globally. Methods The GBD uses all available data to produce estimates of mortality rates between 1950 and 2017 for 23 age groups, both sexes, and 918 locations, including 195 countries and territories and subnational locations for 16 countries. Data used include vital registration systems, sample registration systems, household surveys (complete birth histories, summary birth histories, sibling histories), censuses (summary birth histories, household deaths), and Demographic Surveillance Sites. In total, this analysis used 8259 data sources. Estimates of the probability of death between birth and the age of 5 years and between ages 15 and 60 years are generated and then input into a model life table system to produce complete life tables for all locations and years. Fatal discontinuities and mortality due to HIV/AIDS are analysed separately and then incorporated into the estimation. We analyse the relationship between age-specific mortality and development status using the Socio-demographic Index, a composite measure based on fertility under the age of 25 years, education, and income. There are four main methodological improvements in GBD 2017 compared with GBD 2016: 622 additional data sources have been incorporated; new estimates of population, generated by the GBD study, are used; statistical methods used in different components of the analysis have been further standardised and improved; and the analysis has been extended backwards in time by two decades to start in 1950. Findings Globally, 18·7% (95% uncertainty interval 18·4–19·0) of deaths were registered in 1950 and that proportion has been steadily increasing since, with 58·8% (58·2–59·3) of all deaths being registered in 2015. At the global level, between 1950 and 2017, life expectancy increased from 48·1 years (46·5–49·6) to 70·5 years (70·1–70·8) for men and from 52·9 years (51·7–54·0) to 75·6 years (75·3–75·9) for women. Despite this overall progress, there remains substantial variation in life expectancy at birth in 2017, which ranges from 49·1 years (46·5–51·7) for men in the Central African Republic to 87·6 years (86·9–88·1) among women in Singapore. The greatest progress across age groups was for children younger than 5 years; under-5 mortality dropped from 216·0 deaths (196·3–238·1) per 1000 livebirths in 1950 to 38·9 deaths (35·6–42·83) per 1000 livebirths in 2017, with huge reductions across countries. Nevertheless, there were still 5·4 million (5·2–5·6) deaths among children younger than 5 years in the world in 2017. Progress has been less pronounced and more variable for adults, especially for adult males, who had stagnant or increasing mortality rates in several countries. The gap between male and female life expectancy between 1950 and 2017, while relatively stable at the global level, shows distinctive patterns across super-regions and has consistently been the largest in central Europe, eastern Europe, and central Asia, and smallest in south Asia. Performance was also variable across countries and time in observed mortality rates compared with those expected on the basis of development. Interpretation This analysis of age-sex-specific mortality shows that there are remarkably complex patterns in population mortality across countries. The findings of this study highlight global successes, such as the large decline in under-5 mortality, which reflects significant local, national, and global commitment and investment over several decades. However, they also bring attention to mortality patterns that are a cause for concern, particularly among adult men and, to a lesser extent, women, whose mortality rates have stagnated in many countries over the time period of this study, and in some cases are increasing., Research reported in this publication was supported by the Bill & Melinda Gates Foundation, the University of Melbourne, Public Health England, the Norwegian Institute of Public Health, St. Jude Children's Research Hospital, the National Institute on Aging of the National Institutes of Health (award P30AG047845), and the National Institute of Mental Health of the National Institutes of Health (award R01MH110163).
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- 2018
38. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015
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Glaser, Elizabeth, Godwin, William W, Gomez-Dantes, Hector, Gona, Philimon, Goodridge, Amador, Gopalani, Sameer Vali, Gotay, Carolyn C, Goto, Atsushi, Gouda, Hebe N, Grainger, Rebecca, Greaves, Felix, Guillemin, Franci, Guo, Yuming, Gupta, Rahul, Gupta, Rajeev, Gupta, Vipin, Gutiérrez, Reyna A, Haile, Demewoz, Hailu, Alemayehu Desalegne, Hailu, Gessessew Bugssa, Halasa, Yara A, Hamadeh, Randah Ribhi, Hamidi, Samer, Hammami, Mouhanad, Hancock, Jamie, Handal, Alexis J, Hankey, Graeme J, Hao, Yuantao, Harb, Hilda L, Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Havmoeller, Rasmu, Hay, Roderick J, Heredia-Pi, Ileana Beatriz, Heydarpour, Pouria, Hoek, Hans W, Horino, Masako, Horita, Nobuyuki, Hosgood, H Dean, Hoy, Damian G, Htet, Aung Soe, Huang, Hsiang, Huang, John J, Huynh, Chantal, Iannarone, Marissa, Iburg, Kim Moesgaard, Innos, Kaire, Inoue, Manami, Iyer, Veena J, Jacobsen, Kathryn H, Jahanmehr, Nader, Jakovljevic, Mihajlo B, Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jee, Sun Ha, Jeemon, Panniyammakal, Jensen, Paul N, Jiang, Ying, Jibat, Tariku, Jimenez-Corona, Aida, Jin, Ye, Jonas, Jost B, Kabir, Zubair, Kalkonde, Yogeshwar, Kamal, Ritul, Kan, Haidong, Karch, André, Karema, Corine Kakizi, Karimkhani, Chante, Kasaeian, Amir, Kaul, Anil, Kawakami, Norito, Keiyoro, Peter Njenga, Kemp, Andrew Haddon, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khan, Abdur Rahman, Khan, Ejaz Ahmad, Khang, Young-Ho, Khera, Sahil, Khoja, Tawfik Ahmed Muthafer, Khubchandani, Jagdish, Kieling, Christian, Kim, Pauline, Kim, Cho-il, Kim, Daniel, Kim, Yun Jin, Kissoon, Niranjan, Knibbs, Luke D, Knudsen, Ann Kristin, Kokubo, Yoshihiro, Kolte, Dhaval, Kopec, Jacek A, Kosen, Soewarta, Kotsakis, Georgios A, Koul, Parvaiz A, Koyanagi, Ai, Kravchenko, Michael, Defo, Barthelemy Kuate, Bicer, Burcu Kucuk, Kudom, Andreas A, Kuipers, Ernst J, Kumar, G Anil, Kutz, Michael, Kwan, Gene F, Lal, Aparna, Lalloo, Ratilal, Lallukka, Tea, Lam, Hilton, Lam, Jennifer O, Langan, Sinead M, Larsson, Ander, Lavados, Pablo M, Leasher, Janet L, Leigh, Jame, Leung, Ricky, Levi, Miriam, Li, Yichong, Li, Yongmei, Liang, Juan, Liu, Shiwei, Liu, Yang, Lloyd, Belinda K, Lo, Warren D, Logroscino, Giancarlo, Looker, Katharine J, Lotufo, Paulo A, Lunevicius, Raimunda, Lyons, Ronan A, Mackay, Mark T, Magdy, Mohammed, Razek, Abd El, Mahdavi, Mahdi, Majdan, Marek, Majeed, Azeem, Malekzadeh, Reza, Marcenes, Wagner, Margolis, David Joel, Martinez-Raga, Jose, Masiye, Felix, Massano, João, Mcgarvey, Stephen Theodore, Mcgrath, John J, Mckee, Martin, Mcmahon, Brian J, Meaney, Peter A, Mehari, Alem, Mejia-Rodriguez, Fabiola, Mekonnen, Alemayehu B, Melaku, Yohannes Adama, Memiah, Peter, Memish, Ziad A, Mendoza, Walter, Meretoja, Atte, Meretoja, Tuomo J, Mhimbira, Francis Apolinary, Miller, Ted R, Mills, Edward J, Mirarefin, Mojde, Mitchell, Philip B, Mock, Charles N, Mohammadi, Alireza, Mohammed, Shafiu, Monasta, Lorenzo, Hernandez, Julio Cesar Montañez, Montico, Marcella, Mooney, Meghan D, Moradi-Lakeh, Maziar, Morawska, Lidia, Mueller, Ulrich O, Mullany, Erin, Mumford, John Everett, Murdoch, Michele E, Nachega, Jean B, Nagel, Gabriele, Naheed, Aliya, Naldi, Luigi, Nangia, Vinay, Newton, John N, Ng, Marie, Ngalesoni, Frida Namnyak, Nguyen, Quyen Le, Nisar, Muhammad Imran, Pete, Patrick Martial Nkamedjie, Nolla, Joan M, Norheim, Ole F, Norman, Rosana E, Norrving, Bo, Nunes, Bruno P, Ogbo, Felix Akpojene, Oh, In-Hwan, Ohkubo, Takayoshi, Olivares, Pedro R, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ortiz, Alberto, Osman, Majdi, Ota, Erika, Pa, Mahesh, Park, Eun-Kee, Parsaeian, Mahboubeh, de Azeredo Passos, Valéria Maria, Caicedo, Angel J Paternina, Patten, Scott B, Patton, George C, Pereira, David M, Perez-Padilla, Rogelio, Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael Robert, Piel, Frédéric B, Pillay, Julian David, Pishgar, Farhad, Plass, Dietrich, Platts-Mills, James A, Polinder, Suzanne, Pond, Constance D, Popova, Svetlana, Poulton, Richie G, Pourmalek, Farshad, Prabhakaran, Dorairaj, Prasad, Noela M, Qorbani, Mostafa, Rabiee, Rynaz H S, Radfar, Amir, Rafay, Anwar, Rahimi, Kazem, Rahimi-Movaghar, Vafa, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Sajjad Ur, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Rao, Puja, Refaat, Amany H, Reitsma, Marissa B, Remuzzi, Giuseppe, Resnikoff, Serge, Reynolds, Alex, Ribeiro, Antonio L, Blancas, Maria Jesus Rio, Roba, Hirbo Shore, Rojas-Rueda, David, Ronfani, Luca, Roshandel, Gholamreza, Roth, Gregory A, Rothenbacher, Dietrich, Roy, Ambuj, Sagar, Rajesh, Sahathevan, Ramesh, Sanabria, Juan R, Sanchez-Niño, Maria Dolore, Santos, Itamar S, Santos, João Vasco, Sarmiento-Suarez, Rodrigo, Sartorius, Benn, Satpathy, Maheswar, Savic, Miloje, Sawhney, Monika, Schaub, Michael P, Schmidt, Maria Inê, Schneider, Ione J C, Schöttker, Ben, Schwebel, David C, Scott, James G, Seedat, Soraya, Sepanlou, Sadaf G, Servan-Mori, Edson E, Shackelford, Katya A, Shaheen, Amira, Shaikh, Masood Ali, Sharma, Rajesh, Sharma, Upasana, Shen, Jiabin, Shepard, Donald S, Sheth, Kevin N, Shibuya, Kenji, Shin, Min-Jeong, Shiri, Rahman, Shiue, Ivy, Shrime, Mark G, Sigfusdottir, Inga Dora, Silva, Diego Augusto Santo, Silveira, Dayane Gabriele Alve, Singh, Abhishek, Singh, Jasvinder A, Singh, Om Prakash, Singh, Prashant Kumar, Sivonda, Anna, Skirbekk, Vegard, Skogen, Jens Christoffer, Sligar, Amber, Sliwa, Karen, Soljak, Michael, Søreide, Kjetil, Soriano, Joan B, Sposato, Luciano A, Sreeramareddy, Chandrashekhar T, Stathopoulou, Vasiliki, Steel, Nichola, Stein, Dan J, Steiner, Timothy J, Steinke, Sabine, Stovner, Lar, Stroumpoulis, Konstantino, Sunguya, Bruno F, Sur, Patrick, Swaminathan, Soumya, Sykes, Bryan L, Szoeke, Cassandra E I, Tabarés-Seisdedos, Rafael, Takala, Jukka S, Tandon, Nikhil, Tanne, David, Tavakkoli, Mohammad, Taye, Bineyam, Taylor, Hugh R, Ao, Braden J Te, Tedla, Bemnet Amare, Terkawi, Abdullah Sulieman, Thomson, Alan J, Thorne-Lyman, Andrew L, Thrift, Amanda G, Thurston, George D, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Tran, Bach Xuan, Dimbuene, Zacharie Tsala, Tsilimbaris, Miltiadi, Tura, Abera Kenay, Tuzcu, Emin Murat, Tyrovolas, Stefano, Ukwaja, Kingsley N, Undurraga, Eduardo A, Uneke, Chigozie Jesse, Uthman, Olalekan A, van Gool, Coen H, Varakin, Yuri Y, Vasankari, Tommi, Venketasubramanian, Narayanaswamy, Verma, Raj Kumar, Violante, Francesco S, Vladimirov, Sergey K, Vlassov, Vasiliy Victorovich, Vollset, Stein Emil, Wagner, Gregory R, Waller, Stephen G, Wang, Linhong, Watkins, David A, Weichenthal, Scott, Weiderpass, Elisabete, Weintraub, Robert G, Werdecker, Andrea, Westerman, Ronny, White, Richard A, Williams, Hywel C, Wiysonge, Charles Shey, Wolfe, Charles D A, Won, Sungho, Woodbrook, Rachel, Wubshet, Mamo, Xavier, Deni, Xu, Gelin, Yadav, Ajit Kumar, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Ye, Pengpeng, Yebyo, Henock Gebremedhin, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Younis, Mustafa Z, Yu, Chuanhua, Zaidi, Zoubida, Zaki, Maysaa El Sayed, Zeeb, Hajo, Zhou, Maigeng, Zodpey, Sanjay, Zuhlke, Liesl Joanna, and Murray, Christopher J L
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Medicine(all) ,VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801 ,Incidence ,Medicine (all) ,Public Health, Global Health, Social Medicine and Epidemiology ,Bayes Theorem ,11 Medical And Health Sciences ,Articles ,Department of Error ,Global Health ,Cost of Illne ,Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi ,Cost of Illness ,disability ,General & Internal Medicine ,Quality-Adjusted Life Year ,Prevalence ,Humans ,Disabled Person ,Disabled Persons ,Quality-Adjusted Life Years ,VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801 ,Human - Abstract
Background Non-fatal outcomes of disease and injury increasingly detract from the ability of the world's population to live in full health, a trend largely attributable to an epidemiological transition in many countries from causes affecting children, to non-communicable diseases (NCDs) more common in adults. For the Global Burden of Diseases, Injuries, and Risk Factors Study 2015 (GBD 2015), we estimated the incidence, prevalence, and years lived with disability for diseases and injuries at the global, regional, and national scale over the period of 1990 to 2015. Methods We estimated incidence and prevalence by age, sex, cause, year, and geography with a wide range of updated and standardised analytical procedures. Improvements from GBD 2013 included the addition of new data sources, updates to literature reviews for 85 causes, and the identification and inclusion of additional studies published up to November, 2015, to expand the database used for estimation of non-fatal outcomes to 60 900 unique data sources. Prevalence and incidence by cause and sequelae were determined with DisMod-MR 2.1, an improved version of the DisMod-MR Bayesian meta-regression tool first developed for GBD 2010 and GBD 2013. For some causes, we used alternative modelling strategies where the complexity of the disease was not suited to DisMod-MR 2.1 or where incidence and prevalence needed to be determined from other data. For GBD 2015 we created a summary indicator that combines measures of income per capita, educational attainment, and fertility (the Socio-demographic Index [SDI]) and used it to compare observed patterns of health loss to the expected pattern for countries or locations with similar SDI scores. Findings We generated 9·3 billion estimates from the various combinations of prevalence, incidence, and YLDs for causes, sequelae, and impairments by age, sex, geography, and year. In 2015, two causes had acute incidences in excess of 1 billion: upper respiratory infections (17·2 billion, 95% uncertainty interval [UI] 15·4–19·2 billion) and diarrhoeal diseases (2·39 billion, 2·30–2·50 billion). Eight causes of chronic disease and injury each affected more than 10% of the world's population in 2015: permanent caries, tension-type headache, iron-deficiency anaemia, age-related and other hearing loss, migraine, genital herpes, refraction and accommodation disorders, and ascariasis. The impairment that affected the greatest number of people in 2015 was anaemia, with 2·36 billion (2·35–2·37 billion) individuals affected. The second and third leading impairments by number of individuals affected were hearing loss and vision loss, respectively. Between 2005 and 2015, there was little change in the leading causes of years lived with disability (YLDs) on a global basis. NCDs accounted for 18 of the leading 20 causes of age-standardised YLDs on a global scale. Where rates were decreasing, the rate of decrease for YLDs was slower than that of years of life lost (YLLs) for nearly every cause included in our analysis. For low SDI geographies, Group 1 causes typically accounted for 20–30% of total disability, largely attributable to nutritional deficiencies, malaria, neglected tropical diseases, HIV/AIDS, and tuberculosis. Lower back and neck pain was the leading global cause of disability in 2015 in most countries. The leading cause was sense organ disorders in 22 countries in Asia and Africa and one in central Latin America; diabetes in four countries in Oceania; HIV/AIDS in three southern sub-Saharan African countries; collective violence and legal intervention in two north African and Middle Eastern countries; iron-deficiency anaemia in Somalia and Venezuela; depression in Uganda; onchoceriasis in Liberia; and other neglected tropical diseases in the Democratic Republic of the Congo. Interpretation Ageing of the world's population is increasing the number of people living with sequelae of diseases and injuries. Shifts in the epidemiological profile driven by socioeconomic change also contribute to the continued increase in years lived with disability (YLDs) as well as the rate of increase in YLDs. Despite limitations imposed by gaps in data availability and the variable quality of the data available, the standardised and comprehensive approach of the GBD study provides opportunities to examine broad trends, compare those trends between countries or subnational geographies, benchmark against locations at similar stages of development, and gauge the strength or weakness of the estimates available. Funding Bill & Melinda Gates Foundation. Open Access funded by Bill & Melinda Gates FoundationUnder a Creative Commons license Attribution 4.0 International (CC BY 4.0)
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39. Epidemiologic and genomic characterization of an outbreak of Rift Valley fever among humans and dairy cattle in northern Tanzania.
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Madut DB, Rubach MP, Allan KJ, Thomas KM, de Glanville WA, Halliday JEB, Costales C, Carugati M, Rolfe RJ, Bonnewell JP, Maze MJ, Mremi AR, Amsi PT, Kalengo NH, Lyamuya F, Kinabo GD, Mbwasi R, Kilonzo KG, Maro VP, Mmbaga BT, Lwezaula B, Mosha C, Marandu A, Kibona TJ, Zhu F, Chawla T, Chia WN, Anderson DE, Wang LF, Liu J, Houpt ER, Martines RB, Zaki SR, Leach A, Gibbons A, Chiang CF, Patel K, Klena JD, Cleaveland S, and Crump JA
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Background: A peri-urban outbreak of Rift Valley fever virus (RVFV) among dairy cattle from May through August 2018 in northern Tanzania was detected through testing samples from prospective livestock abortion surveillance. We sought to identify concurrent human infections, their phylogeny, and epidemiologic characteristics in a cohort of febrile patients enrolled from 2016-2019 at hospitals serving the epizootic area., Methods: From September 2016 through May 2019, we conducted a prospective cohort study that enrolled febrile patients hospitalized at two hospitals in Moshi, Tanzania. Archived serum, plasma, or whole blood samples were retrospectively tested for RVFV by PCR. Human samples positive for RVFV were sequenced and compared to RVFV sequences obtained from cattle through a prospective livestock abortion study. Phylogenetic analysis was performed on complete RVFV genomes., Results: Among 656 human participants, we detected RVFV RNA in four (0.6%), including one death with hepatic necrosis and other end-organ damage at autopsy. Humans infected with RVFV were enrolled from June through August 2018, and all resided in or near urban areas. Phylogenetic analysis of human and cattle RVFV sequences demonstrated that most clustered to lineage B, a lineage previously described in East Africa. A lineage E strain clustering with lineages in Angola was also identified in cattle., Conclusion: We provide evidence that an apparently small RVFV outbreak among dairy cattle in northern Tanzania was associated with concurrent severe and fatal infections among humans. Our findings highlight the unidentified scale and diversity of inter-epizootic RVFV transmission, including near and within an urban area., (Published by Oxford University Press on behalf of Infectious Diseases Society of America 2024.)
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- 2024
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40. Predicting mortality in febrile adults: comparative performance of the MEWS, qSOFA, and UVA scores using prospectively collected data among patients in four health-care sites in sub-Saharan Africa and South-Eastern Asia.
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Lal S, Luangraj M, Keddie SH, Ashley EA, Baerenbold O, Bassat Q, Bradley J, Crump JA, Feasey NA, Green EW, Kain KC, Olaru ID, Lalloo DG, Roberts CH, Mabey DCW, Moore CC, and Hopkins H
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Background: Clinical severity scores can identify patients at risk of severe disease and death, and improve patient management. The modified early warning score (MEWS), the quick Sequential (Sepsis-Related) Organ Failure Assessment (qSOFA), and the Universal Vital Assessment (UVA) were developed as risk-stratification tools, but they have not been fully validated in low-resource settings where fever and infectious diseases are frequent reasons for health care seeking. We assessed the performance of MEWS, qSOFA, and UVA in predicting mortality among febrile patients in the Lao PDR, Malawi, Mozambique, and Zimbabwe., Methods: We prospectively enrolled in- and outpatients aged ≥ 15 years who presented with fever (≥37.5 °C) from June 2018-March 2021. We collected clinical data to calculate each severity score. The primary outcome was mortality 28 days after enrolment. The predictive performance of each score was determined using area under the receiver operating curve (AUC)., Findings: A total of 2797 participants were included in this analysis. The median (IQR) age was 32 (24-43) years, 38% were inpatients, and 60% (1684/2797) were female. By the time of follow-up, 7% (185/2797) had died. The AUC (95% CI) for MEWS, qSOFA and UVA were 0.67 (0.63-0.71), 0.68 (0.64-0.72), and 0.82 (0.79-0.85), respectively. The AUC comparison found UVA outperformed both MEWS (p < 0.001) and qSOFA (p < 0.001)., Interpretation: We showed that the UVA score performed best in predicting mortality among febrile participants by the time follow-up compared with MEWS and qSOFA, across all four study sites. The UVA score could be a valuable tool for early identification, triage, and initial treatment guidance of high-risk patients in resource-limited clinical settings., Funding: FCDO., Competing Interests: HH reports royalties from Wolters Kluwer Health as the primary author and maintainer of the “Laboratory tools for diagnosis of malaria” clinical decision support tool., (© 2024 The Author(s).)
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- 2024
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41. Population Structure and Antimicrobial Resistance in Campylobacter jejuni and C. coli Isolated from Humans with Diarrhea and from Poultry, East Africa.
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French NP, Thomas KM, Amani NB, Benschop J, Bigogo GM, Cleaveland S, Fayaz A, Hugho EA, Karimuribo ED, Kasagama E, Maganga R, Melubo ML, Midwinter AC, Mmbaga BT, Mosha VV, Mshana FI, Munyua P, Ochieng JB, Rogers L, Sindiyo E, Swai ES, Verani JR, Widdowson MA, Wilkinson DA, Kazwala RR, Crump JA, and Zadoks RN
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- Humans, Animals, Drug Resistance, Bacterial, Poultry Diseases microbiology, Poultry Diseases epidemiology, Poultry Diseases drug therapy, Whole Genome Sequencing, Africa, Eastern epidemiology, Drug Resistance, Multiple, Bacterial, Phylogeny, Campylobacter jejuni drug effects, Campylobacter jejuni genetics, Campylobacter jejuni isolation & purification, Diarrhea microbiology, Diarrhea epidemiology, Diarrhea drug therapy, Campylobacter Infections microbiology, Campylobacter Infections epidemiology, Campylobacter Infections drug therapy, Campylobacter Infections veterinary, Poultry microbiology, Anti-Bacterial Agents pharmacology, Campylobacter coli drug effects, Campylobacter coli genetics, Campylobacter coli isolation & purification, Microbial Sensitivity Tests
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Campylobacteriosis and antimicrobial resistance (AMR) are global public health concerns. Africa is estimated to have the world's highest incidence of campylobacteriosis and a relatively high prevalence of AMR in Campylobacter spp. from humans and animals. Few studies have compared Campylobacter spp. isolated from humans and poultry in Africa using whole-genome sequencing and antimicrobial susceptibility testing. We explored the population structure and AMR of 178 Campylobacter isolates from East Africa, 81 from patients with diarrhea in Kenya and 97 from 56 poultry samples in Tanzania, collected during 2006-2017. Sequence type diversity was high in both poultry and human isolates, with some sequence types in common. The estimated prevalence of multidrug resistance, defined as resistance to >3 antimicrobial classes, was higher in poultry isolates (40.9%, 95% credible interval 23.6%-59.4%) than in human isolates (2.5%, 95% credible interval 0.3%-6.8%), underlining the importance of antimicrobial stewardship in livestock systems.
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- 2024
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42. Environmental contamination with carbapenem resistant Acinetobacter baumannii in healthcare settings in Fiji: a potential source of infection.
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Baleivanualala SC, Matanitobua S, Samisoni Y, Soqo V, Smita S, Mailulu J, Nabose I, Lata A, Shayam C, Sharma R, Wilson D, Crump JA, and Ussher JE
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- Humans, Fiji epidemiology, Hospitals, Environmental Microbiology, Whole Genome Sequencing, Bacterial Proteins genetics, beta-Lactamases genetics, beta-Lactamases metabolism, Acinetobacter baumannii drug effects, Acinetobacter baumannii genetics, Acinetobacter baumannii isolation & purification, Acinetobacter baumannii classification, Carbapenems pharmacology, Acinetobacter Infections microbiology, Acinetobacter Infections epidemiology, Microbial Sensitivity Tests, Cross Infection microbiology, Cross Infection epidemiology, Phylogeny, Anti-Bacterial Agents pharmacology
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Introduction: There are multiple ongoing outbreaks of carbapenem resistant Acinetobacter baumannii (CR Ab ) infection in Fiji's hospitals. CR Ab is able to colonize and persist on various hospital surfaces for extended periods. We conducted a study to understand the extent of hospital environmental contamination and phylogenetic links with clinical isolates., Methods: Swabs were collected from high-touch surfaces at Colonial War Memorial Hospital (CWMH) September 2021 and December 2022; Lautoka Hospital (LTKH) August 2022; and Labasa Hospital (LBSH) November 2022. All bacterial isolates were identified, and antimicrobial susceptibility testing (AST) performed; isolates resistant to carbapenems and producing a carbapenemase underwent whole genome sequencing. Comparison was made to clinical isolates obtained from CWMH in 2016-2017 and 2019-2021 and from LTKH and LBSH from 2020-2021., Results: From the 180 environmental samples collected, ten (5.6%) CR Ab were isolated; no other carbapenem-resistant gram-negative organisms were isolated. Seven (70%) of the CR Ab were isolated from CWMH and three (30%) from LTKH; no CR Ab were isolated from LBSH. Of the seven CWMH CR Ab , two were sequence type 2 (ST2), three ST25, and two ST499. All LTKH isolates were ST499. The two environmental CR Ab ST2 isolates were closely genetically linked to isolates obtained from patients in CWMH, LTKH, and LBSH 2020-2021. Similarly, the three environmental CR Ab ST25 isolates were closely genetically linked to isolates obtained from patients admitted to CWMH in 2019-2021 and LBSH in 2020. The environmental CR Ab ST499 isolates represented two distinct clones, with clone 1 comprising two genetically identical isolates from CWMH and clone 2 the three isolates from LTKH. Although no genetic linkages were observed when comparing environmental ST499 isolates to those from CWMH patients in 2020-2021, both clone 1 isolates were genetically identical to an isolate obtained from a patient admitted during the sampling period., Conclusion: Our study highlights the contamination of high-touch surfaces within Fiji hospitals with CR Ab , suggesting that these may serve as important sources for CR Ab . Phylogenetic linkages to CR Ab isolated from patients since 2019 underscores the persistence of this resistant pathogen in hospital settings and the ongoing risk for hospital-acquired infections., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Baleivanualala, Matanitobua, Samisoni, Soqo, Smita, Mailulu, Nabose, Lata, Shayam, Sharma, Wilson, Crump and Ussher.)
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- 2024
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43. Metagenomic Detection of Bacterial Zoonotic Pathogens among Febrile Patients, Tanzania, 2007-2009 1 .
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Rolfe RJ, Sheldon SW, Kingry LC, Petersen JM, Maro VP, Kinabo GD, Saganda W, Maze MJ, Halliday JEB, Nicholson WL, Galloway RL, Rubach MP, and Crump JA
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- Humans, Tanzania epidemiology, Adult, Child, Preschool, Adolescent, Male, Female, Animals, Child, Young Adult, Bacteria genetics, Bacteria classification, Bacteria isolation & purification, Bacterial Zoonoses microbiology, Bacterial Zoonoses epidemiology, Bacterial Infections microbiology, Bacterial Infections epidemiology, Bacterial Infections diagnosis, Zoonoses microbiology, Zoonoses epidemiology, Metagenomics methods, Fever microbiology, RNA, Ribosomal, 16S genetics
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Bacterial zoonoses are established causes of severe febrile illness in East Africa. Within a fever etiology study, we applied a high-throughput 16S rRNA metagenomic assay validated for detecting bacterial zoonotic pathogens. We enrolled febrile patients admitted to 2 referral hospitals in Moshi, Tanzania, during September 2007-April 2009. Among 788 participants, median age was 20 (interquartile range 2-38) years. We performed PCR amplification of V1-V2 variable region 16S rRNA on cell pellet DNA, then metagenomic deep-sequencing and pathogenic taxonomic identification. We detected bacterial zoonotic pathogens in 10 (1.3%) samples: 3 with Rickettsia typhi, 1 R. conorii, 2 Bartonella quintana, 2 pathogenic Leptospira spp., and 1 Coxiella burnetii. One other sample had reads matching a Neoerhlichia spp. previously identified in a patient from South Africa. Our findings indicate that targeted 16S metagenomics can identify bacterial zoonotic pathogens causing severe febrile illness in humans, including potential novel agents.
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- 2024
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44. Vaccine value profile for invasive non-typhoidal Salmonella disease.
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Martin LB, Tack B, Marchello CS, Sikorski MJ, Owusu-Dabo E, Nyirenda T, Mogasale V, and Crump JA
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- Humans, Africa South of the Sahara epidemiology, Salmonella typhimurium immunology, Salmonella typhimurium pathogenicity, Salmonella typhimurium genetics, Salmonella enteritidis immunology, Salmonella enteritidis genetics, Salmonella enteritidis pathogenicity, Salmonella Infections prevention & control, Salmonella Infections epidemiology, Salmonella Infections microbiology, Salmonella Infections immunology, Salmonella Vaccines immunology, Salmonella Vaccines administration & dosage
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Invasive non-typhoidal Salmonella (iNTS) disease is an under-recognized high-burden disease causing major health and socioeconomic issues in sub-Saharan Africa (sSA), predominantly among immune-naïve infants and young children, including those with recognized comorbidities such as HIV infection. iNTS disease is primarily caused by Salmonella enterica serovar Typhimurium sequence type (ST) 313 and 'African-restricted clades' of Salmonella Enteritidis ST11 that have emerged across the African continent as a series of epidemics associated with acquisition of new antimicrobial resistance. Due to genotypes with a high prevalence of antimicrobial resistance and scarcity of therapeutic options, these NTS serovars are designated by the World Health Organization as a priority pathogen for research and development of interventions, including vaccines, to address and reduce NTS associated bacteremia and meningitis in sSA. Novel and traditional vaccine technologies are being applied to develop vaccines against iNTS disease, and the results of the first clinical trials in the infant target population should become available in the near future. The "Vaccine Value Profile" (VVP) addresses information related predominantly to invasive disease caused by Salmonella Enteritidis and Salmonella Typhimurium prevalent in sSA. Information is included on stand-alone iNTS disease candidate vaccines and candidate vaccines targeting iNTS disease combined with another invasive serotype, Salmonella Typhi, that is also common across sSA. Out of scope for the first version of this VVP is a wider discussion on either diarrheagenic NTS disease (dNTS) also associated with Salmonella Enteritidis and Salmonella Typhimurium or the development of a multivalent Salmonella vaccines targeting key serovars for use globally. This VVP for vaccines to prevent iNTS disease is intended to provide a high-level, holistic assessment of the information and data that are currently available to inform the potential public health, economic, and societal value of pipeline vaccines and vaccine-like products. Future versions of this VVP will be updated to reflect ongoing activities such as vaccine development strategies and a "Full Vaccine Value Assessment" that will inform the value proposition of an iNTS disease vaccine. This VVP was developed by a working group of subject matter experts from academia, non-profit organizations, public private partnerships, and multi-lateral organizations, and in collaboration with stakeholders from the World Health Organization African Region. All contributors have extensive expertise on various elements of the iNTS disease VVP and collectively aimed to identify current research and knowledge gaps. The VVP was developed using only existing and publicly available information., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: LBM and MJS report financial support and administrative support by the World Health Organization. LBM was an independent consultant during VVP development; she is currently employed by the US Pharmacopeial Convention. CSM and JAC received support through the received funding from the EU Horizon 2020 research and innovation programme under the project Vacc-iNTS (grant agreement number 815439).VM was employed by the International Vaccines Institute during VVP development; he is currently employed by the World Health Organization. All other authors declare no conflicts of interest., (Copyright © 2024. Published by Elsevier Ltd.)
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- 2024
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45. Molecular and clinical epidemiology of carbapenem resistant Acinetobacter baumannii , Pseudomonas aeruginosa and Enterobacterales in Fiji: a multicentre prospective observational study.
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Baleivanualala SC, Matanitobua S, Soqo V, Smita S, Limaono J, Sharma SC, Devi SV, Boseiwaqa LV, Vera N, Kumar S, Lalibuli A, Mailulu J, Wilson D, Samisoni Y, Crump JA, and Ussher JE
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Background: Carbapenem resistant organisms (CROs) such as Acinetobacter baumannii (CR Ab ), Pseudomonas aeruginosa (CR Pa ), Escherichia coli (CR Ec ), and Klebsiella pneumoniae (CR Kp ) have been identified by the World Health Organization (WHO) as global priority pathogens. The dissemination of these pathogens and clonal outbreaks within healthcare facilities are of serious concern, particularly in regions with limited resources. In Fiji, where healthcare services are primarily provided by public hospitals, understanding the extent and nature of this problem is essential for the development of effective patient management, prevention interventions and control strategies., Methods: CROs isolated from 211 (77.3%) non-sterile (urinary catheters, urine, sputum, wound swab, and endotracheal tube) and 62 (22.7%) normally sterile (blood, cerebrospinal fluid, intravascular catheter, and aspirates) body sites of 272 patients treated at the three major hospitals in Fiji, the Colonial War Memorial Hospital (CWMH), Lautoka Hospital (LTKH), and Labasa Hospital (LBSH), and outer peripheral health centres around Fiji, were analysed. Clinical and demographic patient data such as age, sex, admission diagnosis, admission and discharge dates, patient outcomes, date of death, start and end date of meropenem and colistin treatment were reviewed. These CRO isolates comprised A. baumannii , P. aeruginosa , E. coli , and K. pneumoniae , that were prospectively collected at the microbiology laboratory of CWMH and LBSH from January 2020 through August 2021 and at the LTKH from January 2020 to December 2021. In addition, 10 retrospectively stored CR Pa isolates collected from patients at the CWMH from January through December 2019, were also included in the study. All isolates were characterised using mass spectrometry, antimicrobial susceptibility testing, and whole genome sequencing. Phylogenetic relationships among the CROs were assessed through core genome single nucleotide polymorphism (SNP) analysis. The CR Ab isolates were also compared to the CR Ab isolates from CWMH isolated in 2016/2017 and 2019, along with CR Ab isolates obtained from Fijian patients admitted to New Zealand hospitals in 2020 and 2021 from our retrospective study., Findings: Of 272 patients, 140 (51.5%) were male, the median (range) age of patients was 45 (<1-89) years, 161 (59.2%) were I-Taukei, 104 (38.2%) Fijians of Indian descent, and 7 (2.6%) were from other ethnic backgrounds. 234 (86.0%) of these 272 patients, had their first positive CRO sample collected ≥72 h following admission and the remaining 38 (14.0%) were isolated within 72 h following admission. Of the 273 CROs, 146 (53.5%) were collected at the CWMH, 66 (24.2%) LTKH, and 61 (22.3%) LBSH, while 62 (22.7%) were isolated from normally sterile sites and 211 (77.3%) from sites that are not sterile. Of 273 isolates, 131 (48.0%) were CR Ab , 90 (33.0%) CR Pa , 46 (16.8%) CR Ec , and 6 (2.2%) CR Kp . Of 131 CR Ab , 108 (82.4%) were ST2, with three distinct clones, all encoding bla
OXA-23 and blaOXA - 66 , while clone 3 also encoded blaNDM-1 ; blaOXA-23 was associated with two copies of IS Aba1 insertion element, forming the composite transposon Tn 2006 . The first two CR Ab ST2 clones were genetically linked to those isolated at CMWH 2016 through 2019, while the third was genetically linked to isolates from Fijian patients admitted to New Zealand hospitals in 2020 and 2021. Of CR Pa , 65 (72.2%) were ST773 and carried β-lactamase genes blaNDM-1 , blaOXA-50 , and blaOXA-395 . Of 10 retrospective CR Pa isolates, all belonged to CR Pa ST773 and carried blaNDM-1 , blaOXA-50 , and blaOXA-395 . Of 46 CR Ec , 44 (95.7%) were ST410 and encoded blaNDM-7 on an IncX3 plasmid. Of 6 CR Kp , 4 (66.7%) were ST16 and carried blaNDM-5 on an IncX3 plasmid. Other sequence types of CR Pa (ST9, ST357, ST654, ST664), CR Ab (ST25, ST374, ST499), CR Ec (ST167), and CR Kp (ST45, ST336) were also detected. Of those receiving meropenem treatment in the prospective study, 30 (57.7%) received it inappropriately. Of 272 patients, 65 (23.9%) died within the 30 days after first positive CRO isolation., Interpretation: We identified nosocomial transmission of distinct clones of CR Ab ST2, CR Pa ST773, CR Ec ST410, and CR Kp ST16 within and between the three major hospitals in Fiji. Moreover, community onset infections associated with CR Pa , CR Ec , and CR Ab were also detected. Of note, cross-border transmission of CR Ab ST2 clone 3 strain between Fiji and New Zealand was also detected. These clones encoded an array of carbapenem resistance genes associated with mobile genetic elements, including plasmids, transposons, and integrative and conjugative elements, signifying their potential for increased mobility, further acquisition of resistance genes, and spread. Inappropriate use of meropenem was common. Of note, the majority of patients who died had acquired CRO during their hospital stay. These findings highlight the need for stringent IPC strategies focusing on catheter and ventilator management, meticulous wound care, rigorous sepsis control, consistent hand hygiene, effective use of disinfectants, and thorough sanitisation of both hospital environments and medical equipment in the three major hospitals in Fiji. Additionally, diligent surveillance of AMR and robust antimicrobial stewardship are crucial for effectively managing nosocomial infections., Funding: This project was funded by the Otago Medical School Foundations Trust (Dean's Bequest Fund) and a Fiji National University seed grant. The funders of the study had no role in the study design, data collection, data analysis, data interpretation, or writing of the report., Competing Interests: The authors have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Author(s).)- Published
- 2024
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46. Prevalence and risk factors for Q fever, spotted fever group rickettsioses, and typhus group rickettsioses in a pastoralist community of northern Tanzania, 2016-2017.
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Moorthy GS, Rubach MP, Maze MJ, Refuerzo RP, Shirima GM, Lukambagire AS, Bodenham RF, Cash-Goldwasser S, Thomas KM, Sakasaka P, Mkenda N, Bowhay TR, Perniciaro JL, Nicholson WL, Kersh GJ, Kazwala RR, Mmbaga BT, Buza JJ, Maro VP, Haydon DT, Crump JA, and Halliday JEB
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- Humans, Tanzania epidemiology, Male, Risk Factors, Female, Adult, Adolescent, Prevalence, Young Adult, Middle Aged, Child, Animals, Rickettsia immunology, Rickettsia isolation & purification, Child, Preschool, Coxiella burnetii immunology, Aged, Zoonoses microbiology, Q Fever epidemiology, Spotted Fever Group Rickettsiosis epidemiology, Spotted Fever Group Rickettsiosis microbiology, Rickettsia Infections epidemiology, Rickettsia Infections microbiology
- Abstract
Background: In northern Tanzania, Q fever, spotted fever group (SFG) rickettsioses, and typhus group (TG) rickettsioses are common causes of febrile illness. We sought to describe the prevalence and risk factors for these zoonoses in a pastoralist community., Methods: Febrile patients ≥2 years old presenting to Endulen Hospital in the Ngorongoro Conservation Area were enrolled from August 2016 through October 2017. Acute and convalescent blood samples were collected, and a questionnaire was administered. Sera were tested by immunofluorescent antibody (IFA) IgG assays using Coxiella burnetii (Phase II), Rickettsia africae, and Rickettsia typhi antigens. Serologic evidence of exposure was defined by an IFA titre ≥1:64; probable cases by an acute IFA titre ≥1:128; and confirmed cases by a ≥4-fold rise in titre between samples. Risk factors for exposure and acute case status were evaluated., Results: Of 228 participants, 99 (43.4%) were male and the median (interquartile range) age was 27 (16-41) years. Among these, 117 (51.3%) had C. burnetii exposure, 74 (32.5%) had probable Q fever, 176 (77.2%) had SFG Rickettsia exposure, 134 (58.8%) had probable SFG rickettsioses, 11 (4.8%) had TG Rickettsia exposure, and 4 (1.8%) had probable TG rickettsioses. Of 146 participants with paired sera, 1 (0.5%) had confirmed Q fever, 8 (5.5%) had confirmed SFG rickettsioses, and none had confirmed TG rickettsioses. Livestock slaughter was associated with acute Q fever (adjusted odds ratio [OR] 2.54, 95% confidence interval [CI] 1.38-4.76) and sheep slaughter with SFG rickettsioses case (OR 4.63, 95% CI 1.08-23.50)., Discussion: Acute Q fever and SFG rickettsioses were detected in participants with febrile illness. Exposures to C. burnetii and to SFG Rickettsia were highly prevalent, and interactions with livestock were associated with increased odds of illness with both pathogens. Further characterisation of the burden and risks for these diseases is warranted., (© 2024 The Authors. Tropical Medicine & International Health Published by John Wiley & Sons Ltd.)
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- 2024
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47. Incidence of typhoid fever in Burkina Faso, Democratic Republic of the Congo, Ethiopia, Ghana, Madagascar, and Nigeria (the Severe Typhoid in Africa programme): a population-based study.
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Marks F, Im J, Park SE, Pak GD, Jeon HJ, Wandji Nana LR, Phoba MF, Mbuyi-Kalonji L, Mogeni OD, Yeshitela B, Panzner U, Cruz Espinoza LM, Beyene T, Owusu-Ansah M, Twumasi-Ankrah S, Yeshambaw M, Alemu A, Adewusi OJ, Adekanmbi O, Higginson E, Adepoju A, Agbi S, Cakpo EG, Ogunleye VO, Tunda GN, Ikhimiukor OO, Mbuyamba J, Toy T, Agyapong FO, Osei I, Amuasi J, Razafindrabe TJL, Raminosoa TM, Nyirenda G, Randriamampionona N, Seo HW, Seo H, Siribie M, Carey ME, Owusu M, Meyer CG, Rakotozandrindrainy N, Sarpong N, Razafindrakalia M, Razafimanantsoa R, Ouedraogo M, Kim YJ, Lee J, Zellweger RM, Kang SSY, Park JY, Crump JA, Hardy L, Jacobs J, Garrett DO, Andrews JR, Poudyal N, Kim DR, Clemens JD, Baker SG, Kim JH, Dougan G, Sugimoto JD, Van Puyvelde S, Kehinde A, Popoola OA, Mogasale V, Breiman RF, MacWright WR, Aseffa A, Tadesse BT, Haselbeck A, Adu-Sarkodie Y, Teferi M, Bassiahi AS, Okeke IN, Lunguya-Metila O, Owusu-Dabo E, and Rakotozandrindrainy R
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- Humans, Ghana, Madagascar, Burkina Faso epidemiology, Ethiopia, Incidence, Nigeria, Prospective Studies, Bayes Theorem, Democratic Republic of the Congo, Typhoid Fever epidemiology, Typhoid Fever prevention & control, Vaccines
- Abstract
Background: Typhoid Fever remains a major cause of morbidity and mortality in low-income settings. The Severe Typhoid in Africa programme was designed to address regional gaps in typhoid burden data and identify populations eligible for interventions using novel typhoid conjugate vaccines., Methods: A hybrid design, hospital-based prospective surveillance with population-based health-care utilisation surveys, was implemented in six countries in sub-Saharan Africa. Patients presenting with fever (≥37·5°C axillary or ≥38·0°C tympanic) or reporting fever for three consecutive days within the previous 7 days were invited to participate. Typhoid fever was ascertained by culture of blood collected upon enrolment. Disease incidence at the population level was estimated using a Bayesian mixture model., Findings: 27 866 (33·8%) of 82 491 participants who met inclusion criteria were recruited. Blood cultures were performed for 27 544 (98·8%) of enrolled participants. Clinically significant organisms were detected in 2136 (7·7%) of these cultures, and 346 (16·2%) Salmonella enterica serovar Typhi were isolated. The overall adjusted incidence per 100 000 person-years of observation was highest in Kavuaya and Nkandu 1, Democratic Republic of the Congo (315, 95% credible interval 254-390). Overall, 46 (16·4%) of 280 tested isolates showed ciprofloxacin non-susceptibility., Interpretation: High disease incidence (ie, >100 per 100 000 person-years of observation) recorded in four countries, the prevalence of typhoid hospitalisations and complicated disease, and the threat of resistant typhoid strains strengthen the need for rapid dispatch and implementation of effective typhoid conjugate vaccines along with measures designed to improve clean water, sanitation, and hygiene practices., Funding: The Bill & Melinda Gates Foundation., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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48. Examining geospatial and temporal distribution of invasive non-typhoidal Salmonella disease occurrence in sub-Saharan Africa: a systematic review and modelling study.
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Kim JH, Tack B, Fiorino F, Pettini E, Marchello CS, Jacobs J, Crump JA, and Marks F
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- Humans, Africa South of the Sahara epidemiology, Spatio-Temporal Analysis, Salmonella isolation & purification, Sanitation, Salmonella Infections epidemiology
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Background: Invasive non-typhoidal Salmonella (iNTS) disease is a significant health concern in sub-Saharan Africa. While our knowledge of a larger-scale variation is growing, understanding of the subnational variation in iNTS disease occurrence is lacking, yet crucial for targeted intervention., Method: We performed a systematic review of reported occurrences of iNTS disease in sub-Saharan Africa, consulting literature from PubMed, Embase and Web of Science published since 2000. Eligibility for inclusion was not limited by study type but required that studies reported original data on human iNTS diseases based on the culture of a normally sterile site, specifying subnational locations and the year, and were available as full-text articles. We excluded studies that diagnosed iNTS disease based on clinical indications, cultures from non-sterile sites or serological testing. We estimated the probability of occurrence of iNTS disease for sub-Saharan Africa on 20 km × 20 km grids by exploring the association with geospatial covariates such as malaria, HIV, childhood growth failure, access to improved water, and sanitation using a boosted regression tree., Results: We identified 130 unique references reporting human iNTS disease in 21 countries published from 2000 through 2020. The estimated probability of iNTS occurrence grids showed significant spatial heterogeneity at all levels (20 km × 20 km grids, subnational, country and subregional levels) and temporal heterogeneity by year. For 2020, the probability of occurrence was higher in Middle Africa (0.34, 95% CI: 0.25 to 0.46), followed by Western Africa (0.33, 95% CI: 0.23 to 0.44), Eastern Africa (0.24, 95% CI: 0.17 to 0.33) and Southern Africa (0.08, 95% CI: 0.03 to 0.11). Temporal heterogeneity indicated that the probability of occurrence increased between 2000 and 2020 in countries such as the Republic of the Congo (0.05 to 0.59) and Democratic Republic of the Congo (0.10 to 0.48) whereas it decreased in countries such as Uganda (0.65 to 0.23) or Zimbabwe (0.61 to 0.37)., Conclusion: The iNTS disease occurrence varied greatly across sub-Saharan Africa, with certain regions being disproportionately affected. Exploring regions at high risk for iNTS disease, despite the limitations in our data, may inform focused resource allocation. This targeted approach may enhance efforts to combat iNTS disease in more affected areas., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)
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- 2024
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49. Global distribution of Leptospira serovar isolations and detections from animal host species: A systematic review and online database.
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Hagedoorn NN, Maze MJ, Carugati M, Cash-Goldwasser S, Allan KJ, Chen K, Cossic B, Demeter E, Gallagher S, German R, Galloway RL, Habuš J, Rubach MP, Shiokawa K, Sulikhan N, and Crump JA
- Abstract
Objectives: Leptospira, the spirochaete causing leptospirosis, can be classified into >250 antigenically distinct serovars. Although knowledge of the animal host species and geographic distribution of Leptospira serovars is critical to understand the human and animal epidemiology of leptospirosis, current data are fragmented. We aimed to systematically review, the literature on animal host species and geographic distribution of Leptospira serovars to examine associations between serovars with animal host species and regions and to identify geographic regions in need of study., Methods: Nine library databases were searched from inception through 9 March 2023 using keywords including Leptospira, animal, and a list of serovars. We sought reports of detection of Leptospira, from any animal, characterised by cross agglutinin absorption test, monoclonal antibody typing, serum factor analysis, or pulsed-field gel electrophoresis to identify the serovar., Results: We included 409 reports, published from 1927 through 2022, yielding data on 154 Leptospira serovars. The reports included data from 66 (26.5%) of 249 countries. Detections were from 144 animal host species including 135 (93.8%) from the class Mammalia, 5 (3.5%) from Amphibia, 3 (2.1%) from Reptilia, and 1 (0.7%) from Arachnida. Across the animal host species, Leptospira serovars that were detected in the largest number of animal species included Grippotyphosa (n = 39), Icterohaemorrhagiae (n = 29), Pomona (n = 28), Australis (n = 25), and Ballum (n = 25). Of serovars, 76 were detected in a single animal host species. We created an online database to identify animal host species for each serovar by country., Conclusions: We found that many countries have few or no Leptospira serovars detected from animal host species and that many serovars were detected from a single animal species. Our study highlights the importance of efforts to identify animal host species of leptospirosis, especially in places with a high incidence of human leptospirosis. We provide an updated resource for leptospirosis researchers., (© 2024 The Authors Tropical Medicine & International Health Published by John Wiley & Sons Ltd.)
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- 2024
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50. Public opinion on global COVID-19 vaccine procurement and distribution policies: A nationally representative survey in Aotearoa New Zealand 2022.
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Kolandai K, Milne B, von Randow M, Bullen C, Marsh S, and Crump JA
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- Humans, Public Opinion, New Zealand epidemiology, Policy, COVID-19 Vaccines, COVID-19 epidemiology, COVID-19 prevention & control
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The World Health Organisation and many health experts have regarded vaccine nationalism, a "my country first" approach to vaccines procurement, as a critical pandemic response failure. However, few studies have considered public opinion in this regard. This study gauged public support for vaccine nationalism and vaccine internationalism in a representative survey in New Zealand (N = 1,135). Support for vaccine internationalism (M (mean rating) = 3.64 on 5-point scales) was significantly stronger than for vaccine nationalism (M = 3.24). Additionally, support for openly sharing COVID-19 vaccine manufacturing knowledge and technology (M = 4.17 on 5-point scales) was significantly stronger than support for safeguarding vaccine manufacturers' intellectual property (M = 2.66). The public also supported a utilitarian approach that would see distributions based on need (M = 3.76 on 5-point scales) over an equal proportional international distribution (M = 3.16). Akin to the few preceding studies, the present observations suggest that the public is likely to be more supportive of pandemic responses that are globally equitable and long-term orientated. Our findings have substantial implications for pandemic preparedness as the congruence or lack thereof of public vaccine-related values with government policies can affect public trust, which, in turn, can affect public cooperation. It may pay for governments to invest in proactive public engagement efforts before and during a pandemic to discuss critical ethical issues and inequities in global vaccine procurement and distributions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
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- 2024
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