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1. Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Author: Haeuser, E, Serfes, AL, Cork, MA, Yang, M, Abbastabar, H, Abhilash, ES, Adabi, M, Adebayo, OM, Adekanmbi, V, Adeyinka, DA, Afzal, S, Ahinkorah, BO, Ahmadi, K, Ahmed, MB, Akalu, Y, Akinyemi, RO, Akunna, CJ, Alahdab, F, Alanezi, FM, Alanzi, TM, Alene, KA, Alhassan, RK, Alipour, V, Almasi-Hashiani, A, Alvis-Guzman, N, Ameyaw, EK, Amini, S, Amugsi, DA, Ancuceanu, R, Anvari, D, Appiah, SCY, Arabloo, J, Aremu, O, Asemahagn, MA, Jafarabadi, MA, Awedew, AF, Quintanilla, BPA, Ayanore, MA, Aynalem, YA, Azari, S, Azene, ZN, Darshan, BB, Babalola, TK, Baig, AA, Banach, M, Bärnighausen, TW, Bell, AW, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bijani, A, Bitew, ZW, Bohlouli, S, Bolarinwa, OA, Boloor, A, Bozicevic, I, Butt, ZA, Cárdenas, R, Carvalho, F, Charan, J, Chattu, VK, Chowdhury, MAK, Chu, D-T, Cowden, RG, Dahlawi, SMA, Damiani, G, Darteh, EKM, Darwesh, AM, das Neves, J, Weaver, ND, De Leo, D, De Neve, J-W, Deribe, K, Deuba, K, Dharmaratne, S, Dianatinasab, M, Diaz, D, Didarloo, A, Djalalinia, S, Dorostkar, F, Dubljanin, E, Duko, B, El Tantawi, M, El-Jaafary, SI, Eshrati, B, Eskandarieh, S, Eyawo, O, Ezeonwumelu, IJ, Ezzikouri, S, Farzadfar, F, Fattahi, N, Fauk, NK, Fernandes, E, Filip, I, Fischer, F, Foigt, NA, Foroutan, M, Fukumoto, T, Gad, MM, Gaidhane, AM, Gebregiorgis, BG, Gebremedhin, KB, Getacher, L, Ghadiri, K, Ghashghaee, A, Golechha, M, Gubari, MIM, Gugnani, HC, Guimarães, RA, Haider, MR, Haj-Mirzaian, A, Hamidi, S, Hashi, A, Hassanipour, S, Hassankhani, H, Hayat, K, Herteliu, C, Ho, HC, Holla, R, Hosseini, M, Hosseinzadeh, M, Hwang, B-F, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Islam, RM, Iwu, CCD, Jakovljevic, M, Jha, RP, Ji, JS, Johnson, KB, Joseph, N, Joshua, V, Joukar, F, Jozwiak, JJ, Kalankesh, LR, Kalhor, R, Kamyari, N, Kanchan, T, Matin, BK, Karimi, SE, Kayode, GA, Karyani, AK, Keramati, M, Khan, EA, Khan, G, Khan, MN, Khatab, K, Khubchandani, J, Kim, YJ, Kisa, A, Kisa, S, Kopec, JA, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Defo, BK, Kugbey, N, Kulkarni, V, Kumar, M, Kumar, N, Kusuma, D, La Vecchia, C, Lal, DK, Landires, I, Larson, HJ, Lasrado, S, Lee, PH, Li, S, Liu, X, Maleki, A, Malik, P, Mansournia, MA, Martins-Melo, FR, Mendoza, W, Menezes, RG, Mengesha, EW, Meretoja, TJ, Mestrovic, T, Mirica, A, Moazen, B, Mohamad, O, Mohammad, Y, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, S, Mokdad, AH, Moradi, M, Moraga, P, Mubarik, S, Mulu, GBB, Mwanri, L, Nagarajan, AJ, Naimzada, MD, Naveed, M, Nazari, J, Ndejjo, R, Negoi, I, Ngalesoni, FN, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, CT, Nguyen, HLT, Nnaji, CA, Noubiap, JJ, Nuñez-Samudio, V, Nwatah, VE, Oancea, B, Odukoya, OO, Olagunju, AT, Olakunde, BO, Olusanya, BO, Olusanya, JO, Bali, AO, Onwujekwe, OE, Orisakwe, OE, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Mahesh, PA, Padubidri, JR, Pana, A, Pandey, A, Pandi-Perumal, SR, Kan, FP, Patton, GC, Pawar, S, Peprah, EK, Postma, MJ, Preotescu, L, Syed, ZQ, Rabiee, N, Radfar, A, Rafiei, A, Rahim, F, Rahimi-Movaghar, V, Rahmani, AM, Ramezanzadeh, K, Rana, J, Ranabhat, CL, Rao, SJ, Rawaf, DL, Rawaf, S, Rawassizadeh, R, Regassa, LD, Rezaei, N, Rezapour, A, Riaz, MA, Ribeiro, AI, Ross, JM, Rubagotti, E, Rumisha, SF, Rwegerera, GM, Moghaddam, SS, Sagar, R, Sahiledengle, B, Sahu, M, Salem, MR, Kafil, HS, Samy, AM, Sartorius, B, Sathian, B, Seidu, A-A, Shaheen, AA, Shaikh, MA, Shamsizadeh, M, Shiferaw, WS, Shin, JI, Shrestha, R, Singh, JA, Skryabin, VY, Skryabina, AA, Soltani, S, Sufiyan, MB, Tabuchi, T, Tadesse, EG, Taveira, N, Tesfay, FH, Thapar, R, Tovani-Palone, MR, Tsegaye, GW, Umeokonkwo, CD, Unnikrishnan, B, Villafañe, JH, Violante, FS, Vo, B, Vu, GT, Wado, YD, Waheed, Y, Wamai, RG, Wang, Y, Ward, P, Wickramasinghe, ND, Wilson, K, Yaya, S, Yip, P, Yonemoto, N, Yu, C, Zastrozhin, MS, Zhang, Y, Zhang, Z-J, Hay, SI, Dwyer-Lindgren, L, Local Burden of Disease sub-Saharan Africa HIV Prevalence Collaborators, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Haeuser, Emily, Serfes, Audrey L., Cork, Michael A., Yang, Mingyou, Ahmed, Muktar Beshir, Dwyer Lindgrena, Laura, HUS Comprehensive Cancer Center, Helsinki University Hospital Area, Department of Oncology, Epidemiologie, and RS: NUTRIM - R3 - Respiratory & Age-related Health
Subjects: Male, Adult, Settore MED/17 - Malattie Infettive, Adolescent, Settore MED/42 - Igiene Generale e Applicata, HIV Infections, Settore MED/01 - Statistica Medica, Young Adult, HIV Infections/prevention & control, Pregnancy, Seroepidemiologic Studies, General & Internal Medicine, Prevalence, Humans, Geostatistics, Africa, Demographics, HIV, HIV prevalence, Mapping, Spatial statistics, 11 Medical and Health Sciences, Africa South of the Sahara, Acquired Immunodeficiency Syndrome, Acquired Immunodeficiency Syndrome/epidemiology, General Medicine, Middle Aged, Settore SECS-S/04 - Demografia, Africa South of the Sahara/epidemiology, 3142 Public health care science, environmental and occupational health, 3121 General medicine, internal medicine and other clinical medicine, Female
Abstract: Background Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15–59 years across SSA. Methods We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. Results We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. Conclusions As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA.
Published: 2022

2. Spending on health and HIV/AIDS: domestic health spending and development assistance in 188 countries, 1995–2015

Author: Dieleman, JL, Haakenstad, A, Micah, A, Moses, M, Abbafati, C, Acharya, P, Adhikari, TB, Adou, AK, Ahmad Kiadaliri, A, Alam, K, Alizadeh-Navaei, R, Rai, RK, Ram, U, Ranabhat, CL, Ray, SE, Global Burden of Disease Health Financing Collaborator Network, Alkerwi, A, Ammar, W, Antonio, CAT, Aremu, O, Asgedom, SW, Atey, TM, Avila-Burgos, L, Awasthi, A, Ayer, R, Badali, H, Banach, M, Banstola, A, Barac, A, Belachew, AB, Birungi, C, Bragazzi, NL, Breitborde, NJK, Cahuana-Hurtado, L, Car, J, Catalá-López, F, Chapin, A, Dandona, L, Dandona, R, Daryani, A, Dharmaratne, SD, Dubey, M, Edessa, D, Eldrenkamp, E, Eshrati, B, Faro, A, Feigl, AB, Fenny, AP, Fischer, F, Foigt, N, Foreman, KJ, Fullman, N, Ghimire, M, Goli, S, Hailu, AD, Hamidi, S, Harb, HL, Hay, SI, Hendrie, D, Ikilezi, G, Javanbakht, M, John, D, Jonas, JB, Kaldjian, A, Kasaeian, A, Kates, J, Khalil, IA, Khang, YH, Khubchandani, J, Kim, YJ, Kinge, JM, Kosen, S, Krohn, KJ, Kumar, GA, Lam, H, Listl, S, Magdy Abd El Razek, H, Magdy Abd El Razek, M, Majeed, A, Malekzadeh, R, Malta, DC, Mensah, GA, Meretoja, A, Miller, TR, Mirrakhimov, EM, Mlashu, FW, Mohammed, E, Mohammed, S, Naghavi, M, Nangia, V, Ngalesoni, FN, Nguyen, CT, Nguyen, TH, Niriayo, Y, Noroozi, M, Owolabi, MO, Pereira, DM, Qorbani, M, Rafay, A, Rafiei, A, and Rahimi-Movaghar, V
Abstract: Copyright © 2018 The Author(s). Background: Comparable estimates of health spending are crucial for the assessment of health systems and to optimally deploy health resources. The methods used to track health spending continue to evolve, but little is known about the distribution of spending across diseases. We developed improved estimates of health spending by source, including development assistance for health, and, for the first time, estimated HIV/AIDS spending on prevention and treatment and by source of funding, for 188 countries. Methods: We collected published data on domestic health spending, from 1995 to 2015, from a diverse set of international agencies. We tracked development assistance for health from 1990 to 2017. We also extracted 5385 datapoints about HIV/AIDS spending, between 2000 and 2015, from online databases, country reports, and proposals submitted to multilateral organisations. We used spatiotemporal Gaussian process regression to generate complete and comparable estimates for health and HIV/AIDS spending. We report most estimates in 2017 purchasing-power parity-adjusted dollars and adjust all estimates for the effect of inflation. Findings: Between 1995 and 2015, global health spending per capita grew at an annualised rate of 3·1% (95% uncertainty interval [UI] 3·1 to 3·2), with growth being largest in upper-middle-income countries (5·4% per capita [UI 5·3–5·5]) and lower-middle-income countries (4·2% per capita [4·2–4·3]). In 2015, $9·7 trillion (9·7 trillion to 9·8 trillion) was spent on health worldwide. High-income countries spent $6·5 trillion (6·4 trillion to 6·5 trillion) or 66·3% (66·0 to 66·5) of the total in 2015, whereas low-income countries spent $70·3 billion (69·3 billion to 71·3 billion) or 0·7% (0·7 to 0·7). Between 1990 and 2017, development assistance for health increased by 394·7% ($29·9 billion), with an estimated $37·4 billion of development assistance being disbursed for health in 2017, of which $9·1 billion (24·2%) targeted HIV/AIDS. Between 2000 and 2015, $562·6 billion (531·1 billion to 621·9 billion) was spent on HIV/AIDS worldwide. Governments financed 57·6% (52·0 to 60·8) of that total. Global HIV/AIDS spending peaked at 49·7 billion (46·2–54·7) in 2013, decreasing to $48·9 billion (45·2 billion to 54·2 billion) in 2015. That year, low-income and lower-middle-income countries represented 74·6% of all HIV/AIDS disability-adjusted life-years, but just 36·6% (34·4 to 38·7) of total HIV/AIDS spending. In 2015, $9·3 billion (8·5 billion to 10·4 billion) or 19·0% (17·6 to 20·6) of HIV/AIDS financing was spent on prevention, and $27·3 billion (24·5 billion to 31·1 billion) or 55·8% (53·3 to 57·9) was dedicated to care and treatment. Interpretation: From 1995 to 2015, total health spending increased worldwide, with the fastest per capita growth in middle-income countries. While these national disparities are relatively well known, low-income countries spent less per person on health and HIV/AIDS than did high-income and middle-income countries. Furthermore, declines in development assistance for health continue, including for HIV/AIDS. Additional cuts to development assistance could hasten this decline, and risk slowing progress towards global and national goals. Funding: The Bill & Melinda Gates Foundation. The Bill & Melinda Gates Foundation.
Published: 2018

3. Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

Author: Dieleman, JL, Sadat, N, Chang, AY, Fullman, N, Abbafati, C, Acharya, P, Adou, AK, Ahmad Kiadaliri, A, Alam, K, Alizadeh-Navaei, R, Alkerwi, A, Rafay, A, Rafiei, A, Global Burden of Disease Health Financing Collaborator Network, Ammar, W, Antonio, CAT, Aremu, O, Asgedom, SW, Atey, TM, Avila-Burgos, L, Ayer, R, Badali, H, Banach, M, Banstola, A, Barac, A, Belachew, AB, Birungi, C, Bragazzi, NL, Breitborde, NJK, Cahuana-Hurtado, L, Car, J, Catalá-López, F, Chapin, A, Chen, CS, Dandona, L, Dandona, R, Daryani, A, Dharmaratne, SD, Dubey, M, Edessa, D, Eldrenkamp, E, Eshrati, B, Faro, A, Feigl, AB, Fenny, AP, Fischer, F, Foigt, N, Foreman, KJ, Ghimire, M, Goli, S, Hailu, AD, Hamidi, S, Harb, HL, Hay, SI, Hendrie, D, Ikilezi, G, Javanbakht, M, John, D, Jonas, JB, Kaldjian, A, Kasaeian, A, Kasahun, YC, Khalil, IA, Khang, YH, Khubchandani, J, Kim, YJ, Kinge, JM, Kosen, S, Krohn, KJ, Kumar, GA, Lafranconi, A, Lam, H, Listl, S, Magdy Abd El Razek, H, Magdy Abd El Razek, M, Majeed, A, Malekzadeh, R, Malta, DC, Martinez, G, Mensah, GA, Meretoja, A, Micah, A, Miller, TR, Mirrakhimov, EM, Mlashu, FW, Mohammed, E, Mohammed, S, Moses, M, Mousavi, SM, Naghavi, M, Nangia, V, Ngalesoni, FN, Nguyen, CT, Nguyen, TH, Niriayo, Y, Noroozi, M, Owolabi, MO, Patel, T, Pereira, DM, Polinder, S, and Qorbani, M
Abstract: This online publication has been corrected. The corrected version first appeared at thelancet.com on May 3, 2018 © 2018 The Author(s). Background: Achieving universal health coverage (UHC) requires health financing systems that provide prepaid pooled resources for key health services without placing undue financial stress on households. Understanding current and future trajectories of health financing is vital for progress towards UHC. We used historical health financing data for 188 countries from 1995 to 2015 to estimate future scenarios of health spending and pooled health spending through to 2040. Methods: We extracted historical data on gross domestic product (GDP) and health spending for 188 countries from 1995 to 2015, and projected annual GDP, development assistance for health, and government, out-of-pocket, and prepaid private health spending from 2015 through to 2040 as a reference scenario. These estimates were generated using an ensemble of models that varied key demographic and socioeconomic determinants. We generated better and worse alternative future scenarios based on the global distribution of historic health spending growth rates. Last, we used stochastic frontier analysis to investigate the association between pooled health resources and UHC index, a measure of a country's UHC service coverage. Finally, we estimated future UHC performance and the number of people covered under the three future scenarios. Findings: In the reference scenario, global health spending was projected to increase from US$10 trillion (95% uncertainty interval 10 trillion to 10 trillion) in 2015 to $20 trillion (18 trillion to 22 trillion) in 2040. Per capita health spending was projected to increase fastest in upper-middle-income countries, at 4·2% (3·4–5·1) per year, followed by lower-middle-income countries (4·0%, 3·6–4·5) and low-income countries (2·2%, 1·7–2·8). Despite global growth, per capita health spending was projected to range from only $40 (24–65) to $413 (263–668) in 2040 in low-income countries, and from $140 (90–200) to $1699 (711–3423) in lower-middle-income countries. Globally, the share of health spending covered by pooled resources would range widely, from 19·8% (10·3–38·6) in Nigeria to 97·9% (96·4–98·5) in Seychelles. Historical performance on the UHC index was significantly associated with pooled resources per capita. Across the alternative scenarios, we estimate UHC reaching between 5·1 billion (4·9 billion to 5·3 billion) and 5·6 billion (5·3 billion to 5·8 billion) lives in 2030. Interpretation: We chart future scenarios for health spending and its relationship with UHC. Ensuring that all countries have sustainable pooled health resources is crucial to the achievement of UHC. The Bill & Melinda Gates Foundation.
Published: 2018

4. 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

Author: 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, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, 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, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, 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, and Murray, CJL
Published: 2017

5. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015 : the Global Burden of Disease Study 2015

Author: GBD 2015 HIV Collaborators, Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Mills, EJ, Trickey, A, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Salomon, J, Larson, HJ, Friedman, J, Abajobir, AA, Abate, KH, Abbas, KM, Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Abubakar, I, Abu-Raddad, LJ, Abu-Rmeileh, NM, Abyu, GY, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adofo, K, Adou, AK, Ajala, ON, Akinyemiju, TF, Akseer, N, Lami, FH, Al-Aly, Z, Alam, K, Alam, NK, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alegretti, MA, Aleman, AV, Alemu, ZA, Alfonso-Cristancho, R, Ali, R, Alkerwi, A, Alla, F, Mohammad, R, Al-Raddadi, S, Alsharif, U, Alvarez, E, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Antonio, CA, Anwari, P, Ärnlöv, J, Artaman, A, Asayesh, H, Asghar, RJ, Assadi, R, Atique, S, Atkins, LS, Avokpaho, EF, Awasthi, A, Quintanilla, BP, Bacha, U, Badawi, A, Barac, A, Bärnighausen, T, Basu, A, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, N, Bennett, DA, Bensenor, IM, Betsu, BD, Beyene, AS, Bhatia, E, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Bisanzio, D, Brainin, M, Brazinova, A, Breitborde, NJ, Brown, A, Burch, M, Butt, ZA, Campuzano, JC, Cárdenas, R, Carrero, JJ, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Chang, HY, Chang, JC, Chavan, L, Chen, W, Chiang, PP, Chibalabala, M, Chisumpa, VH, Choi, JY, Christopher, DJ, Ciobanu, LG, Cooper, C, Dahiru, T, Damtew, SA, Dandona, L, Dandona, R, Das Neves, J, De Jager, P, De Leo, D, Degenhardt, L, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dharmaratne, SD, Ding, EL, Doshi, PP, Driscoll, TR, Dubey, M, Elshrek, YM, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faghmous, ID, Farinha, CS, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, SM, Fernandes, JC, Fischer, F, Fitchett, JR, Foigt, N, Fullman, N, Fürst, T, Gankpé, FG, Gebre, T, Gebremedhin, AT, Gebru, AA, Geleijnse, JM, Gessner, BD, Gething, PW, Ghiwot, TT, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Goodridge, A, Gopalani, SV, Goto, A, Gugnani, HC, Guimaraes, MD, Gupta, R, Gupta, V, Haagsma, J, Hafezi-Nejad, N, Hagan, H, Hailu, GB, Hamadeh, RR, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Harikrishnan, S, Haro, JM, Harun, KM, Havmoeller, R, Hedayati, MT, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Hsairi, M, Hu, G, Huang, H, Huang, JJ, Iburg, KM, Idrisov, BT, Innos, K, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karema, CK, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Keiyoro, PN, Kemp, AH, Kengne, AP, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khang, YH, Khubchandani, J, Kim, YJ, Kinfu, Y, Kivipelto, M, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Defo, BK, Bicer, BK, Kulkarni, VS, Kumar, GA, Lal, DK, 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Subjects: GBD 2015 HIV Collaborators
Abstract: BACKGROUND: Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. METHODS: For countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. FINDINGS: Global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1-3·4 million). Annual incidence has stayed relatively constant at about 2·6 million per year (range 2·5-2·8 million) since 2005, after a period of fast decline between 1997 and 2005. The number of people living with HIV/AIDS has been steadily increasing and reached 38·8 million (95% UI 37·6-40·4 million) in 2015. At the same time, HIV/AIDS mortality has been declining at a steady pace, from a peak of 1·8 million deaths (95% UI 1·7-1·9 million) in 2005, to 1·2 million deaths (1·1-1·3 million) in 2015. We recorded substantial heterogeneity in the levels and trends of HIV/AIDS across countries. Although many countries have experienced decreases in HIV/AIDS mortality and in annual new infections, other countries have had slowdowns or increases in rates of change in annual new infections. INTERPRETATION: Scale-up of ART and prevention of mother-to-child transmission has been one of the great successes of global health in the past two decades. However, in the past decade, progress in reducing new infections has been slow, development assistance for health devoted to HIV has stagnated, and resources for health in low-income countries have grown slowly. Achievement of the new ambitious goals for HIV enshrined in Sustainable Development Goal 3 and the 90-90-90 UNAIDS targets will be challenging, and will need continued efforts from governments and international agencies in the next 15 years to end AIDS by 2030. Funding: We thank the countless individuals who have contributed to the Global Burden of Disease (GBD) Study 2015 in various capacities. We specifically thank Jeffrey Eaton and John Stover. HW and CJLM received funding for this study from the Bill & Melinda Gates Foundation; the National Institute of Mental Health, National Institutes of Health (NIH; R01MH110163); and the National Institute on Aging, NIH (P30AG047845). LJAR acknowledges the support of Qatar National Research Fund (NPRP 04-924-3-251) who provided the main funding for generating the data provided to the GBD-Institute for Health Metrics and Evaluation effort. BPAQ acknowledges institutional support from PRONABEC (National Program of Scholarship and Educational Loan), provided by the Peruvian government. DB is supported by the Bill & Melinda Gates Foundation (grant number OPP1068048). JDN was supported in his contribution to this work by a Fellowship from Fundacao para a Ciencia e a Tecnologia, Portugal (SFRH/BPD/92934/2013). KD is supported by a Wellcome Trust Fellowship in Public Health and Tropical Medicine (grant number 099876). TF received financial support from the Swiss National Science Foundation (SNSF; project number P300P3-154634). AG acknowledges funding from Sistema Nacional de Investigadores de Panama-SNI. PJ is supported by Wellcome Trust-DBT India Alliance Clinical and Public Health Intermediate Fellowship. MK receives research support from the Academy of Finland, the Swedish Research Council, Alzheimerfonden, Alzheimer's Research & Prevention Foundation, Center for Innovative Medicine (CIMED) at Karolinska Institutet South Campus, AXA Research Fund, Wallenberg Clinical Scholars Award from the Knut och Alice Wallenbergs Foundation, and the Sheika Salama Bint Hamdan Al Nahyan Foundation. AK's work was 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). SML is funded by a National Institute for Health Research (NIHR) Clinician Scientist Fellowship (grant number NIHR/CS/010/014). HJL reports grants from the NIHR, EU Innovative Medicines Initiative, Centre for Strategic & International Studies, and WHO. WM is Program analyst, Population and Development, in the Peru Country Office of the United Nations Population Fund, which does not necessarily endorse this study. For UOM, funding from the German National Cohort Consortium (O1ER1511D) is gratefully acknowledged. KR reports grants from NIHR Oxford Biomedical Research Centre, NIHR Career Development Fellowship, and Oxford Martin School during the conduct of the study. GR acknowledges that work related to this paper has been done on the behalf of the GBD Genitourinary Disease Expert Group supported by the International Society of Nephrology (ISN). ISS reports grants from FAPESP (Brazilian public agency). RSS receives institutional support from Universidad de Ciencias Aplicadas y Ambientales, UDCA, Bogota Colombia. SS receives postdoctoral funding from the Fonds de la recherche en sante du Quebec (FRSQ), including its renewal. RTS was supported in part by grant number PROMETEOII/2015/021 from Generalitat Valenciana and the national grant PI14/00894 from ISCIII-FEDER. PY acknowledges support from Strategic Public Policy Research (HKU7003-SPPR-12).
Published: 2016

6. 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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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. Abdel, Abera, Semaw F., Aboyans, Victor, Abraham, Jerry P., Abraham, Biju, Abubakar, Ibrahim, Abu-Raddad, Laith J., Abu-Rmeileh, Niveen M.E., Aburto, Tania C., Achoki, Tom, Ackerman, Ilana N., Adelekan, Ademola, Ademi, Zanfina, Adou, Arsène K., Adsuar, Josef C., Arnlov, Johan, Agardh, Emilie E., Al Khabouri, Mazin J., Alam, Sayed Saidul, Alasfoor, Deena, Albittar, Mohammed I., Alegretti, Miguel A., Aleman, Alicia V., Alemu, Zewdie A., Alfonso-Cristancho, Rafael, Alhabib, Samia, Ali, Raghib, Alla, Francoi, Allebeck, Peter, Allen, Peter J., Almazroa, Mohammad Abdulaziz, Alsharif, Ubai, Alvarez, Elena, Alvis-Guzman, Nelson, Ameli, Omid, Amini, Heresh, Ammar, Walid, Anderson, Benjamin O., Anderson, H. Ro, Antonio, Carl Abelardo T., Anwari, Palwasha, Apfel, Henry, Arsenijevic, Valentain S. 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
Subjects: 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.
Published: 2015

7. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015: the Global Burden of Disease Study 2015

Author: Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Mills, EJ, Trickey, A, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Salomon, J, Larson, HJ, Friedman, J, Abajobir, AA, Abate, KH, Abbas, KM, Abd El Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Abubakar, I, Abu-Raddad, LJ, Abu-Rmeileh, NME, Abyu, GY, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adofo, K, Adou, AK, Ajala, ON, Akinyemiju, TF, Akseer, N, Al Lami, FH, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SFS, Aldridge, RW, Alegretti, MA, Aleman, AV, Alemu, ZA, Alfonso-Cristancho, R, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, RMS, Alsharif, U, Alvarez, E, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Antonio, CAT, Anwari, P, Arnlov, J, Al, A, Asayesh, H, Asghar, RJ, Assadi, R, Atique, S, Atkins, LS, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Bacha, U, Badawi, A, Barac, A, Barnighausen, T, Basu, A, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, N, Bennett, DA, Bensenor, IM, Betsu, BD, Beyene, AS, Bhatia, E, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Bisanzio, D, Brainin, M, Brazinova, A, Breitborde, NJK, Brown, A, Burch, M, Butt, ZA, Campuzano, JC, Cardenas, R, Carrero, JJ, Castaneda-Orjuela, CA, Rivas, JC, Catala-Lopez, F, Chang, H-Y, Chang, J-C, Chavan, L, Chen, W, Chiang, PP-C, Chibalabala, M, Chisumpa, VH, Choi, J-YJ, Christopher, DJ, Ciobanu, LG, Cooper, C, Dahiru, T, Damtew, SA, Dandona, L, Dandona, R, das Neves, J, de Jager, P, De Leo, D, Degenhardt, L, Dellavalle, RP, Deribe, K, Deribew, A, Jarlais, DCD, Dharmaratne, SD, Ding, EL, Doshi, PP, Driscoll, TR, Dubey, M, Elshrek, YM, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faghmous, IDA, Sofia e Sa Farinha, C, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fernandes, JC, Fischer, F, Fitchett, JRA, Foigt, N, Fullman, N, Furst, T, Gankpe, FG, Gebre, T, Gebremedhin, AT, Gebru, AA, Geleijnse, JM, Gessner, BD, Gething, PW, Ghiwot, TT, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Goodridge, A, Gopalani, SV, Goto, A, Gugnani, HC, Guimaraes, MDC, Gupta, R, Gupta, V, Haagsma, J, Hafezi-Nejad, N, Hagan, H, Hailu, GB, Hamadeh, RR, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Harikrishnan, S, Haro, JM, Harun, KM, Havmoeller, R, Hedayati, MT, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Hsairi, M, Hu, G, Huang, H, Huang, JJ, Iburg, KM, Idrisov, BT, Innos, K, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karema, CK, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Keiyoro, PN, Kemp, AH, Kengne, AP, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khang, Y-H, Khubchandani, J, Kim, YJ, Kinfu, Y, Kivipelto, M, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Defo, BK, Bicer, BK, Kulkarni, VS, Kumar, GA, Lal, DK, Lam, H, Lam, JO, Langan, SM, Lansingh, VC, Larsson, A, Leigh, J, Leung, R, Li, Y, Lim, SS, Lipshultz, SE, Liu, S, Lloyd, BK, Logroscino, G, Lotufo, PA, Lunevicius, R, Abd El Razek, HM, Mahdavi, M, Majdan, M, Majeed, A, Makhlouf, C, Malekzadeh, R, Mapoma, CC, Marcenes, W, Martinez-Raga, J, Marzan, MB, Masiye, F, Mason-Jones, AJ, Mayosi, BM, Mckee, M, Meaney, PA, Mehndiratta, MM, Mekonnen, AB, Melaku, YA, Memiah, P, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mikesell, J, Mirarefin, M, Mohammad, KA, Mohammed, S, Mokdad, AH, Monasta, L, Moradi-Lakeh, M, Mori, R, Mueller, UO, Murimira, B, Murthy, GVS, Naheed, A, Naldi, L, Nangia, V, Nash, D, Nawaz, H, Nejjari, C, Ngalesoni, FN, Ngirabega, JDD, Quyen, LN, Nisar, MI, Norheim, OF, Norman, RE, Nyakarahuka, L, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Padukudru, MA, Park, H-Y, Park, J-H, Patil, ST, Patten, SB, Paul, VK, Pearson, K, Peprah, EK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Plass, D, Polinder, S, Pourmalek, F, Prokop, DM, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Rajsic, S, Ram, U, Rana, SM, Rao, PV, Remuzzi, G, Rojas-Rueda, D, Ronfani, L, Roshandel, G, Roy, A, Ruhago, GM, Saeedi, MY, Sagar, R, Saleh, MM, Sanabria, JR, Santos, IS, Sarmiento-Suarez, R, Sartorius, B, Sawhney, M, Schutte, AE, Schwebel, DC, Seedat, S, Sepanlou, SG, Servan-Mori, EE, Shaikh, MA, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shibuya, K, Shin, HH, Sigfusdottir, ID, Silpakit, N, Santos Silva, DA, Alves Silveira, DG, Simard, EP, Sindi, S, Singh, JA, Singh, OP, Singh, PK, Skirbekk, V, Sliwa, K, Soneji, S, Sorensen, RJD, Soriano, JB, Soti, DO, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Sunguya, BF, Swaminathan, S, Sykes, BL, Tabares-Seisdedos, R, Talongwa, RT, Tavakkoli, M, Taye, B, Tedla, BA, Tekle, T, Shifa, GT, Temesgen, AM, Terkawi, AS, Tesfay, FH, Tessema, GA, Thapa, K, Thomson, AJ, Thorne-Lyman, AL, Tobe-Gai, R, Topor-Madry, R, Towbin, JA, Bach, XT, Dimbuene, ZT, Tsilimparis, N, Tura, AK, Ukwaja, KN, Uneke, CJ, Uthman, OA, Venketasubramanian, N, Vladimirov, SK, Vlassov, VV, Vollset, SE, Wang, L, Weiderpass, E, Weintraub, RG, Werdecker, A, Westerman, R, Wijeratne, T, Wilkinson, JD, Wiysonge, CS, Wolfe, CDA, Won, S, Wong, JQ, Xu, G, Yadav, AK, Yakob, B, Yalew, AZ, Yano, Y, Yaseri, M, Yebyo, HG, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Yu, S, Zaidi, Z, Zaki, MES, Zeeb, H, Zhang, H, Zhao, Y, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Lopez, AD, Murray, CJL, Wang, H, Wolock, TM, Carter, A, Nguyen, G, Kyu, HH, Gakidou, E, Hay, SI, Mills, EJ, Trickey, A, Msemburi, W, Coates, MM, Mooney, MD, Fraser, MS, Sligar, A, Salomon, J, Larson, HJ, Friedman, J, Abajobir, AA, Abate, KH, Abbas, KM, Abd El Razek, MM, Abd-Allah, F, Abdulle, AM, Abera, SF, Abubakar, I, Abu-Raddad, LJ, Abu-Rmeileh, NME, Abyu, GY, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adofo, K, Adou, AK, Ajala, ON, Akinyemiju, TF, Akseer, N, Al Lami, FH, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SFS, Aldridge, RW, Alegretti, MA, Aleman, AV, Alemu, ZA, Alfonso-Cristancho, R, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, RMS, Alsharif, U, Alvarez, E, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Antonio, CAT, Anwari, P, Arnlov, J, Al, A, Asayesh, H, Asghar, RJ, Assadi, R, Atique, S, Atkins, LS, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Bacha, U, Badawi, A, Barac, A, Barnighausen, T, Basu, A, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, N, Bennett, DA, Bensenor, IM, Betsu, BD, Beyene, AS, Bhatia, E, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Bisanzio, D, Brainin, M, Brazinova, A, Breitborde, NJK, Brown, A, Burch, M, Butt, ZA, Campuzano, JC, Cardenas, R, Carrero, JJ, Castaneda-Orjuela, CA, Rivas, JC, Catala-Lopez, F, Chang, H-Y, Chang, J-C, Chavan, L, Chen, W, Chiang, PP-C, Chibalabala, M, Chisumpa, VH, Choi, J-YJ, Christopher, DJ, 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Huang, JJ, Iburg, KM, Idrisov, BT, Innos, K, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karema, CK, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Keiyoro, PN, Kemp, AH, Kengne, AP, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khang, Y-H, Khubchandani, J, Kim, YJ, Kinfu, Y, Kivipelto, M, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Defo, BK, Bicer, BK, Kulkarni, VS, Kumar, GA, Lal, DK, Lam, H, Lam, JO, Langan, SM, Lansingh, VC, Larsson, A, Leigh, J, Leung, R, Li, Y, Lim, SS, Lipshultz, SE, Liu, S, Lloyd, BK, Logroscino, G, Lotufo, PA, Lunevicius, R, Abd El Razek, HM, Mahdavi, M, Majdan, M, Majeed, A, Makhlouf, C, Malekzadeh, R, Mapoma, CC, Marcenes, W, Martinez-Raga, J, Marzan, MB, Masiye, F, Mason-Jones, AJ, Mayosi, BM, Mckee, M, Meaney, PA, Mehndiratta, MM, Mekonnen, AB, Melaku, YA, Memiah, P, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mikesell, J, Mirarefin, M, Mohammad, KA, Mohammed, S, Mokdad, AH, Monasta, L, Moradi-Lakeh, M, Mori, R, Mueller, UO, Murimira, B, Murthy, GVS, Naheed, A, Naldi, L, Nangia, V, Nash, D, Nawaz, H, Nejjari, C, Ngalesoni, FN, Ngirabega, JDD, Quyen, LN, Nisar, MI, Norheim, OF, Norman, RE, Nyakarahuka, L, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Padukudru, MA, Park, H-Y, Park, J-H, Patil, ST, Patten, SB, Paul, VK, Pearson, K, Peprah, EK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Plass, D, Polinder, S, Pourmalek, F, Prokop, DM, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Rajsic, S, Ram, U, Rana, SM, Rao, PV, Remuzzi, G, Rojas-Rueda, D, Ronfani, L, Roshandel, G, Roy, A, Ruhago, GM, Saeedi, MY, Sagar, R, Saleh, MM, Sanabria, JR, Santos, IS, Sarmiento-Suarez, R, Sartorius, B, Sawhney, M, Schutte, AE, 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HG, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Yu, S, Zaidi, Z, Zaki, MES, Zeeb, H, Zhang, H, Zhao, Y, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Lopez, AD, and Murray, CJL
Abstract: BACKGROUND: Timely assessment of the burden of HIV/AIDS is essential for policy setting and programme evaluation. In this report from the Global Burden of Disease Study 2015 (GBD 2015), we provide national estimates of levels and trends of HIV/AIDS incidence, prevalence, coverage of antiretroviral therapy (ART), and mortality for 195 countries and territories from 1980 to 2015. METHODS: For countries without high-quality vital registration data, we estimated prevalence and incidence with data from antenatal care clinics and population-based seroprevalence surveys, and with assumptions by age and sex on initial CD4 distribution at infection, CD4 progression rates (probability of progression from higher to lower CD4 cell-count category), on and off antiretroviral therapy (ART) mortality, and mortality from all other causes. Our estimation strategy links the GBD 2015 assessment of all-cause mortality and estimation of incidence and prevalence so that for each draw from the uncertainty distribution all assumptions used in each step are internally consistent. We estimated incidence, prevalence, and death with GBD versions of the Estimation and Projection Package (EPP) and Spectrum software originally developed by the Joint United Nations Programme on HIV/AIDS (UNAIDS). We used an open-source version of EPP and recoded Spectrum for speed, and used updated assumptions from systematic reviews of the literature and GBD demographic data. For countries with high-quality vital registration data, we developed the cohort incidence bias adjustment model to estimate HIV incidence and prevalence largely from the number of deaths caused by HIV recorded in cause-of-death statistics. We corrected these statistics for garbage coding and HIV misclassification. FINDINGS: Global HIV incidence reached its peak in 1997, at 3·3 million new infections (95% uncertainty interval [UI] 3·1-3·4 million). Annual incidence has stayed relatively constant at about 2·6 million per year (range 2·5-2·8 mi
Published: 2016

8. Global, regional, and national levels of maternal mortality, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

Author: Kassebaum, NJ, Barber, RM, Bhutta, ZA, Dandona, L, Gething, PW, Hay, SI, Kinfu, Y, Larson, HJ, Liang, X, Lim, SS, Lopez, AD, Lozano, R, Mensah, GA, Mokdad, AH, Naghavi, M, Pinho, C, Salomon, JA, Steiner, C, Vos, T, Wang, H, Abajobir, AA, Abate, KH, Abbas, KM, Abd-Allah, F, Abdallat, MA, Abdulle, AM, Abera, SF, Aboyans, V, Abubakar, I, Abu-Rmeileh, NME, Achoki, T, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adou, AK, Afanvi, KA, Agarwal, A, Kiadaliri, AA, Ajala, ON, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alhabib, S, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, R, Alsharif, U, Martin, EA, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Andersen, HH, Anderson, GM, Antoine, RM, Antonio, CAT, Aregay, AF, Arnlov, J, Arora, M, Arsenijevic, VSA, Al, A, Asayesh, H, Atique, S, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Azzopardi, P, Bacha, U, Badawi, A, Bahit, MC, Balakrishnan, K, Banerjee, A, Barac, A, Barker-Collo, SL, Barnighausen, T, Basu, S, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, NW, Bekele, T, Bell, ML, Bennett, DA, Bensenor, IM, Berhane, A, Bernabe, E, Betsu, BD, Beyene, AS, Biadgilign, S, Bikbov, B, Bin Abdulhak, AA, Biroscak, BJ, Biryukov, S, Bisanzio, D, Bjertness, E, Blore, JD, Brainin, M, Brazinova, A, Breitborde, NJK, Brugha, TS, Butt, ZA, Campos-Nonato, IR, Campuzano, JC, Cardenas, R, Carrero, JJ, Carter, A, Casey, DC, Castaneda-Oquela, CA, Castro, RE, Catala-Lopez, F, Cavalleri, F, Chang, H-Y, Chang, J-C, Chavan, L, Chibueze, CE, Chisumpa, VH, Choi, J-YJ, Chowdhury, R, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coates, MM, Coggeshall, M, Colistro, V, Colquhoun, SM, Cooper, C, Cooper, LT, Cortinovis, M, Dahiru, T, Damasceno, A, Danawi, H, Dandona, R, Das Neves, J, De Leo, D, Dellavalle, RP, Deribe, K, Deribew, A, Jarlais, DCD, Dharmaratne, SD, Dicker, DJ, Ding, EL, Dossou, E, Dubey, M, Ebel, BE, Ellingsen, CL, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fernandes, JC, Fischer, F, Fitchett, JRA, Fleming, T, Gt, NF, Franca, EB, Franklin, RC, Fraser, MS, Friedman, J, Pullman, N, Furst, T, Futran, ND, Gambashidze, K, Gamkrelidze, A, Gebre, T, Gebrehiwot, TT, Gebremedhin, AT, Gebremedhin, M, Gebru, AA, Geleijnse, JM, Gibney, KB, Giref, AZ, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Gomez-Dantes, H, Gona, P, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Gugnani, HC, Guo, Y, Gupta, R, Gupta, V, Hafezi-Nejad, N, Hailu, AD, Hailu, GB, Hamadeh, RR, Hamidi, S, Hancock, J, Handal, AJ, Hankey, GJ, Harb, HL, Harikrishnan, S, Harun, KM, Havmoeller, R, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huybrechts, I, Huynh, C, Iannarone, M, Iburg, KM, Idrisov, BT, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jee, SH, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Kazanjan, K, Kazi, DS, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Keren, A, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khan, AR, Khan, EA, Khang, Y-H, Khonelidze, I, Khosravi, A, Khubchandani, J, Kim, YJ, Kivipelto, M, Knibbs, LD, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Krishnaswami, S, Defo, BK, Bicer, BK, Kudom, AA, Kulikoff, XR, Kulkarni, C, Kumar, GA, Kutz, MJ, Lal, DK, Lalloo, R, Lam, H, Lamadrid-Figueroa, H, Lan, Q, Larsson, A, Laryea, DO, Leigh, J, Leung, R, Li, Y, Lipshultz, SE, Liu, PY, Liu, S, Liu, Y, Lloyd, BK, Lotufo, PA, Lunevicius, R, Ma, S, El Razek, HMA, El Razek, MMA, Majdan, M, Majeed, A, Malekzadeh, R, Mapoma, CC, Marcenes, W, Margolis, DJ, Marquez, N, Masiye, F, Marzan, MB, Mason-Jones, AJ, Mazorodze, TT, Meaney, PA, Mehari, A, Mehndiratta, MM, Mena-Rodriguez, F, Mekonnen, AB, Melaku, YA, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mills, EJ, Mirarefin, M, Misganaw, A, Ibrahim, NM, Mohammad, KA, Mohammadi, A, Mohammed, S, Mola, GLD, Monasta, L, Monis, JDLC, Hernandez, JCM, Montero, P, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Morawska, L, Mori, R, Mueller, U, Murthy, GVS, Murthy, S, Nachega, JB, Naheed, A, Naldi, L, Nand, D, Nangia, V, Nash, D, Neupane, S, Newton, JN, Ng, M, Ngalesoni, FN, Nguhiu, P, Nguyen, G, Le Nguyen, Q, Nisar, MI, Nomura, M, Norheim, OF, Norman, RE, Nyakarahuka, L, Obermeyer, CM, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olivares, PR, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Oyekale, AS, Pa, M, Pain, A, Papantoniou, N, Park, E-K, Park, H-Y, Caicedo, AJP, Patten, SB, Paul, VK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Pishgar, F, Polinder, S, Pope, D, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Ram, U, Ranabhat, CL, Rangaswamy, T, Rao, PV, Refaat, AH, Remuzzi, G, Violante, FS, Kassebaum, NJ, Barber, RM, Bhutta, ZA, Dandona, L, Gething, PW, Hay, SI, Kinfu, Y, Larson, HJ, Liang, X, Lim, SS, Lopez, AD, Lozano, R, Mensah, GA, Mokdad, AH, Naghavi, M, Pinho, C, Salomon, JA, Steiner, C, Vos, T, Wang, H, Abajobir, AA, Abate, KH, Abbas, KM, Abd-Allah, F, Abdallat, MA, Abdulle, AM, Abera, SF, Aboyans, V, Abubakar, I, Abu-Rmeileh, NME, Achoki, T, Adebiyi, AO, Adedeji, IA, Adelekan, AL, Adou, AK, Afanvi, KA, Agarwal, A, Kiadaliri, AA, Ajala, ON, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, NKM, Alasfoor, D, Aldhahri, SF, Aldridge, RW, Alhabib, S, Ali, R, Alkerwi, A, Alla, F, Al-Raddadi, R, Alsharif, U, Martin, EA, Alvis-Guzman, N, Amare, AT, Amberbir, A, Amegah, AK, Ammar, W, Amrock, SM, Andersen, HH, Anderson, GM, Antoine, RM, Antonio, CAT, Aregay, AF, Arnlov, J, Arora, M, Arsenijevic, VSA, Al, A, Asayesh, H, Atique, S, Avokpaho, EFGA, Awasthi, A, Quintanilla, BPA, Azzopardi, P, Bacha, U, Badawi, A, Bahit, MC, Balakrishnan, K, Banerjee, A, Barac, A, Barker-Collo, SL, Barnighausen, T, Basu, S, Bayou, TA, Bayou, YT, Bazargan-Hejazi, S, Beardsley, J, Bedi, NW, Bekele, T, Bell, ML, Bennett, DA, Bensenor, IM, Berhane, A, Bernabe, E, Betsu, BD, Beyene, AS, Biadgilign, S, Bikbov, B, Bin Abdulhak, AA, Biroscak, BJ, Biryukov, S, Bisanzio, D, Bjertness, E, Blore, JD, Brainin, M, Brazinova, A, Breitborde, NJK, Brugha, TS, Butt, ZA, Campos-Nonato, IR, Campuzano, JC, Cardenas, R, Carrero, JJ, Carter, A, Casey, DC, Castaneda-Oquela, CA, Castro, RE, Catala-Lopez, F, Cavalleri, F, Chang, H-Y, Chang, J-C, Chavan, L, Chibueze, CE, Chisumpa, VH, Choi, J-YJ, Chowdhury, R, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coates, MM, Coggeshall, M, Colistro, V, Colquhoun, SM, Cooper, C, Cooper, LT, Cortinovis, M, Dahiru, T, Damasceno, A, Danawi, H, Dandona, R, Das Neves, J, De Leo, D, Dellavalle, RP, Deribe, K, Deribew, A, Jarlais, DCD, Dharmaratne, SD, Dicker, DJ, Ding, EL, Dossou, E, Dubey, M, Ebel, BE, Ellingsen, CL, Elyazar, I, Endries, AY, Ermakov, SP, Eshrati, B, Esteghamati, A, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fernandes, JC, Fischer, F, Fitchett, JRA, Fleming, T, Gt, NF, Franca, EB, Franklin, RC, Fraser, MS, Friedman, J, Pullman, N, Furst, T, Futran, ND, Gambashidze, K, Gamkrelidze, A, Gebre, T, Gebrehiwot, TT, Gebremedhin, AT, Gebremedhin, M, Gebru, AA, Geleijnse, JM, Gibney, KB, Giref, AZ, Giroud, M, Gishu, MD, Glaser, E, Goenka, S, Gomez-Dantes, H, Gona, P, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Gugnani, HC, Guo, Y, Gupta, R, Gupta, V, Hafezi-Nejad, N, Hailu, AD, Hailu, GB, Hamadeh, RR, Hamidi, S, Hancock, J, Handal, AJ, Hankey, GJ, Harb, HL, Harikrishnan, S, Harun, KM, Havmoeller, R, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Hoy, DG, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huybrechts, I, Huynh, C, Iannarone, M, Iburg, KM, Idrisov, BT, Iyer, VJ, Jacobsen, KH, Jahanmehr, N, Jakovljevic, MB, Javanbakht, M, Jayatilleke, AU, Jee, SH, Jeemon, P, Jha, V, Jiang, G, Jiang, Y, Jibat, T, Jonas, JB, Kabir, Z, Kamal, R, Kan, H, Karch, A, Karletsos, D, Kasaeian, A, Kaul, A, Kawakami, N, Kayibanda, JF, Kazanjan, K, Kazi, DS, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Keren, A, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khan, AR, Khan, EA, Khang, Y-H, Khonelidze, I, Khosravi, A, Khubchandani, J, Kim, YJ, Kivipelto, M, Knibbs, LD, Kokubo, Y, Kosen, S, Koul, PA, Koyanagi, A, Krishnaswami, S, Defo, BK, Bicer, BK, Kudom, AA, Kulikoff, XR, Kulkarni, C, Kumar, GA, Kutz, MJ, Lal, DK, Lalloo, R, Lam, H, Lamadrid-Figueroa, H, Lan, Q, Larsson, A, Laryea, DO, Leigh, J, Leung, R, Li, Y, Lipshultz, SE, Liu, PY, Liu, S, Liu, Y, Lloyd, BK, Lotufo, PA, Lunevicius, R, Ma, S, El Razek, HMA, El Razek, MMA, Majdan, M, Majeed, A, Malekzadeh, R, Mapoma, CC, Marcenes, W, Margolis, DJ, Marquez, N, Masiye, F, Marzan, MB, Mason-Jones, AJ, Mazorodze, TT, Meaney, PA, Mehari, A, Mehndiratta, MM, Mena-Rodriguez, F, Mekonnen, AB, Melaku, YA, Memish, ZA, Mendoza, W, Meretoja, A, Meretoja, TJ, Mhimbira, FA, Miller, TR, Mills, EJ, Mirarefin, M, Misganaw, A, Ibrahim, NM, Mohammad, KA, Mohammadi, A, Mohammed, S, Mola, GLD, Monasta, L, Monis, JDLC, Hernandez, JCM, Montero, P, Montico, M, Mooney, MD, Moore, AR, Moradi-Lakeh, M, Morawska, L, Mori, R, Mueller, U, Murthy, GVS, Murthy, S, Nachega, JB, Naheed, A, Naldi, L, Nand, D, Nangia, V, Nash, D, Neupane, S, Newton, JN, Ng, M, Ngalesoni, FN, Nguhiu, P, Nguyen, G, Le Nguyen, Q, Nisar, MI, Nomura, M, Norheim, OF, Norman, RE, Nyakarahuka, L, Obermeyer, CM, Ogbo, FA, Oh, I-H, Ojelabi, FA, Olivares, PR, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ota, E, Oyekale, AS, Pa, M, Pain, A, Papantoniou, N, Park, E-K, Park, H-Y, Caicedo, AJP, Patten, SB, Paul, VK, Pereira, DM, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pillay, JD, Pishgar, F, Polinder, S, Pope, D, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rahman, SU, Rai, RK, Ram, U, Ranabhat, CL, Rangaswamy, T, Rao, PV, Refaat, AH, Remuzzi, G, and Violante, FS
Abstract: BACKGROUND: In transitioning from the Millennium Development Goal to the Sustainable Development Goal era, it is imperative to comprehensively assess progress toward reducing maternal mortality to identify areas of success, remaining challenges, and frame policy discussions. We aimed to quantify maternal mortality throughout the world by underlying cause and age from 1990 to 2015. METHODS: We estimated maternal mortality at the global, regional, and national levels from 1990 to 2015 for ages 10-54 years by systematically compiling and processing all available data sources from 186 of 195 countries and territories, 11 of which were analysed at the subnational level. We quantified eight underlying causes of maternal death and four timing categories, improving estimation methods since GBD 2013 for adult all-cause mortality, HIV-related maternal mortality, and late maternal death. Secondary analyses then allowed systematic examination of drivers of trends, including the relation between maternal mortality and coverage of specific reproductive health-care services as well as assessment of observed versus expected maternal mortality as a function of Socio-demographic Index (SDI), a summary indicator derived from measures of income per capita, educational attainment, and fertility. FINDINGS: Only ten countries achieved MDG 5, but 122 of 195 countries have already met SDG 3.1. Geographical disparities widened between 1990 and 2015 and, in 2015, 24 countries still had a maternal mortality ratio greater than 400. The proportion of all maternal deaths occurring in the bottom two SDI quintiles, where haemorrhage is the dominant cause of maternal death, increased from roughly 68% in 1990 to more than 80% in 2015. The middle SDI quintile improved the most from 1990 to 2015, but also has the most complicated causal profile. Maternal mortality in the highest SDI quintile is mostly due to other direct maternal disorders, indirect maternal disorders, and abortion, ectopic pregnancy
Published: 2016

9. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

Author: Lozano, Rafael, Fullman, Nancy, Abate, Degu, 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, Abebe, Nebiyu Dereje, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F, Abil, Olifan Zewdie, Aboyans, Victor, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Abu-Rmeileh, Niveen Me, Abyu, Gebre Y, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Acharya, Pawan, Adamu, Abdu A, 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, Afshari, Mahdi, Afshin, Ashkan, Agarwal, Gina, Aghayan, Sargis Aghasi, Agius, Dominic, Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Mehdi, Ahmadieh, Hamid, Ahmed, Muktar Beshir, Ahmed, Sayem, Akalu, Temesgen Yihunie, Akanda, Ali S, Akbari, Mohammad Esmaeil, Akibu, Mohammed, Akinyemi, Rufus Olusola, Akinyemiju, Tomi, Akseer, Nadia, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Tahiya, Albujeer, Ammar, Alebel, Animut, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Alhabib, Samia, Ali, Raghib, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine A, Almasi, Ali, Al-Maskari, Fatma, Al-Mekhlafi, Hesham M, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amenu, Kebede, Amini, Erfan, Ammar, Walid, Anber, Nahla Hamed, Anderson, Jason A, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Ansariadi, Ansariadi, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Anwari, Palwasha, Appiah, Lambert Tetteh, Aremu, Olatunde, Areri, Habtamu Abera, Ärnlöv, Johan, Arora, Monika, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Asghar, Rana Jawad, Assadi, Reza, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R, Atteraya, Madhu Sudhan, Ausloos, Marcel, Avila-Burgos, Leticia, Avokpaho, Euripide F G A, Awasthi, Ashish, Ayala Quintanilla, Beatriz Paulina, Ayele, Henok Tadesse, Ayele, Yohanes, Ayer, Rakesh, Azarpazhooh, Mahmoud Reza, Azzopardi, Peter S, Azzopardi-Muscat, Natasha, Babalola, Tesleem Kayode, Babazadeh, Arefeh, Badali, Hamid, Badawi, Alaa, Balakrishnan, Kalpana, Bali, Ayele Geleto, Banach, Maciej, Banerjee, Amitava, Banoub, Joseph Adel Mattar, Banstola, Amrit, Barac, Aleksandra, Barboza, Miguel A, Barker-Collo, Suzanne Lyn, Bärnighausen, Till Winfried, Barrero, Lope H, Barthelemy, Celine M, Bassat, Quique, Basu, Arindam, Basu, Sanjay, Battista, Robert J, Baune, Bernhard T, Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Bedi, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Meysam, Béjot, Yannick, Bekele, Bayu Begashaw, Belachew, Abate Bekele, Belay, Aregawi Gebreyesus, Belay, Saba Abraham, Belay, Yihalem Abebe, Bell, Michelle L, Bello, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Benzian, Habib, Berhane, Adugnaw, Berhe, Abadi Kidanemariam, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhalla, Ashish, Bhansali, Anil, Bhattarai, Suraj, Bhaumik, Soumyadeep, Bhutta, Zulfiqar A, Biadgo, Belete, Biehl, Molly H, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bitew, Helen, Bizuneh, Hailemichael, Bjertness, Espen, Bobasa, Eshetu Mulisa, Boufous, Soufiane, Bourne, Rupert, Bozorgmehr, Kayvan, Bragazzi, Nicola Luigi, Brainin, Michael, Brant, Luisa C, Brauer, Michael, Brazinova, Alexandra, Breitborde, Nicholas J K, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Bukhman, Gene, Busse, Reinhard, Butt, Zahid 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Subjects: GENDER-DIFFERENCES, SUICIDE, Medicine (all), Burden of Disease Study 2017, SDG, CONSUMPTION, 11 Medical And Health Sciences, GBD, Sustainable Development Goals, PREVENTION, ALCOHOL-USE, CARDIOVASCULAR-DISEASE, SMOKING PREVALENCE, General & Internal Medicine, factors risk, Medicine and Health Sciences, Human medicine, CESSATION, PERSPECTIVE, TRANSITION
Abstract: Background Efforts to establish the 2015 baseline and monitor early implementation of the UN Sustainable Development Goals (SDGs) highlight both great potential for and threats to improving health by 2030. To fully deliver on the SDG aim of "leaving no one behind", it is increasingly important to examine the health-related SDGs beyond national-level estimates. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 (GBD 2017), we measured progress on 41 of 52 health -related SDG indicators and estimated the health-related SDG index for 195 countries and territories for the period 1990-2017, projected indicators to 2030, and analysed global attainment. Methods We measured progress on 41 health-related S DG indicators from 1990 to 2017, an increase of four indicators since GBD 2016 (new indicators were health worker density, sexual violence by non-intimate partners, population census status, and prevalence of physical and sexual violence [reported separately]). We also improved the measurement of several previously reported indicators. We constructed national-level estimates and, for a subset of health-related SDGs, examined indicator-level differences by sex and Socio-demographic Index (SDI) quintile. We also did subnational assessments of performance for selected countries. To construct the health related SDG index, we transformed the value for each indicator on a scale of 0-100, with 0 as the 2.5th percentile and 100 as the 97.5th percentile of 1000 draws calculated from 1990 to 2030, and took the geometric mean of the scaled indicators by target. To generate projections through 2030, we used a forecasting framework that drew estimates from the broader GBD study and used weighted averages of indicator-specific and country-specific annualised rates of change from 1990 to 2017 to inform future estimates. We assessed attainment of indicators with defined targets in two ways: first, using mean values projected for 2030, and then using the probability of attainment in 2030 calculated from 1000 draws. We also did a global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends. Using 2015 global averages of indicators with defined SDG targets, we calculated the global annualised rates of change required from 2015 to 2030 to meet these targets, and then identified in what percentiles the required global annualised rates of change fell in the distribution of country-level rates of change from 1990 to 2015. We took the mean of these global percentile values across indicators and applied the past rate of change at this mean global percentile to all health-related SDG indicators, irrespective of target definition, to estimate the equivalent 2030 global average value and percentage change from 2015 to 2030 for each indicator. Findings The global median health-related SDG index in 2017 was 59.4 (IQR 35.4-67.3), ranging from a low of 11.6 (95% uncertainty interval 9.6-14.0) to a high of 84.9 (83.1-86.7). SDG index values in countries assessed at the subnational level varied substantially particularly in China and India, although scores in Japan and the UK were more homogeneous. Indicators also varied by SDI quintile and sex, with males having worse outcomes than females for non-communicable disease (NCD) mortality, alcohol use, and smoking, among others. Most countries were projected to have a higher health-related SDG index in 2030 than in 2017, while country-level probabilities of attainment by 2030 varied widely by indicator. Under-5 mortality, neonatal mortality, maternal mortality ratio, and malaria indicators had the most countries with at least 95% probability of target attainment. Other indicators, including NCD mortality and suicide mortality, had no countries projected to meet corresponding SDG targets on the basis of projected mean values for 2030 but showed some probability of attaimnent by 2030. For some indicators, including child malnutrition, several infectious diseases, and most violence measures, the annualised rates of change required to meet SDG targets far exceeded the pace of progress achieved by any country in the recent past. We found that applying the mean global annualised rate of change to indicators without defined targets would equate to about 19% and 22% reductions in global smoking and alcohol consumption, respectively; a 47% decline in adolescent birth rates; and a more than 85% increase in health worker density per 1000 population by 2030. Interpretation The GBD study offers a unique, robust platform for monitoring the health -related SDGs across demographic and geographic dimensions. Our findings underscore the importance of increased collection and analysis of disaggregated data and highlight where more deliberate design or targeting of interventions could accelerate progress in attaining the SDGs. Current projections show that many health -related SDG indicators, NCDs, NCD-related risks, and violence -related indicators will require a concerted shift away from what might have driven past gains curative interventions in the case of NCDs towards multisectoral, prevention -oriented policy action and investments to achieve SDG aims. Notably, several targets, if they are to be met by 2030, demand a pace of progress that no country has achieved in the recent past. The future is fundamentally uncertain, and no model can fully predict what breakthroughs or events might alter the course of the S DGs. What is clear is that our actions or inaction today will ultimately dictate how close the world, collectively, can get to leaving no one behind by 2030. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.
Published: 2018

10. 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: Roth, Gregory A., Collaborotors, G. B. D.Causes Death, Abate, Degu, Abate, Kalkidan Hassen, Abay, Solomon M., Abbafati, Cristiana, Abbasi, Nooshin, Abbastabar, Hedayat, Abd-Allah, Load, Abdela, Jemal, Abdelalim, Ahmed, Abdollahpour, Ibrahim, Abdulkader, Rizwan Suliankatchi, Abebe, Haftom Temesgen, Abebe, Molla, Abebe, Zegeye, Abejie, Ayenew Negesse, Abera, Semaw F., Abil, Olifan Zewdie, Abraha, Haftom Niguse, Abrham, Aklilu Roba, Abu-Raddad, Laith Jamal, Accrombessi, Manfred Mario Kokou, Acharya, Dilaram, Adamu, Abdu A., Adebayo, Oladimeji, Adedoyin, Rufus Adesoji, Adekanmbi, Victor, Adookunboh, Olatunii, Adhena, Beyene Meressa, Adib, Mina G., Admasie, Aniha, Afshin, Ashkan, Agarwal, Gina, Agesa, Karelia M., Agrawal, Anurag, Agrawal, Sutapa, Ahmadi, Alireza, Ahmadi, Melidi, Ahmed, Muktar Beshir, Ahmed, Sayent, Aichour, Amani Nidhal, Aichour, Ibtihel, Aichour, Miloud Taki Fddine, Akbari, Mohammad Esmaeil, Akinyeniti, Rufus Olusola, Akseer, Nadia, Al-Aly, Ziyad, Al-Eyadhy, Ayman, Al-Raddadi, Rajaa M., Alandab, Fares, Alam, Khurshid, Alam, Tahiya, Alebel, Animut, Alene, Kefyalew Addis, Alijanzadeh, Mehran, Alizadeh-Navaei, Reza, Aljunid, Syed Mohamed, Alkerwi, Ala'a, Alla, Francois, Allebeck, Peter, Alonso, Jordi, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T., Aminde, Leopold N., Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampern, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Anjomshoa, Mina, Ansari, Hossein, Aniha, Mustafa Geleto, Antonio, Carl Abelardo T., Anwari, Palwasha, Aremu, Olatunde, Arnlov, Johan, Arora, Amit, Arora, Monika, Artaman, Al, Aryal, Krishna K., Asayesh, Hamid, Asfaw, Ephremi Tsegay, Ataro, Zerihun, Atique, Suleman, Atre, Sachin R., Ausloos, Marcel, Avokpaho, Euripide F. G. A., Awasthi, Ashish, Quintattilla, Beatriz Paulina Ayala, Ayele, Yohanes, Ayer, Rakesh, Azzopardi, Peter S., Babazadeh, Arefeh, Bacha, Umar, Badali, Hamid, Badawi, Alaa, Bali, Ayele Geleto, Ballesteros, Katherine E., Banach, Maciej, Banerjee, Kajori, Bannick, Marlena S., Banoub, Joseph Adel Mattar, Barboza, Miguel A., Barker-Collo, Suzanne Lyu, Barnighausen, Till Winfried, Barquera, Simon, Barrero, Lope, Bassat, Quique, Base, Sanjay, Baune, Bernhard T., Baynes, Habtamu Wondifraw, Bazargan-Hejazi, Shahrzad, Beth, Neeraj, Beghi, Ettore, Behzadifar, Masoud, Behzadifar, Mcysam, Bejot, Yannick, Bekele, Bayu Begashaw, Belacliew, Abate Bekele, Belay, Ezra, Belay, Yihalem Abebe, Bell, Michelle L., Bello, Aminu K., Bennett, Derrick A., Bensenor, Isabela M., Berman, Adam F., Bernabe, Eduardo, Bernstein, Robert S., Bertolacci, Gregory J., Beuran, Mircea, Beyranvand, Tina, Bhalla, Ashish, Bhattarai, Suraj, Bhaumik, Sounayadeeep, Bhutta, Zulfiqar A., Biadgo, Belete, Biehl, Molly H., Bijani, Ali, Bikbov, Boris, Bilano, Ver, Bililign, Nigus, Bin Sayeed, Muhammad Shandaat, Bisanzio, Donal, Biswas, Tuhin, Blacker, Brigitte F., Basara, Berrak Bora, Borschmann, Rohan, Bosetti, Cristina, Bozorgmehr, Kayvan, Brady, Oliver J., Brant, Luisa C., Brayne, Carol, Brazinova, Alexandra, Breitborde, Nicholas J. K., Brenner, Hermann, Briant, Paul Svitil, Britton, Gabrielle, Brugha, Traolach, Busse, Reinhard, Butt, Zahid A., Callender, Charlton S. K. H., Campos-Nonato, Ismael R., Rincon, Julio Cesar Canapuzano, Cano, Jorge, Car, Mate, Cardenas, Rosario, Carreras, Giulia, Carrero, Juan J., Carter, Austin, Carvalho, Felix, Castaneda-Orjuela, Carlos A., Rivas, Jacqueline Castillo, Castle, Chris D., Castro, Clara, Castro, Franz, Catala-Lopez, Ferran, Cerin, Ester, Chaiah, Yazan, Chang, Jung -Chen, Chanson, Fiona J., Chaturvedi, Pankaj, Chiang, Peggy Pei-Chia, Chimed-Ochir, Odgerel, Chisumpa, Vesper Hichilombwe, Chitheet, Abdulaal, Chowdhury, Rajiv, Christensen, Hanne, Christopher, Devasahayam J., Chiang, Sheng-Chia, Cicuttini, Flavia M., Ciobanu, Liliana G., Cirillo, Massimo, Cohen, Aaron J., Cooper, Leslie Trumbull, Cortesi, Paolo Angelo, Cortinovis, Monica, Cousin, Ewerton, Cowie, Benjamin C., Criqui, Michael H., Cromwell, Elizabeth A., Crowe, Christopher Stephen, Crump, John A., Cunningham, Matthew, Daba, Alemneh Kabeta, Dadi, Abel Fekadu, Dandona, Lalit, Dandona, Rakhi, Dang, Anh Kim, Dargan, Paul I., Daryani, Ahmad, Das, Siddharth K., Das Gupta, Rajat, Das Neves, Jose, Dasa, Tamirat Tesfaye, Dash, Aditya Prasad, Davis, Adrian C., Weaver, Nicole Davis, Davitoiu, Dragos Virgil, Davletov, Kairat, De La Hoz, Fernando Pio, De Neve, Jan-Walter, Degefa, Meaza Girma, Degenhardt, Louisa, Degfie, Tizta T., Deiparine, Selina, Demoz, Gebre Teklemariam, Demtsu, Baleen Betsu, Denova-Gutierrez, Edgar, Deribe, Kebede, Dervenis, Nikolaos, Jarlais, Don C. Des, Dessie, Getenet Ayalew, Dey, Subhojit, Dhannaratne, Samath D., Dicker, Daniel, Dinberu, Mesfin Tadese, Ding, Eric L., Dirac, M. Ashworth, Djalalinia, Shirin, Dokova, Klara, Ter Doku, David, Donnelly, Christl A., Dorsey, E. Ray, Doshi, Pratik P., Douwes-Schultz, Dirk, Doyle, Kerrie E., Driscoll, Tim R., Dubey, Manisha, Dubljanin, Eleonora, Duken, Eyasu Ejeta, Duncan, Bruce B., Duraes, Andre R., Ebrahimi, Hedyeh, Ebrahimpour, Soheil, Edessa, Dumessa, Edvardsson, David, Eggen, Anne Elise, El Bcheraoui, Charbel, Zaki, Maysaa El Sayed, El-Khatib, Ziad, Elkout, Hajer, Eltinsel, Christian Lycke, Endres, Matthias, Endries, Aman Yesuf, Er, Benjamin, Erskine, Holly E., Eshrati, Babak, Eskandarieh, Sharareh, Esmaeili, Reza, Esteghamati, Alireza, Fakhar, Mahdi, Fakhim, Hamed, Faramarzi, Mahbobeh, Fareed, Mohammad, Farhadi, Farzaneh, Faninha, Carla Sofia E. Sa, Faro, Andre, Farvid, Maryam S., Farzadfar, Farshad, Farzaei, Mohammad Hosein, Feign, Valery L., Feigl, Andrea B., Fentahun, Netsanet, Eereshtehnejad, Seyed-Mohammad, Fernandes, Eduarda, Fernandes, Joao C., Ferrari, Alice J., Feyissa, Garumma Tolu, Filip, Irina, Finegold, Samuel, Fischer, Florian, Eitzmaurice, Christina, Foigt, Nataliya A., Foreman, Kyle J., Fornari, Carla, Frank, Tahvi D., Fukumoto, Takeshi, Fuller, John E., Fullman, Nancy, Furst, Thomas, Furtado, Joao M., Futran, Neal D., Gallus, Silvano, Garcia-Basteiro, Alberto L., Garcia-Gordillo, Miguel A., Gardner, William M., Gebre, Abadi Kahsu, Gebrehiwol, Tsegaye Tewelde, Gebremedhin, Amanuel Tesfay, Gebremichael, Bereket, Gebremichael, Teklu Gebrehiwo, Gelano, Tilayie Feto, Geleijinse, Johanna M., Genova-Maleras, Ricard, Geramo, Yilma Chisha Dea, Gething, Peter W., Gezae, Kebede Embaye, Ghadami, Mohammad Rasoul, Ghadimi, Reza, Falavarjani, Khalil Ghasemi, Ghasemi-Kasman, Maryam, Ghimire, Mamata, Gibney, Katherine B., Gill, Paramjit Singh, Gill, Tiffany K., Gillum, Richard F., Ginawi, Ibrahim Abdelmageed, Giroud, Maurice, Giussani, Giorgia, Goenka, Shifalika, Goldberg, Ellen M., Goli, Srinivas, Gomez-Dantes, Hector, Gona, Philimon N., Gopalani, Sameer Vali, Gorman, Taren M., Goto, Atsushi, Goulart, Alessandra C., Gnedovskaya, Elena V., Grada, Aymara, Grosso, Giuseppe, Gugnani, Hanish Chander, Guimaraes, Andre Luiz Sena, Gun, Nailing, Gupta, Prakash C., Gupta, Rahid, Gupta, Rajenv, Gupta, Tanush, Gutierrez, Reyna Alma, Gyawali, Bishal, Haagsma, Juanita A., Hafezi-Nejad, Nima, Hagos, Tekleberhan B., Hailegiyorgis, Tewodros Tesfa, Hailu, Gessessew Bugssa, Haj-Mirzaian, Arvin, Haj-Mirzaian, Arya, Hamadeh, Randall R., Hamidi, Sinner, Handal, Meads J., Hankey, Graeme J., Harb, Hilda L., Harikrishnan, Sivadasanpillai, Haro, Josep Maria, Hasan, Mehedi, Hassankhani, Hadi, Hassen, Hamid, Havmoeller, Rasmus, Hay, Roderick J., Hay, Simon I., He, Yihua, Hedayatizadeh-Omran, Akbar, Hegazy, Mohamed I., Heibati, Behzad, Heidari, Mohsen, Hendrie, Delia, Henok, Andualem, Henry, Nathaniel J., Herteliu, Claudiu, Heydarpour, Fatemeh, Heydarpour, Pouria, Heydarpour, Sousan, Hibstu, Desalegn Tsegaw, Hoek, Hans W., Hole, Michael K., Red, Enayatollah Homaie, Hoogar, Praveen, Hosgood, H. Dean, Hosseini, Seyed Mostafa, Hosseinzadeh, Mehdi, Hostiuc, Mihaela, Hostiuc, Sorin, Hotez, Peter J., Hoy, Damian C., Hsiao, Thomas, Hu, Guoqing, Huang, John J., Husseini, Abdullatif, Hussen, Mohammedaman Mama, Hutfless, Susan, Idrisov, Bulat, Ilesanmi, Olayinka Stephen, Iqbal, Usman, Irvani, Seyed Sina Naghibi, Irvine, Caleb Mackay Salpeter, Islam, Nazrul, Islam, Sheikh Mohammed Shariful, Islami, Farhad, Jacobsen, Kathryn H., Jahangiry, Leila, Jahanmehr, Nader, Jain, Sudhir Kumar, Jakovlievic, Mihajlo, Jalu, Moti Tolera, James, Spencer L., Javanbakht, Mehdi, Jayatilleke, Achala Upendra, Jeemon, Panniyammakal, Jenkins, Kathy J., Jha, Ravi Prakash, Jha, Vivekanand, Johnson, Catherine O., Johnson, Sarah C., Jonas, Jost B., Joshi, Ankur, Jozwiak, Jacek Jerzy, Jungari, Suresh Banayya, Jurisson, Mikk, Kabir, Zubair, Kadel, Rajendra, Kahsay, Amaha, Kalani, Rizwan, Karami, Manoochehr, Matin, Behzad Karami, Karch, Andre, Karema, Corine, Karimi-Sari, Hamidreza, Kasaeian, Amir, Kassa, Dessalegn H., Kassa, Getachew Mullu, Kassa, Tesfaye Dessale, Kassebaum, Nicholas J., Katikireddi, Srinivasa Vittal, Kaul, Anil, Kazemi, Zhila, Karyani, Ali Kazemi, Kazi, Dhruv Satish, Kefale, Adane Teshome, Keiyoro, Peter Njenga, Kemp, Grant Rodgers, Kengne, Andre Pascal, Keren, Andre, Kesavachandran, Chandrasekharan Nair, Khader, Yousef Saleh, Khafaei, Behzad, Khafaie, Morteza Abdullatif, Khajavi, Alireza, Khalid, Nauman, Khalil, Ibrahim A., Khan, Ejaz Ahmad, Khan, Muhammad Shahzeb, Khan, Muhammad Ali, Khang, Young-Ho, Khater, Mona M., Khoja, Abdullah T., Khosravi, Ardeshir, Khosravi, Mohammad Hossein, Khubchandani, Jagdish, Kiadaliri, Aliasghar A., Kibret, Getiye D., Kidanemariam, Zelalem Teklemariam, Kiirithio, Daniel N., Kim, Daniel, Kim, Young-Eun, Kim, Yun Jin, Kimokoti, Ruth W., Kinfu, Yohannes, Kisa, Adnan, Kissimova-Skarbek, Katarzyna, Kivimaki, Mika, Knudsen, Ann Kristin Skrindo, Kocarnik, Jonathan M., Kochhar, Sonali, Kokubo, Yoshihiro, Kolola, Tufa, Kopec, Jacek A., Koul, Parvaiz A., Koyanagi, Ai, Kravchenko, Michael A., Krishan, Kewal, Defo, Barthelemy Kuate, Bicer, Burcu Kinuk, Kumar, G. Anil, Kumar, Manasi, Kumar, Pushpendra, Kutz, Michael J., Kuzin, Igor, Kyu, Hmwe Hmwe, Lad, Deepesh P., Lad, Sheetal D., Lafranconi, Alessandra, Lal, Dharmesh Kumar, Lalloo, Ratilal, Lallukka, Tea, Lam, Jennifer O., Lami, Faris Hasan, Van Lansingh, C., Lansky, Sonia, Larson, Heidi J., Latifi, Amman, Lau, Kathryn Mei-Ming, Lazarus, Jeffrey V., Lebedev, Georgy, Lee, Paul H., Leigh, James, Leili, Mostafa, Leshargie, Cheru Tesema, Li, Shanshan, Li, Yichong, Liang, Juan, Lim, Lee-Ling, Lim, Stephen S., Limenih, Miteku Andualem, Linn, Shai, Liu, Shiwei, Liu, Yang, Lodha, Rakesh, Lansdale, Chris, Lopez, Alan D., Lorkowski, Stefan, Lotufo, Paulo A., Lozano, Rafael, Lunevicius, Raimundas, Ma, Stefan, Macarayan, Erlyn Rachelle King, Mackay, Mark T., MacLachlan, Jennifer H., Maddison, Emilie R., Nadotto, Fabiana, Abd El Razek, Hassan Magdy, Abd El Razek, Muhammed Magdy, Maghavani, Dhaval P., Majdan, Marek, Majdzadeh, Reza, Majeed, Azeem, Malekzadeh, Reza, Malta, Deborah Carvalho, Manda, Ana-Laura, Mandarano-Filho, Luiz Garcia, Manguerra, Helena, Mansournia, Mohammad Ali, Mapoma, Chabila Christopher, Marami, Dadi, Maravilla, Joemer C., Marcenes, Wagner, Marczak, Laurie, Marks, Ashley, Marks, Guy B., Martinez, Gabriel, Martins-Melo, Francisco Rogerlandio, Martopullo, Ira, Marz, Winfried, Marron, Melvin B., Masci, Joseph R., Lylassenburg, Benjamin Ballard, Mathur, Manu Raj, Mathur, Prashant, Matzopoulos, Richard, Maulik, Pallab K., Mazidi, Mohsen, McAlinden, Cohn, McGrath, John J., McKee, Martin, McMahon, Brian J., Mehata, Suiiesh, Mehndiratta, Man Mohan, Mehrotra, Ravi, Mehta, Kala M., Mehta, Varshil, Mekonnen, Tefera C., Melese, Addisu, Melku, Mulugeta, Memiah, Peter T. N., Memish, Ziad A., Mendoza, Walter, Mengistu, Desalegn Tadese, Mengistu, Getnet, Mensah, George A., Mereta, Seid Tiku, Meretoja, Atte, Meretoja, Tuomo J., Meshovic, Tbmislav, Mezgebe, Haftay Berhane, Miazgowski, Bartosz, Miazgowski, Tomasz, Millear, Anoushka I., Miller, Ted R., Katherine, Molly, Petrie, Miller, Mini, G. K., Mirabi, Parvaneh, Mirarefin, Mojde, Mirica, Andreea, Mirrakhimov, Erkin M., Misganaw, Awoke Temesgen, Mitiku, Habtamu, Moazen, Babak, Mohammad, Karzan Abdulmuhsin, Mohammad, Moslem, Mohammadifard, Noushin, Mohammed, A. Mohammed, Mohammed, Shafiu, Mohan, Viswanathan, Mokdad, Ali H., Molokhia, Mariam, Monasta, Lorenzo, Moradi, Ghobad, Moradi-Lakeh, Maziar, Moradinazar, Mehdi, Moraga, Paula, Morawska, Lidia, Velasquez, Ilais Moreno, Morgado-Da-Costa, Joana, Morrison, Shane Douglas, Moschos, Marilita M., Mouodi, Simin, Mousavi, Seyyed Meysam, Muchie, Kindie Eentahun, Mueller, Ulrich Otto, Mukhopadhyay, Satinath, Muller, Kate, Mumford, John Everett, Musa, Jonah, Musa, Kamand Imran, Mustafa, Ghulam, Muthupandian, Saravanan, Nachega, Jean B., Nagel, Gabriele, Naheed, Aliya, Nahvijou, Azin, Naik, Gunidatta, Nair, Sanjeev, Najafi, Farid, Naldi, Luigi, Nam, Hae Sung, Nangia, Vinay, Nansseu, Jobert Richie, Nascirnento, Bruno Ramos, Natarajan, Gopalakrishnan, Nearnati, Nahid, Negoi, Ionut, Negoi, Ruxcandra Irina, Nettpane, Subas, Newton, Charles R. J., Ngalesoni, Frida N., Ngunjiri, Josephine W., Anh Quynh Nguyen, Nguyen, Grant, Ha Thu Nguyen, Luong Thanh Nguyen, Long Hoang Nguyen, Nguyen, Minh, Trang Huyen Nguyen, Nichols, Emma, Ningnun, Dina Nur Anggraini, Nirayo, Yirga Legesse, Nixon, Molly R., Nolutshungu, Nomonde, Nomura, Shhhei, Norhelin, Ole F., Noroozi, Mehdi, Norrving, Bo, Noubiap, Jean Jacques, Nouri, Hamid Reza, Shiadeh, Malihe Nourollahpour, Nowroozi, Mohammad Reza, Nyasulu, Peter S., Odell, Christopher M., Ofori-Asenso, Richard, Ogbo, Felix Akpojene, Oh, In-Hwan, Oladimeji, Olanrewaju, Olagunju, Andrew T., Olivares, Pedro R., Olsen, Helen Elizabeth, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Ong, Kanyin L., Ong, Sok King Sk, Oren, Eyal, Orpana, Heather M., Ortiz, Alberto, Ortiz, Justin R., Otstavnov, Stanislav S., Overland, Simon, Owolabi, Mayowa Ojo, Ozdemir, Raziye, Mahesh, P. A., Pacella, Rosana, Pakhale, Smita, Pakhare, Abhijit P., Pakpour, Amir H., Pana, Adrian, Panda-Jonas, Songhomitra, Pandian, Jeyaraj Durai, Parisi, Andrea, Park, Eun-Kee, Parry, Charles D. H., Parsian, Hadi, Patel, Shanti, Pati, Sanghamitra, Patton, George C., Paturi, Vishnupriya Rao, Paulson, Katherine R., Pereira, Alexandre, Pereira, David M., Perico, Norberto, Pesudovs, Konrad, Petzold, Max, Phillips, Michael R., Piel, Frederic B., Pigott, David M., Pillay, Julian David, Pirsaheb, Meghdad, Pishgar, Farhad, Polinder, Suzanne, Postma, Maarten J., Pourshams, Akram, Poustchi, Hossein, Pujar, Ashwini, Prakash, Swayam, Prasad, Narayan, Purcell, Caroline A., Qorbani, Mostafa, Quintana, Hedley, Quistberg, D. Alex, Rade, Kirankumar Waman, Radfah, Amir, Rafay, Anwar, Rafiei, Alireza, Rahim, Fakher, Rahimi, Kazem, Rahimi-Movaghar, Afarin, Rahman, Mahfuzar, Rahman, Mohammad Hifz Ur, Rahman, Muhammad Aziz, Rai, Rajesh Kumar, Rajsic, Sasa, Ram, Usha, Ranabhat, Chhabi Lal, Ranjan, Prabhat, Rao, Puja C., Rawaf, David Laith, Rawaf, Salman, Razo-Garcia, Christian, Reddy, K. Srinath, Reiner, Robert C., Reitsma, Marissa B., Remuzzi, Giuseppe, Renzaho, Andre M. N., Resnikoff, Serge, Rezaei, Satar, Rezaeian, Shahab, Rezai, Mohammad Sadegh, Riahi, Seyed Mohammad, Ribeiro, Antonio Luiz P., Rios-Blancas, Maria Jesus, Roba, Kedir Teji, Roberts, Nicholas L. S., Robinson, Stephen R., Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostami, Ali, Rothenbacher, Dietrich, Roy, Ambuj, Rubagotti, Enrico, Sachdev, Perminder S., Saddik, Basema, Sadeghi, Ehsan, Safari, Hosein, Safdarian, Mahdi, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Salam, Nasir, Salama, Joseph S., Salamati, Payman, De Saldanha, Raphael Freitas, Saleem, Zikria, Salimi, Yahya, Salvi, Sundeep Santosh, Salz, Inbal, Sambala, Evanson Zondani, Samy, Abdatiah M., Sanabria, Juan, Sanchez-Nino, Maria Dolores, Santomauro, Damian Francesco, Santos, Itamar S., Santos, Joao Vasco, Milicevic, Milena M. Santric, Jose, Bruno Piassi Sao, Sarker, Abdur Razzaque, Sarmiento-Suarez, Rodrigo, Sarrafzadegan, Nizal, Sartorius, Benn, Sarvi, Shahabeddin, Sathian, Brijesh, Satpathy, Maheswar, Sawant, Arundhati R., Sawhney, Monika, Saxena, Sonia, Sayyah, Mehdi, Schaeffher, Elke, Schmidt, Maria Ines, Schneider, Ione J. C., Schottker, Ben, Schutte, Aletta Elisabeth, Schwebel, David C., Schwendicke, Falk, Scott, James G., Sekerija, Mario, Sepanlou, Sadaf G., Servan-Mori, Edson, Seyedmousavi, Seyedmojtaba, Shabaninejad, Hosein, Shackelford, Katya Anne, Shafieesabet, Azadeh, Shahbazi, Mehdi, Shaheen, Amira A., Shaikh, Masood Ali, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Sharafi, Kiomars, Sharif, Mehdi, Sharif-Alhoseini, Mandi, Sharma, Rajesh, She, Jun, Sheikh, Aziz, Shi, Peilin, Shiferaw, Mekonnen Sisav, Shigematsu, Mika, Shiri, Rahman, Shirkoohi, Reza, Shiue, Ivy, Shokraneh, Farhad, Shrine, Mark G., Si, Si, Siabani, Soraya, Siddiqi, Tariq J., Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silberberg, Donald H., Silva, Diego Augusto Santos, Silva, Joao Pedro, Da Silva, Natacha Torres, Silveira, Dayane Bride Alves, Singh, Jasvinder A., Singh, Narinder Pal, Singh, Prashant Kumar, Singh, Virendra, Sinha, Dhirendra Narain, Sliwa, Karen, Smith, Mari, Sobaih, Badr Hasan, Sobhani, Soheila, Solangwi, Eugene, Soneji, Samir S., Soofi, Moslem, Sorensen, Reed J. D., Soriano, Joan B., Soyiri, Ireneous N., Sposato, Luciano A., Sreeramareddy, Chandrashekhar F., Srinivasan, Vinay, Stanaway, Jeffrey D., Starodubov, Vladimir I., Stathopoulou, Vasiliki, Stein, Dan J., Steiner, Caitlyn, Stewart, Leo G., Stokes, Mark A., Subart, Michelle L., Sudaryanto, Agus, Sufiyan, Mu'awiyyah Babale, Sur, Patrick John, Sutradhar, Ipsita, Sykes, Bryan L., Sylaja, P. N., Sylte, Dillon O., Szoeke, Cassandra E. I., Tabares-Seisdedos, Rafael, Tabuchi, Takahiro, Tadakamadla, Santosh Kumar, Takahashi, Ken, Tandon, Nikhil, Tassew, Segen Gebremeskel, Taveira, Nuno, Tehrani-Banihashemi, Arash, Tekalign, Tigist Gashaw, Tekle, Merhawi Gebremedhin, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tesserna, Belay, Tessema, Gizachew Assefa, Thankappan, Kavumpurathu Raman, Thirinavukkarasu, Sathish, Thomas, Nihal, Thrift, Amanda G., Thurston, George D., Tilahun, Binyam, To, Quyen G., Tobe-Gai, Ruoyan, Tonellli, Marcello, Topor-Madry, Roman, Torre, Anna E., Tortajada-Cirbes, Miguel, Touvier, Mathilde, Tovani-Palone, Marcos Roberto, Bach Xuan Tran, Khah Bao Tran, Tripathi, Suryakant, Troeger, Christopher E., Truelsen, Thomas Clement, Nu Thi Truong, Tsadik, Afewerki Gebremeskel, Tsoi, Derrick, Car, Lorainne Tudor, Tuzcu, E. Murat, Tyrovolas, Stefanos, Ukwaja, Kingsley N., Whiff, Irfan, Undurraga, Eduardo A., Updike, Rachel L., Usman, Muhammad Shariq, Uthman, Olalekan A., Uzun, Selen Begum, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R., Varavikova, Elena, Vasankari, Tommi Juhani, Venketasubramanian, Narayanaswamy, Villafaina, Santos, Violante, Francesco S., Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Email, Vos, Theo, Wagner, Gregory R., Wagnew, Fasil Shiferaw, Waheed, Yasir, Wallin, Mitchell Taylor, Watson, Judd L., Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G., Weldegebreal, Eitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Werkneh, Adhena Ayaliew, West, T. Eoin, Westerman, Ronny, Whiteford, Harvey A., Widecka, Justyna, Wilner, Lauren B., Wilson, Shadrach, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D. A., Wu, Shouling, Wu, Yun-Chun, Wyper, Grant M. A., Xavier, Denis, Xu, Gelin, Yadgir, Simon, Yadollahpour, Ali, Jabbari, Seyed Hossein Yahyazadeh, Yakob, Bereket, Yan, Lijing L., Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Yentur, Gokalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M., Yip, Paul, Yirsaw, Biruck Desalegn, Yisma, Engida, Yonemoto, Naohiro, Yonga, Gerald, Yoon, Seok-Jun, Yotebieng, Marcel, Younis, Mustafa Z., Yousefifard, Mahmoud, Yu, Chuanhua, Zadnik, Vesna, Zaidi, Zoubida, Bin Zaman, Sojib, Zamani, Mohammad, Zare, Zohreh, Zeleke, Ayalew Jejaw, Zenebe, Zerihun Menlkalew, Zhang, Anthony Lin, Zhang, Kai, Zhou, Maigeng, Zodpey, Sanjay, Zuhlke, Liesl Joanna, Naghavi, Ntishsen, Murray, Christopher J. 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Reiner, Rc, Reitsma, Mb, Renzaho, Amn, Riahi, Sm, Ribeiro, Alp, Rios-Blancas, Mj, Roba, Kt, Roberts, Nl, Robinson, Sr, Sahraian, Ma, Saldanha, Rf, Sambala, Ez, Samy, Am, Sanchez-Niño, Md, Santomauro, Df, Santos, Jv, Milicevic, Mm, Sao Jose, Bp, Sarker, Ar, Sarmiento-Suárez, R, Sawant, Ar, Schmidt, Mi, Schneider, Ijc, Schöttker, B, Schutte, Ae, Schwebel, Dc, Scott, Jg, Sepanlou, Sg, Serván-Mori, E, Shackelford, Ka, Shaheen, Aa, Shaikh, Ma, Shrime, Mg, Siddiqi, Tj, Sigfusdottir, Id, Silberberg, Dh, Silva, Da, Silva, Jp, Silva, Ntd, Silveira, Dga, Singh, Ja, Singh, Np, Singh, Pk, Sinha, Dn, Sobaih, Bh, Sorensen, Rjd, Soriano, Jb, Soyiri, In, Sposato, La, Sreeramareddy, Ct, Stanaway, Jd, Starodubov, Vi, Stein, Dj, Stewart, Lg, Stokes, Ma, Subart, Ml, Sufiyan, Mb, Sur, Pj, Sykes, Bl, Sylaja, Pn, Sylte, Do, Szoeke, Cei, Tabarés-Seisdedos, R, Tadakamadla, Sk, Tassew, Sg, Tekalign, Tg, Tekle, Mg, Temsah, Mh, Teshale, My, Tessema, Ga, Thankappan, Kr, Thrift, Ag, Thurston, Gd, To, Qg, Torre, Ae, 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Subjects: 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.
Published: 2018

11. Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

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Sayem, 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, Almasi, Ali, Alonso, Jordi, Al-Raddadi, Rajaa M, Alsharif, Ubai, Altirkawi, Khalid, Alvis-Guzman, Nelson, Amare, Azmeraw T, Ammar, Walid, Anber, Nahla Hamed, Andrei, Catalina Liliana, Androudi, Sofia, Animut, Megbaru Debalkie, Ansari, Hossein, Ansha, Mustafa Geleto, Antonio, Carl Abelardo T, Appiah, Seth Christopher Yaw, Aremu, Olatunde, Areri, Habtamu Abera, Arian, Nicholas, Ärnlöv, Johan, Artaman, Al, Aryal, Krishna K, Asayesh, Hamid, Asfaw, Ephrem Tsegay, Asgedom, Solomon Weldegebreal, Assadi, Reza, Atey, Tesfay Mehari Mehari, Atique, Suleman, 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Subjects: Adult, Male, Population Density, GBD, population, fertility, Adolescent, Medicine (all), Infant, Newborn, Infant, 11 Medical And Health Sciences, Middle Aged, Global Health, Global Burden of Disease, Young Adult, Child, Preschool, General & Internal Medicine, Female, Human medicine, Mortality, Child, Population Growth, Birth Rate, Aged, Human, Maternal Age
Abstract: Background Population estimates underpin demographic and epidemiological research and are used to track progress on numerous international indicators of health and development. To date, internationally available estimates of population and fertility, although useful, have not been produced with transparent and replicable methods and do not use standardised estimates of mortality. We present single-calendar year and single-year of age estimates of fertility and population by sex with standardised and replicable methods. Methods We estimated population in 195 locations by single year of age and single calendar year from 1950 to 2017 with standardised and replicable methods. We based the estimates on the demographic balancing equation, with inputs of fertility, mortality, population, and migration data. Fertility data came from 7817 location-years of vital registration data, 429 surveys reporting complete birth histories, and 977 surveys and censuses reporting summary birth histories. We estimated age-specific fertility rates (ASFRs; the annual number of livebirths to women of a specified age group per 1000 women in that age group) by use of spatiotemporal Gaussian process regression and used the ASFRs to estimate total fertility rates (TFRs; the average number of children a woman would bear if she survived through the end of the reproductive age span [age 10-54 years] and experienced at each age a particular set of ASFRs observed in the year of interest). Because of sparse data, fertility at ages 10-14 years and 50-54 years was estimated from data on fertility in women aged 15-19 years and 45-49 years, through use of linear regression. Age-specific mortality data came from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017 estimates. Data on population came from 1257 censuses and 761 population registry location-years and were adjusted for underenumeration and age misreporting with standard demographic methods. Migration was estimated with the GBD Bayesian demographic balancing model, after incorporating information about refugee migration into the model prior. Final population estimates used the cohort-cotnponent method of population projection, with inputs of fertility, mortality, and migration data. Population uncertainty was estimated by use of out-of-sample predictive validity testing. With these data, we estimated the trends in population by age and sex and in fertility by age between 1950 and 2017 in 195 countries and territories. Findings From 1950 to 2017, TFRs decreased by 49.4% (95% uncertainty interval [UI] 46.4-52.0). The TFR decreased from 4.7 livebirths (4.5-4.9) to 2.4 livebirths (2.2-2.5), and the ASFR of mothers aged 10-19 years decreased from 37 livebirths (34-40) to 22 livebirths (19-24) per 1000 women. Despite reductions in the TFR, the global population has been increasing by an average of 83.8 million people per year since 1985. The global population increased by 197-2% (193.3-200.8) since 1950, from 2.6 billion (2.5-2.6) to 7.6 billion (7.4-7.9) people in 2017; much of this increase was in the proportion of the global population in south Asia and sub-Saharan Africa. The global annual rate of population growth increased between 1950 and 1964, when it peaked at 2.0%; this rate then remained nearly constant until 1970 and then decreased to 1.1% in 2017. Population growth rates in the southeast Asia, east Asia, and Oceania GBD super-region decreased from 2.5% in 1963 to O7% in 2017, whereas in sub-Saharan Africa, population growth rates were almost at the highest reported levels ever in 2017, when they were at 2.7%. The global average age increased from 26.6 years in 1950 to 32.1 years in 2017, and the proportion of the population that is of working age (age 15-64 years) increased from 59.9% to 65.3%. At the national level, the TFR decreased in all countries and territories between 1950 and 2017; in 2017, TFRs ranged from a low of 1.0 livebirths (95% UI 0. 9-1.2) in Cyprus to a high of 7.1 livebirths (6.8-7.4) in Niger. The TFR under age 25 years (TFU25; number of livebirths expected by age 25 years for a hypothetical woman who survived the age group and was exposed to current ASFRs) in 2017 ranged from 0.08 livebirths (0.07-0.09) in South Korea to 2.4 livebirths (2.2-2.6) in Niger, and the TFR over age 30 years (I F030; number of livebirths expected for a hypothetical woman ageing from 30 to 54 years who survived the age group and was exposed to current ASFRs) ranged from a low of 0.3 livebirths (0.3-0-4) in Puerto Rico to a high of 3.1 livebirths (3.0-3.2) in Niger. TF030 was higher than TFU25 in 145 countries and territories in 2017.33 countries had a negative population growth rate from 2010 to 2017, most of which were located in central, eastern, and western Europe, whereas population growth rates of more than 2.0% were seen in 33 of 46 countries in sub-Saharan Africa. In 2017, less than 65% of the national population was of working age in 12 of 34 high-income countries, and less than 50% of the national population was of working age in Mali, Chad, and Niger. Interpretation Population trends create demographic dividends and headwinds (ie, economic benefits and detriments) that affect national economies and determine national planning needs. Although TFRs are decreasing, the global population continues to grow as mortality declines, with diverse patterns at the national level and across age groups. To our knowledge, this is the first study to provide transparent and replicable estimates of population and fertility, which can be used to inform decision making and to monitor progress. Copyright (C) 2018 The Author(s). Published by Elsevier Ltd.
Published: 2018

12. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

Author: 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, Aminu K, Bennett, Derrick A, Bensenor, Isabela M, Berhane, Adugnaw, Berman, Adam E, Bernabe, Eduardo, Bernstein, Robert S, Bertolacci, Gregory J, Beuran, Mircea, Beyranvand, Tina, Bhala, Neeraj, Bhatia, Eesh, Bhatt, Samir, Bhattarai, Suraj, Bhaumik, Soumyadeeep, Bhutta, Zulfiqar A, Biadgo, Belete, Bijani, Ali, Bikbov, Boris, Bililign, Nigus, Bin Sayeed, Muhammad Shahdaat, Birlik, Sait Mentes, Birungi, Charles, Bisanzio, Donal, Biswas, Tuhin, Bjørge, Tone, Bleyer, Archie, Basara, Berrak Bora, Bose, Dipan, Bosetti, Cristina, Boufous, Soufiane, Bourne, Rupert, Brady, Oliver J, Bragazzi, Nicola Luigi, Brant, Luisa C, Brazinova, Alexandra, Breitborde, Nicholas J K, Brenner, Hermann, Britton, Gabrielle, Brugha, Traolach, Burke, Kristin E, Busse, Reinhard, Butt, Zahid A, Cahuana-Hurtado, Lucero, Callender, Charlton S K H, Campos-Nonato, Ismael R, Campuzano Rincon, Julio Cesar, Cano, Jorge, Car, Mate, Cárdenas, Rosario, Carreras, Giulia, Carrero, Juan J, Carter, Austin, Carvalho, Félix, 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Temesgen, Habtamu, Temsah, Mohamad-Hani, Temsah, Omar, Terkawi, Abdullah Sulieman, Teshale, Manaye Yihune, Tessema, Belay, Teweldemedhin, Mebrahtu, Thakur, Jarnail Singh, Thankappan, Kavumpurathu Raman, Thirunavukkarasu, Sathish, Thomas, Laura Anne, Thomas, Nihal, Thrift, Amanda G, Tilahun, Binyam, To, Quyen G, Tobe-Gai, Ruoyan, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Torre, Anna E, Tortajada-Girbés, Miguel, Tovani-Palone, Marcos Roberto, Towbin, Jeffrey A, Tran, Bach Xuan, Tran, Khanh Bao, Tripathi, Suryakant, Tripathy, Srikanth Prasad, Truelsen, Thomas Clement, Truong, Nu Thi, Tsadik, Afewerki Gebremeskel, Tsilimparis, Nikolao, Tudor Car, Lorainne, Tuzcu, E Murat, Tyrovolas, Stefano, Ukwaja, Kingsley Nnanna, Ullah, Irfan, Usman, Muhammad Shariq, Uthman, Olalekan A, Uzun, Selen Begüm, Vaduganathan, Muthiah, Vaezi, Afsane, Vaidya, Gaurang, Valdez, Pascual R, Varavikova, Elena, Varughese, Santosh, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Venketasubramanian, Narayanaswamy, Vidavalur, Ramesh, Villafaina, Santo, Violante, Francesco S, Vladimirov, Sergey Konstantinovitch, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vosoughi, Kia, Vujcic, Isidora S, Wagner, Gregory R, Wagnew, Fasil Wagnew Shiferaw, Waheed, Yasir, Wang, Yanping, Wang, Yuan-Pang, Wassie, Molla Mesele, Weiderpass, Elisabete, Weintraub, Robert G, Weiss, Daniel J, Weiss, Jordan, Weldegebreal, Fitsum, Weldegwergs, Kidu Gidey, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Widecka, Justyna, Widecka, Katarzyna, Wijeratne, Tissa, Winkler, Andrea Sylvia, Wiysonge, Charles Shey, Wolfe, Charles D A, Wondemagegn, Sintayehu Ambachew, Wu, Shouling, Wyper, Grant M A, Xu, Gelin, Yadav, Rajaram, Yakob, Bereket, Yamada, Tomohide, Yan, Lijing L, Yano, Yuichiro, Yaseri, Mehdi, Yasin, Yasin Jemal, Ye, Pengpeng, Yearwood, Jamal A, Yentür, Gökalp Kadri, Yeshaneh, Alex, Yimer, Ebrahim M, Yip, Paul, Yisma, Engida, Yonemoto, Naohiro, Yoon, Seok-Jun, York, Hunter W, Yotebieng, Marcel, Younis, Mustafa Z, Yousefifard, Mahmoud, Yu, Chuanhua, Zachariah, Geevar, Zadnik, Vesna, Zafar, Shamsa, Zaidi, Zoubida, Zaman, Sojib Bin, Zamani, Mohammad, Zare, Zohreh, Zeeb, Hajo, Zeleke, Mulugeta Molla, Zenebe, Zerihun Menlkalew, Zerfu, Taddese Alemu, Zhang, Kai, Zhang, Xueying, Zhou, Maigeng, Zhu, Jun, Zodpey, Sanjay, Zucker, Inbar, Zuhlke, Liesl Joanna J, Lopez, Alan D, Gakidou, Emmanuela, and Murray, Christopher J L
Subjects: 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).
Published: 2018

13. Early Initiation of Breastfeeding and Associated Factors Among Women of Reproductive age in Simiyu Region, Tanzania.

Author: Shirima LJ, Mlay HL, Mkuwa S, Fabian A, Mushy SE, Ngalesoni FN, Mboya IB, and Manongi RN
Abstract: Background: Breast milk provides infants with complete nutrition for immune development and protection against childhood diseases and associated mortality. Early initiation of breastfeeding (EIBF) aids in providing colostrum to newborns, providing protection against infection, and improving newborn and infant survival. Although Simiyu reported the lowest prevalence of EIBF in Tanzania, no study has investigated the factors associated with EIBF in this region., Objective: The study aimed to determine early breastfeeding initiation prevalence and associated factors among women of reproductive age in the Simiyu region., Methodology: We used data from a cross-sectional study conducted by AMREF Health Africa among 669 women of reproductive age (15-49 years) in the Simiyu region, Tanzania. An interviewer-administered questionnaire collected data on breastfeeding practices (including breastfeeding initiation) among others. A multilevel logistic regression analysis estimated the adjusted odds ratio (OR) and 95% confidence intervals (CI) for factors associated with EIBF., Results: The mean age of 669 women analyzed was 28.3 years (SD ± 6.8). The prevalence of EIBF was 62.2%, ranging from 52.7% in Bariadi district to 73.3% in Maswa district. Lower odds of EIBF were among women who had a caesarian section (OR = 0.41; 95% CI = 0.17-0.98) and those who gave birth to male children (OR = 0.57; 95%CI = 0.39-0.82) while higher odds of EIBF were among mothers who reported skin-to-skin contact (OR = 2.40; 95%CI = 1.53-3.83) and from Maswa district (OR = 2.73; 95%CI = 1.09-6.89)., Conclusion: The prevalence of EIBF in the Simiyu region remains low (62%) relative to the global target of 70% by 2030 and varies by district. To promote EIBF in the region, good engagement and communication practices between mothers and healthcare providers should be emphasised in educating women about the importance of EIBF. Moreover, the practice of skin-to-skin contact between mother and child should be encouraged immediately after delivery., Competing Interests: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (© The Author(s) 2023.)
Published: 2023
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14. Understanding the implication of direct health facility financing on health commodities availability in Tanzania.

Author: Ruhago GM, John MB, Ngalesoni FN, Msasi D, Kapologwe N, Kengia JT, Bukundi E, Ndakidemi R, and Tukai MA
Abstract: The Government of Tanzania (GoT) has in the last decade made progress in strengthening the health system financing with progress towards Universal Health Coverage (UHC). The major reforms includes development of the health financing strategy, reforming the Community Health Fund (CHF) and introduction of the Direct Health Facility Financing (DHFF). DHFF was introduced in all district councils in the 2017/18 financial year. One of the anticipated goals of DHFF is to improve availability of health commodities. The objective of this study is to assess the effect of DHFF in improving the availability of health commodities in primary health care facilities. This study employed cross sectional study design, using quantitative techniques to analyze data related to expenditures and availability of health commodities at the primary health care facilities in Tanzania mainland. Secondary data was extracted from Electronic Logistics Management Information System (eLMIS) and Facility Financial Accounting and Reporting System (FFARS). Descriptive analysis was used to summarize the data using Microsoft Excel (2021) and inferential analysis was done using Stata SE 16.1. There has been an increase in allocation of funds for health commodities over the past three years. The Health Basket Funds (HBFs) accounted for an average of 50% of all health commodities expenditures. The complimentary funds (user fees and insurance) contributed about 20%, which is less than the 50% required by the cost sharing guideline. There is potentiality in DHFF improving visibility and tracking of health commodities funding. Implementation of DHFF has increased the amount of funding for health commodities at health facilities. The visibility and tracking of health commodity funding has improved. There is a scope of increasing health commodity funds at health facilities since the expenditures on health commodities is lower than what is indicated in the cost sharing collection and use guideline., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ruhago et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2023
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15. Strengthening financial management systems at primary health care: Performance assessment of the Facility Financial Accounting and Reporting System (FFARS) in Tanzania.

Author: Ruhago GM, Ngalesoni FN, Kapologwe NA, Kengia JT, Ngocho J, Kabusi SM, Kalolo A, Kitali EJ, Rwamiago E, and Mtei G
Abstract: Background: Universal coverage remains a challenging pursuit around the world, even among the highest-income countries. Strengthening financial management capacity is essential towards attaining the three universal health coverage (UHC) goals, namely, expanded coverage, quality service, and financial protection. In this regard, Tanzania introduced the Facility Financial Accounting and Reporting System (FFARS) in line with the introduction of the Direct Health Facility Financing (DHFF) initiative in primary health care (PHC) in 2017-2018. We aim to assess the functionality of the FFARS in management, accounting, and reporting funds received and disbursed in the stride forward strengthening public financial management in PHC facilities towards UHC., Methods: The study applied implementation research using a concurrent convergent mixed-methods design to assess sources of revenue, expenditure priorities, and changes of revenues and to explore the usability and benefits of FFARS in improving facility finance and reporting systems in more than 5,000 PHC facilities in Tanzania. Quantitative methods assessed the changes in revenues and expenditure between the financial years (FYs) 2017-2018 and 2018-2019, while the qualitative part explored the usability and the benefits FFARS offers in improving facility finances and reporting systems. Data analysis involved a thematic and descriptive analysis for qualitative and quantitative data, respectively., Results: Of the 5,473 PHC facilities, 88% were in rural areas; however, the annual average revenue was higher in urban facilities in FYs 2017-2018 and 2018-2019. Overall, district hospitals showed an increase whereas health centers reported a decline of more than 40% in revenue. The user fee was the predominant source of revenue, particularly in urban facilities, while revenue from health insurance was not among the top three highest sources of revenue. Expenditure priorities leaned more towards drugs and supplies (25%) followed by allowances and training (21%); these did not differ by facility geographies. In health centers, expenditure on facility infrastructure was predominant. Key Informant Interviews revealed an overall satisfaction and positive experiences related to the system., Conclusion: The implementation of FFARS in Tanzania demonstrated its high potential in improving facility financial management, including its ability to track revenue and expenditure at PHC facilities. Staffing shortages, ICT infrastructure, and limited opportunities for capacity building could be the limiting factors to reaching the potential of the implementation of FFARS and the attainment of its full impact on Tanzania's pursuit for UHC., 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., (© 2023 Ruhago, Ngalesoni, Kapologwe, Kengia, Ngocho, Kabusi, Kalolo, Kitali, Rwamiago and Mtei.)
Published: 2023
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16. The public health sector supply chain costs in Tanzania.

Author: Ruhago GM, Ngalesoni FN, Msasi D, Kengia JT, Mganga M, Kapologwe NA, Mtoroki M, and Tukai MA
Abstract: Tanzania's supply chain system is a complicated web of integrated and vertical systems, covering essential and vertical programs health commodities, laboratory and diagnostics, equipment, and supplies. Despite significant improvement in the supply chain over the decades, the availability of medicines has remained uneven. Therefore, identifying the cost of operating the supply chain is vital to facilitate allocation of adequate finances to run the supply chain. We adopted a three-step approach to costing, which included i) identification, ii) measurement, and (iii) valuation of the resource use. Two levels of the Tanzanian supply chain system were examined to determine the cost of running the supply chain by function. These included first the Medical Stores Department (MSD) central and zonal level, secondly the health service delivery level that include National, Zonal and regional hospitals and the Primary Health Care (District Hospital, health center and Dispensary). The review adopted the health system perspective, whereby all resources consumed in delivering health commodities were considered, resource use was then classified as financial and economic costs. The costing period was an average of two financial years, 2015/16 and 2016/17. The cost data were exchanged from Tanzania Shillings to 2017 US$ and then adjusted for inflation to 2020 US$. The study used the total sales reported in audited financial accounts for throughput value. The average annual costs of running the supply chain at the central MSD was estimated at USD$ 15.5 million and US$ 4.1 million at the four sampled MSD Zonal branches. There is a wide variation in annual running costs among MSD zonal branches; the supply chain's unit cost was highest in the Dodoma zone and lowest in the Mwanza zone at 26% and 8%, respectively. When examined on a cost-per-unit basis, supply chain systems operate at sub-optimal levels at health facilities at a unit cost of 37% per unit of commodity throughput value. There are inefficiencies in supply chain financing in Tanzania. Storage costs are higher than distribution costs, this may imply some efficiency gains. MSD should employ a "just in time" inventory model, reducing the inventory holding costs, including the high-expired commodities holding charge, this could be improved by increasing the order fill rate., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Ruhago et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)
Published: 2022
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17. Cost-Efficiency Analysis of the Improved Web-Based Planning, Budgeting, and Reporting System (PlanRep) in Tanzania.

Author: Ruhago GM, Kapologwe NA, Ngalesoni FN, Kengia JT, Kibusi SM, Kalolo A, Kitali EJ, Mtatifikolo JD, Masuha SR, Kikula A, and Mtei G
Abstract: Background: Information systems offer unlimited potential for innovation and digitalization of management functions to facilitate citizen participation and improve accountability, transparency, and efficiency in government operations and service delivery. In line with this, for more than one decade, Tanzania implemented an integrated planning, budgeting, and reporting system (PlanRep) that was used to prepare plans and budgets at the local government authorities (LGAs) using a desktop application. In 2017, PlanRep was upgraded to a Web-based system to address several challenges, including poor coordination and high cost involved in the preparation of plans and budgets. However, operational evidence regarding the cost-efficiencies and benefits of shifting to Web-based PlanRep has not been explored. This study aims to address this gap by assessing efficiency gains (in terms of cost and time) of shifting to a Web-based PlanRep system as a tool for the preparation of LGA plans and budgets., Methods: The study applied a retrospective before-and-after study design whereby quantitative data was used to assess the amount of time and the cost incurred by LGAs when preparing their budget 1 year before the introduction of PlanRep and 1 year after. Parallelly, qualitative data were collected through key informant interviews with selected LGA officials, Regional Secretariats (RSs), President's Office Regional Administration and Local Government (PORALG), and system end-users such as heads of health facilities and schools (primary and secondary). Secondary data was analyzed by comparing time and cost used before and after Web-based PlanRep, while thematic analysis was employed for qualitative data., Results: The analysis showed a 53% reduction (from USD 3.8 million in 2017/18 to USD 1.8 million in 2018/19) in the total costs LGAs incurred during planning and budgeting after introducing the Web-based PlanRep. The main efficiency gain was related to per diem costs. The analysis also showed significant time saving from an average of 87 days in 2017/18 to only 8 days in 2018/19. PlanRep system end-users also acknowledged that the introduction of Web-based PlanRep has significantly saved their time and costs in preparation of LGA plans and budget., Conclusion: The introduction of the Web-based planning, budgeting, and reporting systems has resulted in tremendous cost reduction, time savings, transparency, accountability, and workload reduction. The findings offer operational evidence to guide the implementation and scale up of similar systems in countries that share equivalent circumstances like Tanzania., 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 © 2022 Ruhago, Kapologwe, Ngalesoni, Kengia, Kibusi, Kalolo, Kitali, Mtatifikolo, Masuha, Kikula and Mtei.)
Published: 2022
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18. Global Burden of Hypertension and Systolic Blood Pressure of at Least 110 to 115 mm Hg, 1990-2015.

Author: Forouzanfar MH, Liu P, Roth GA, Ng M, Biryukov S, Marczak L, Alexander L, Estep K, Hassen Abate K, Akinyemiju TF, Ali R, Alvis-Guzman N, Azzopardi P, Banerjee A, Bärnighausen T, Basu A, Bekele T, Bennett DA, Biadgilign S, Catalá-López F, Feigin VL, Fernandes JC, Fischer F, Gebru AA, Gona P, Gupta R, Hankey GJ, Jonas JB, Judd SE, Khang YH, Khosravi A, Kim YJ, Kimokoti RW, Kokubo Y, Kolte D, Lopez A, Lotufo PA, Malekzadeh R, Melaku YA, Mensah GA, Misganaw A, Mokdad AH, Moran AE, Nawaz H, Neal B, Ngalesoni FN, Ohkubo T, Pourmalek F, Rafay A, Rai RK, Rojas-Rueda D, Sampson UK, Santos IS, Sawhney M, Schutte AE, Sepanlou SG, Shifa GT, Shiue I, Tedla BA, Thrift AG, Tonelli M, Truelsen T, Tsilimparis N, Ukwaja KN, Uthman OA, Vasankari T, Venketasubramanian N, Vlassov VV, Vos T, Westerman R, Yan LL, Yano Y, Yonemoto N, Zaki ME, and Murray CJ
Subjects: Adult, Age Distribution, Aged, Aged, 80 and over, Blood Pressure, Cause of Death, Female, Health Surveys, Humans, Hypertension complications, Hypertension mortality, Intracranial Hemorrhages etiology, Intracranial Hemorrhages mortality, Male, Middle Aged, Monte Carlo Method, Myocardial Ischemia etiology, Myocardial Ischemia mortality, Normal Distribution, Prevalence, Quality-Adjusted Life Years, Renal Insufficiency, Chronic etiology, Renal Insufficiency, Chronic mortality, Risk Assessment, Sex Distribution, Stroke etiology, Stroke mortality, Systole, Uncertainty, Global Health statistics & numerical data, Hypertension epidemiology
Abstract: Importance: Elevated systolic blood (SBP) pressure is a leading global health risk. Quantifying the levels of SBP is important to guide prevention policies and interventions., Objective: To estimate the association between SBP of at least 110 to 115 mm Hg and SBP of 140 mm Hg or higher and the burden of different causes of death and disability by age and sex for 195 countries and territories, 1990-2015., Design: A comparative risk assessment of health loss related to SBP. Estimated distribution of SBP was based on 844 studies from 154 countries (published 1980-2015) of 8.69 million participants. Spatiotemporal Gaussian process regression was used to generate estimates of mean SBP and adjusted variance for each age, sex, country, and year. Diseases with sufficient evidence for a causal relationship with high SBP (eg, ischemic heart disease, ischemic stroke, and hemorrhagic stroke) were included in the primary analysis., Main Outcomes and Measures: Mean SBP level, cause-specific deaths, and health burden related to SBP (≥110-115 mm Hg and also ≥140 mm Hg) by age, sex, country, and year., Results: Between 1990-2015, the rate of SBP of at least 110 to 115 mm Hg increased from 73 119 (95% uncertainty interval [UI], 67 949-78 241) to 81 373 (95% UI, 76 814-85 770) per 100 000, and SBP of 140 mm Hg or higher increased from 17 307 (95% UI, 17 117-17 492) to 20 526 (95% UI, 20 283-20 746) per 100 000. The estimated annual death rate per 100 000 associated with SBP of at least 110 to 115 mm Hg increased from 135.6 (95% UI, 122.4-148.1) to 145.2 (95% UI 130.3-159.9) and the rate for SBP of 140 mm Hg or higher increased from 97.9 (95% UI, 87.5-108.1) to 106.3 (95% UI, 94.6-118.1). For loss of DALYs associated with systolic blood pressure of 140 mm Hg or higher, the loss increased from 95.9 million (95% uncertainty interval [UI], 87.0-104.9 million) to 143.0 million (95% UI, 130.2-157.0 million) [corrected], and for SBP of 140 mm Hg or higher, the loss increased from 5.2 million (95% UI, 4.6-5.7 million) to 7.8 million (95% UI, 7.0-8.7 million). The largest numbers of SBP-related deaths were caused by ischemic heart disease (4.9 million [95% UI, 4.0-5.7 million]; 54.5%), hemorrhagic stroke (2.0 million [95% UI, 1.6-2.3 million]; 58.3%), and ischemic stroke (1.5 million [95% UI, 1.2-1.8 million]; 50.0%). In 2015, China, India, Russia, Indonesia, and the United States accounted for more than half of the global DALYs related to SBP of at least 110 to 115 mm Hg., Conclusions and Relevance: In international surveys, although there is uncertainty in some estimates, the rate of elevated SBP (≥110-115 and ≥140 mm Hg) increased substantially between 1990 and 2015, and DALYs and deaths associated with elevated SBP also increased. Projections based on this sample suggest that in 2015, an estimated 3.5 billion adults had SBP of at least 110 to 115 mm Hg and 874 million adults had SBP of 140 mm Hg or higher.
Published: 2017
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19. Equity impact analysis of medical approaches to cardiovascular diseases prevention in Tanzania.

Author: Ngalesoni FN, Ruhago GM, Mori AT, Robberstad B, and Norheim OF
Subjects: Adult, Aged, Cost-Benefit Analysis, Female, Humans, Male, Middle Aged, Preventive Medicine economics, Risk Factors, Tanzania, World Health Organization organization & administration, Cardiovascular Diseases mortality, Cardiovascular Diseases prevention & control, Healthcare Disparities trends, Life Expectancy trends, Preventive Medicine statistics & numerical data
Abstract: Primary medical prevention of cardiovascular disease (CVD) has received low priority in Tanzania, despite evidence of the rising prevalence of CVD risk factors. Different guidelines have been proposed for medical CVD prevention, including the European Society of Cardiology (ESC) and the World Health Organization (WHO) guidelines, which recommend medical prevention for all individuals based on the consideration of single CVD risk thresholds. A third alternative is differentiated risk thresholds according to age. This paper compares the WHO and the differentiated risk threshold by age approaches against a baseline of no medical CVD prevention and a best scenario identical to the ESC approach in Tanzania. Assuming fixed budgets, we evaluate the guidelines according to three outcome measures, namely: efficiency, inequality and the combination of efficiency and inequality. We ran a Markov analysis for an estimated Tanzanian population at risk of CVD employing a 40 years time horizon to estimate the total expected costs and CVD deaths associated with provision of the different guidelines. The results were then used to calculate three outcomes: life expectancy at age 40 as a proxy for efficiency, the Gini coefficient (a measure of inequality), and the achievement index (which combines concerns of efficiency and inequality). Our results suggest that higher life expectancy (28.3 vs. 26.6 years) and more equally distributed health (Gini coefficient of 0.22 vs. 0.24) could be attained if medical CVD prevention was based on the differentiated risk threshold approach compared to the WHO single risk threshold, when the total cost of these approaches is the same. Preventing CVD based on differentiating risk thresholds by age seems to be the better alternative when concerns of both efficiency and inequality are considered important. However, further research on the country-specific distribution of CVD risk levels and budget impact analysis are important to assess the feasibility of its implementation., (Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2016
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20. Cost-effectiveness of medical primary prevention strategies to reduce absolute risk of cardiovascular disease in Tanzania: a Markov modelling study.

Author: Ngalesoni FN, Ruhago GM, Mori AT, Robberstad B, and Norheim OF
Subjects: Adult, Aged, Aged, 80 and over, Angiotensin-Converting Enzyme Inhibitors economics, Angiotensin-Converting Enzyme Inhibitors therapeutic use, Aspirin economics, Aspirin therapeutic use, Calcium Channel Blockers economics, Calcium Channel Blockers therapeutic use, Cardiovascular Diseases economics, Cost-Benefit Analysis, Diabetic Angiopathies economics, Diabetic Angiopathies prevention & control, Female, Humans, Male, Meta-Analysis as Topic, Middle Aged, Platelet Aggregation Inhibitors therapeutic use, Primary Prevention economics, Quality-Adjusted Life Years, Randomized Controlled Trials as Topic, Risk Assessment economics, Risk Assessment methods, Risk Reduction Behavior, Tanzania, Treatment Outcome, Cardiovascular Diseases prevention & control
Abstract: Background: Cardiovascular disease (CVD) is a growing cause of mortality and morbidity in Tanzania, but contextualized evidence on cost-effective medical strategies to prevent it is scarce. We aim to perform a cost-effectiveness analysis of medical interventions for primary prevention of CVD using the World Health Organization's (WHO) absolute risk approach for four risk levels., Methods: The cost-effectiveness analysis was performed from a societal perspective using two Markov decision models: CVD risk without diabetes and CVD risk with diabetes. Primary provider and patient costs were estimated using the ingredients approach and step-down methodologies. Epidemiological data and efficacy inputs were derived from systematic reviews and meta-analyses. We used disability- adjusted life years (DALYs) averted as the outcome measure. Sensitivity analyses were conducted to evaluate the robustness of the model results., Results: For CVD low-risk patients without diabetes, medical management is not cost-effective unless willingness to pay (WTP) is higher than US$1327 per DALY averted. For moderate-risk patients, WTP must exceed US$164 per DALY before a combination of angiotensin converting enzyme inhibitor (ACEI) and diuretic (Diu) becomes cost-effective, while for high-risk and very high-risk patients the thresholds are US$349 (ACEI, calcium channel blocker (CCB) and Diu) and US$498 per DALY (ACEI, CCB, Diu and Aspirin (ASA)) respectively. For patients with CVD risk with diabetes, a combination of sulfonylureas (Sulf), ACEI and CCB for low and moderate risk (incremental cost-effectiveness ratio (ICER) US$608 and US$115 per DALY respectively), is the most cost-effective, while adding biguanide (Big) to this combination yielded the most favourable ICERs of US$309 and US$350 per DALY for high and very high risk respectively. For the latter, ASA is also part of the combination., Conclusions: Medical preventive cardiology is very cost-effective for all risk levels except low CVD risk. Budget impact analyses and distributional concerns should be considered further to assess governments' ability and to whom these benefits will accrue.
Published: 2016
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21. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

Author: Forouzanfar MH, Alexander L, Anderson HR, Bachman VF, Biryukov S, Brauer M, Burnett R, Casey D, Coates MM, Cohen A, Delwiche K, Estep K, Frostad JJ, Astha KC, Kyu HH, Moradi-Lakeh M, Ng M, Slepak EL, Thomas BA, Wagner J, Aasvang GM, Abbafati C, Abbasoglu Ozgoren A, Abd-Allah F, Abera SF, Aboyans V, Abraham B, Abraham JP, Abubakar I, Abu-Rmeileh NM, Aburto TC, Achoki T, Adelekan A, Adofo K, Adou AK, Adsuar JC, Afshin A, Agardh EE, Al Khabouri MJ, Al Lami FH, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Aleman AV, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Ali MK, Alla F, Allebeck P, Allen PJ, Alsharif U, Alvarez E, Alvis-Guzman N, Amankwaa AA, Amare AT, Ameh EA, Ameli O, Amini H, Ammar W, Anderson BO, Antonio CA, Anwari P, Argeseanu Cunningham S, Arnlöv J, Arsenijevic VS, Artaman A, Asghar RJ, Assadi R, Atkins LS, Atkinson C, Avila MA, Awuah B, Badawi A, Bahit MC, Bakfalouni T, Balakrishnan K, Balalla S, Balu RK, Banerjee A, Barber RM, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Barrientos-Gutierrez T, Basto-Abreu AC, Basu A, Basu S, Basulaiman MO, Batis Ruvalcaba C, Beardsley J, Bedi N, Bekele T, Bell ML, Benjet C, Bennett DA, Benzian H, Bernabé E, Beyene TJ, Bhala N, Bhalla A, Bhutta ZA, Bikbov B, Bin Abdulhak AA, Blore JD, Blyth FM, Bohensky MA, Bora Başara B, Borges G, Bornstein NM, Bose D, Boufous S, Bourne RR, Brainin M, Brazinova A, Breitborde NJ, Brenner H, Briggs AD, Broday DM, Brooks PM, Bruce NG, Brugha TS, Brunekreef B, Buchbinder R, Bui LN, Bukhman G, Bulloch AG, Burch M, Burney PG, Campos-Nonato IR, Campuzano JC, Cantoral AJ, Caravanos J, Cárdenas R, Cardis E, Carpenter DO, Caso V, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavalleri F, Çavlin A, Chadha VK, Chang JC, Charlson FJ, Chen H, Chen W, Chen Z, Chiang PP, Chimed-Ochir O, Chowdhury R, Christophi CA, Chuang TW, Chugh SS, Cirillo M, Claßen TK, Colistro V, Colomar M, Colquhoun SM, Contreras AG, Cooper C, Cooperrider K, Cooper LT, Coresh J, Courville KJ, Criqui MH, Cuevas-Nasu L, Damsere-Derry J, Danawi H, Dandona L, Dandona R, Dargan PI, Davis A, Davitoiu DV, Dayama A, de Castro EF, De la Cruz-Góngora V, De Leo D, de Lima G, Degenhardt L, del Pozo-Cruz B, Dellavalle RP, Deribe K, Derrett S, Des Jarlais DC, Dessalegn M, deVeber GA, Devries KM, Dharmaratne SD, Dherani MK, Dicker D, Ding EL, Dokova K, Dorsey ER, Driscoll TR, Duan L, Durrani AM, Ebel BE, Ellenbogen RG, Elshrek YM, Endres M, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Fahimi S, Faraon EJ, Farzadfar F, Fay DF, Feigin VL, Feigl AB, Fereshtehnejad SM, Ferrari AJ, Ferri CP, Flaxman AD, Fleming TD, Foigt N, Foreman KJ, Paleo UF, Franklin RC, Gabbe B, Gaffikin L, Gakidou E, Gamkrelidze A, Gankpé FG, Gansevoort RT, García-Guerra FA, Gasana E, Geleijnse JM, Gessner BD, Gething P, Gibney KB, Gillum RF, Ginawi IA, Giroud M, Giussani G, Goenka S, Goginashvili K, Gomez Dantes H, Gona P, Gonzalez de Cosio T, González-Castell D, Gotay CC, Goto A, Gouda HN, Guerrant RL, Gugnani HC, Guillemin F, Gunnell D, Gupta R, Gupta R, Gutiérrez RA, Hafezi-Nejad N, Hagan H, Hagstromer M, Halasa YA, Hamadeh RR, Hammami M, Hankey GJ, Hao Y, Harb HL, Haregu TN, Haro JM, Havmoeller R, Hay SI, Hedayati MT, Heredia-Pi IB, Hernandez L, Heuton KR, Heydarpour P, Hijar M, Hoek HW, Hoffman HJ, Hornberger JC, Hosgood HD, Hoy DG, Hsairi M, Hu G, Hu H, Huang C, Huang JJ, Hubbell BJ, Huiart L, Husseini A, Iannarone ML, Iburg KM, Idrisov BT, Ikeda N, Innos K, Inoue M, Islami F, Ismayilova S, Jacobsen KH, Jansen HA, Jarvis DL, Jassal SK, Jauregui A, Jayaraman S, Jeemon P, Jensen PN, Jha V, Jiang F, Jiang G, Jiang Y, Jonas JB, Juel K, Kan H, Kany Roseline SS, Karam NE, Karch A, Karema CK, Karthikeyan G, Kaul A, Kawakami N, Kazi DS, Kemp AH, Kengne AP, Keren A, Khader YS, Khalifa SE, Khan EA, Khang YH, Khatibzadeh S, Khonelidze I, Kieling C, Kim D, Kim S, Kim Y, Kimokoti RW, Kinfu Y, Kinge JM, Kissela BM, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kose MR, Kosen S, Kraemer A, Kravchenko M, Krishnaswami S, Kromhout H, Ku T, Kuate Defo B, Kucuk Bicer B, Kuipers EJ, Kulkarni C, Kulkarni VS, Kumar GA, Kwan GF, Lai T, Lakshmana Balaji A, Lalloo R, Lallukka T, Lam H, Lan Q, Lansingh VC, Larson HJ, Larsson A, Laryea DO, Lavados PM, Lawrynowicz AE, Leasher JL, Lee JT, Leigh J, Leung R, Levi M, Li Y, Li Y, Liang J, Liang X, Lim SS, Lindsay MP, Lipshultz SE, Liu S, Liu Y, Lloyd BK, Logroscino G, London SJ, Lopez N, Lortet-Tieulent J, Lotufo PA, Lozano R, Lunevicius R, Ma J, Ma S, Machado VM, MacIntyre MF, Magis-Rodriguez C, Mahdi AA, Majdan M, Malekzadeh R, Mangalam S, Mapoma CC, Marape M, Marcenes W, Margolis DJ, Margono C, Marks GB, Martin RV, Marzan MB, Mashal MT, Masiye F, Mason-Jones AJ, Matsushita K, Matzopoulos R, Mayosi BM, Mazorodze TT, McKay AC, McKee M, McLain A, Meaney PA, Medina C, Mehndiratta MM, Mejia-Rodriguez F, Mekonnen W, Melaku YA, Meltzer M, Memish ZA, Mendoza W, Mensah GA, Meretoja A, Mhimbira FA, Micha R, Miller TR, Mills EJ, Misganaw A, Mishra S, Mohamed Ibrahim N, Mohammad KA, Mokdad AH, Mola GL, Monasta L, Montañez Hernandez JC, Montico M, Moore AR, Morawska L, Mori R, Moschandreas J, Moturi WN, Mozaffarian D, Mueller UO, Mukaigawara M, Mullany EC, Murthy KS, Naghavi M, Nahas Z, Naheed A, Naidoo KS, Naldi L, Nand D, Nangia V, Narayan KM, Nash D, Neal B, Nejjari C, Neupane SP, Newton CR, Ngalesoni FN, Ngirabega Jde D, Nguyen G, Nguyen NT, Nieuwenhuijsen MJ, Nisar MI, Nogueira JR, Nolla JM, Nolte S, Norheim OF, Norman RE, Norrving B, Nyakarahuka L, Oh IH, Ohkubo T, Olusanya BO, Omer SB, Opio JN, Orozco R, Pagcatipunan RS Jr, Pain AW, Pandian JD, Panelo CI, Papachristou C, Park EK, Parry CD, Paternina Caicedo AJ, Patten SB, Paul VK, Pavlin BI, Pearce N, Pedraza LS, Pedroza A, Pejin Stokic L, Pekericli A, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Perry SA, Pervaiz A, Pesudovs K, Peterson CB, Petzold M, Phillips MR, Phua HP, Plass D, Poenaru D, Polanczyk GV, Polinder S, Pond CD, Pope CA, Pope D, Popova S, Pourmalek F, Powles J, Prabhakaran D, Prasad NM, Qato DM, Quezada AD, Quistberg DA, Racapé L, Rafay A, Rahimi K, Rahimi-Movaghar V, Rahman SU, Raju M, Rakovac I, Rana SM, Rao M, Razavi H, Reddy KS, Refaat AH, Rehm J, Remuzzi G, Ribeiro AL, Riccio PM, Richardson L, Riederer A, Robinson M, Roca A, Rodriguez A, Rojas-Rueda D, Romieu I, Ronfani L, Room R, Roy N, Ruhago GM, Rushton L, Sabin N, Sacco RL, Saha S, Sahathevan R, Sahraian MA, Salomon JA, Salvo D, Sampson UK, Sanabria JR, Sanchez LM, Sánchez-Pimienta TG, Sanchez-Riera L, Sandar L, Santos IS, Sapkota A, Satpathy M, Saunders JE, Sawhney M, Saylan MI, Scarborough P, Schmidt JC, Schneider IJ, Schöttker B, Schwebel DC, Scott JG, Seedat S, Sepanlou SG, Serdar B, Servan-Mori EE, Shaddick G, Shahraz S, Levy TS, Shangguan S, She J, Sheikhbahaei S, Shibuya K, Shin HH, Shinohara Y, Shiri R, Shishani K, Shiue I, Sigfusdottir ID, Silberberg DH, Simard EP, Sindi S, Singh A, Singh GM, Singh JA, Skirbekk V, Sliwa K, Soljak M, Soneji S, Søreide K, Soshnikov S, Sposato LA, Sreeramareddy CT, Stapelberg NJ, Stathopoulou V, Steckling N, Stein DJ, Stein MB, Stephens N, Stöckl H, Straif K, Stroumpoulis K, Sturua L, Sunguya BF, Swaminathan S, Swaroop M, Sykes BL, Tabb KM, Takahashi K, Talongwa RT, Tandon N, Tanne D, Tanner M, Tavakkoli M, Te Ao BJ, Teixeira CM, Téllez Rojo MM, Terkawi AS, Texcalac-Sangrador JL, Thackway SV, Thomson B, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tobollik M, Tonelli M, Topouzis F, Towbin JA, Toyoshima H, Traebert J, Tran BX, Trasande L, Trillini M, Trujillo U, Dimbuene ZT, Tsilimbaris M, Tuzcu EM, Uchendu US, Ukwaja KN, Uzun SB, van de Vijver S, Van Dingenen R, van Gool CH, van Os J, Varakin YY, Vasankari TJ, Vasconcelos AM, Vavilala MS, Veerman LJ, Velasquez-Melendez G, Venketasubramanian N, Vijayakumar L, Villalpando S, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Waller SG, Wallin MT, Wan X, Wang H, Wang J, Wang L, Wang W, Wang Y, Warouw TS, Watts CH, Weichenthal S, Weiderpass E, Weintraub RG, Werdecker A, Wessells KR, Westerman R, Whiteford HA, Wilkinson JD, Williams HC, Williams TN, Woldeyohannes SM, Wolfe CD, Wong JQ, Woolf AD, Wright JL, Wurtz B, Xu G, Yan LL, Yang G, Yano Y, Ye P, Yenesew M, Yentür GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Younoussi Z, Yu C, Zaki ME, Zhao Y, Zheng Y, Zhou M, Zhu J, Zhu S, Zou X, Zunt JR, Lopez AD, Vos T, and Murray CJ
Subjects: Female, Global Health statistics & numerical data, Health Behavior, Humans, Male, Nutritional Status, Occupational Exposure adverse effects, Risk Assessment methods, Risk Factors, Sanitation trends, Environmental Exposure adverse effects, Global Health trends, Metabolic Diseases epidemiology, Occupational Diseases epidemiology
Abstract: Background: The Global Burden of Disease, Injuries, and Risk Factor study 2013 (GBD 2013) is the first of a series of annual updates of the GBD. Risk factor quantification, particularly of modifiable risk factors, can help to identify emerging threats to population health and opportunities for prevention. The GBD 2013 provides a timely opportunity to update the comparative risk assessment with new data for exposure, relative risks, and evidence on the appropriate counterfactual risk distribution., Methods: Attributable deaths, years of life lost, years lived with disability, and disability-adjusted life-years (DALYs) have been estimated for 79 risks or clusters of risks using the GBD 2010 methods. Risk-outcome pairs meeting explicit evidence criteria were assessed for 188 countries for the period 1990-2013 by age and sex using three inputs: risk exposure, relative risks, and the theoretical minimum risk exposure level (TMREL). Risks are organised into a hierarchy with blocks of behavioural, environmental and occupational, and metabolic risks at the first level of the hierarchy. The next level in the hierarchy includes nine clusters of related risks and two individual risks, with more detail provided at levels 3 and 4 of the hierarchy. Compared with GBD 2010, six new risk factors have been added: handwashing practices, occupational exposure to trichloroethylene, childhood wasting, childhood stunting, unsafe sex, and low glomerular filtration rate. For most risks, data for exposure were synthesised with a Bayesian meta-regression method, DisMod-MR 2.0, or spatial-temporal Gaussian process regression. Relative risks were based on meta-regressions of published cohort and intervention studies. Attributable burden for clusters of risks and all risks combined took into account evidence on the mediation of some risks such as high body-mass index (BMI) through other risks such as high systolic blood pressure and high cholesterol., Findings: All risks combined account for 57·2% (95% uncertainty interval [UI] 55·8-58·5) of deaths and 41·6% (40·1-43·0) of DALYs. Risks quantified account for 87·9% (86·5-89·3) of cardiovascular disease DALYs, ranging to a low of 0% for neonatal disorders and neglected tropical diseases and malaria. In terms of global DALYs in 2013, six risks or clusters of risks each caused more than 5% of DALYs: dietary risks accounting for 11·3 million deaths and 241·4 million DALYs, high systolic blood pressure for 10·4 million deaths and 208·1 million DALYs, child and maternal malnutrition for 1·7 million deaths and 176·9 million DALYs, tobacco smoke for 6·1 million deaths and 143·5 million DALYs, air pollution for 5·5 million deaths and 141·5 million DALYs, and high BMI for 4·4 million deaths and 134·0 million DALYs. Risk factor patterns vary across regions and countries and with time. In sub-Saharan Africa, the leading risk factors are child and maternal malnutrition, unsafe sex, and unsafe water, sanitation, and handwashing. In women, in nearly all countries in the Americas, north Africa, and the Middle East, and in many other high-income countries, high BMI is the leading risk factor, with high systolic blood pressure as the leading risk in most of Central and Eastern Europe and south and east Asia. For men, high systolic blood pressure or tobacco use are the leading risks in nearly all high-income countries, in north Africa and the Middle East, Europe, and Asia. For men and women, unsafe sex is the leading risk in a corridor from Kenya to South Africa., Interpretation: Behavioural, environmental and occupational, and metabolic risks can explain half of global mortality and more than one-third of global DALYs providing many opportunities for prevention. Of the larger risks, the attributable burden of high BMI has increased in the past 23 years. In view of the prominence of behavioural risk factors, behavioural and social science research on interventions for these risks should be strengthened. Many prevention and primary care policy options are available now to act on key risks., Funding: Bill & Melinda Gates Foundation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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22. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

Author: Murray CJ, Barber RM, Foreman KJ, Abbasoglu Ozgoren A, Abd-Allah F, Abera SF, Aboyans V, Abraham JP, Abubakar I, Abu-Raddad LJ, Abu-Rmeileh NM, Achoki T, Ackerman IN, Ademi Z, Adou AK, Adsuar JC, Afshin A, Agardh EE, Alam SS, Alasfoor D, Albittar MI, Alegretti MA, Alemu ZA, Alfonso-Cristancho R, Alhabib S, Ali R, Alla F, Allebeck P, Almazroa MA, Alsharif U, Alvarez E, Alvis-Guzman N, Amare AT, Ameh EA, Amini H, Ammar W, Anderson HR, Anderson BO, Antonio CA, Anwari P, Arnlöv J, Arsic Arsenijevic VS, Artaman A, Asghar RJ, Assadi R, Atkins LS, Avila MA, Awuah B, Bachman VF, Badawi A, Bahit MC, Balakrishnan K, Banerjee A, Barker-Collo SL, Barquera S, Barregard L, Barrero LH, Basu A, Basu S, Basulaiman MO, Beardsley J, Bedi N, Beghi E, Bekele T, Bell ML, Benjet C, Bennett DA, Bensenor IM, Benzian H, Bernabé E, Bertozzi-Villa A, Beyene TJ, Bhala N, Bhalla A, Bhutta ZA, Bienhoff K, Bikbov B, Biryukov S, Blore JD, Blosser CD, Blyth FM, Bohensky MA, Bolliger IW, Bora Başara B, Bornstein NM, Bose D, Boufous S, Bourne RR, Boyers LN, Brainin M, Brayne CE, Brazinova A, Breitborde NJ, Brenner H, Briggs AD, Brooks PM, Brown JC, Brugha TS, Buchbinder R, Buckle GC, Budke CM, Bulchis A, Bulloch AG, Campos-Nonato IR, Carabin H, Carapetis JR, Cárdenas R, Carpenter DO, Caso V, Castañeda-Orjuela CA, Castro RE, Catalá-López F, Cavalleri F, Çavlin A, Chadha VK, Chang JC, Charlson FJ, Chen H, Chen W, Chiang PP, Chimed-Ochir O, Chowdhury R, Christensen H, Christophi CA, Cirillo M, Coates MM, Coffeng LE, Coggeshall MS, Colistro V, Colquhoun SM, Cooke GS, Cooper C, Cooper LT, Coppola LM, Cortinovis M, Criqui MH, Crump JA, Cuevas-Nasu L, Danawi H, Dandona L, Dandona R, Dansereau E, Dargan PI, Davey G, Davis A, Davitoiu DV, Dayama A, De Leo D, Degenhardt L, Del Pozo-Cruz B, Dellavalle RP, Deribe K, Derrett S, Des Jarlais DC, Dessalegn M, Dharmaratne SD, Dherani MK, Diaz-Torné C, Dicker D, Ding EL, Dokova K, Dorsey ER, Driscoll TR, Duan L, Duber HC, Ebel BE, Edmond KM, Elshrek YM, Endres M, Ermakov SP, Erskine HE, Eshrati B, Esteghamati A, Estep K, Faraon EJ, Farzadfar F, Fay DF, Feigin VL, Felson DT, Fereshtehnejad SM, Fernandes JG, Ferrari AJ, Fitzmaurice C, Flaxman AD, Fleming TD, Foigt N, Forouzanfar MH, Fowkes FG, Paleo UF, Franklin RC, Fürst T, Gabbe B, Gaffikin L, Gankpé FG, Geleijnse JM, Gessner BD, Gething P, Gibney KB, Giroud M, Giussani G, Gomez Dantes H, Gona P, González-Medina D, Gosselin RA, Gotay CC, Goto A, Gouda HN, Graetz N, Gugnani HC, Gupta R, Gupta R, Gutiérrez RA, Haagsma J, Hafezi-Nejad N, Hagan H, Halasa YA, Hamadeh RR, Hamavid H, Hammami M, Hancock J, Hankey GJ, Hansen GM, Hao Y, Harb HL, Haro JM, Havmoeller R, Hay SI, Hay RJ, Heredia-Pi IB, Heuton KR, Heydarpour P, Higashi H, Hijar M, Hoek HW, Hoffman HJ, Hosgood HD, Hossain M, Hotez PJ, Hoy DG, Hsairi M, Hu G, Huang C, Huang JJ, Husseini A, Huynh C, Iannarone ML, Iburg KM, Innos K, Inoue M, Islami F, Jacobsen KH, Jarvis DL, Jassal SK, Jee SH, Jeemon P, Jensen PN, Jha V, Jiang G, Jiang Y, Jonas JB, Juel K, Kan H, Karch A, Karema CK, Karimkhani C, Karthikeyan G, Kassebaum NJ, Kaul A, Kawakami N, Kazanjan K, Kemp AH, Kengne AP, Keren A, Khader YS, Khalifa SE, Khan EA, Khan G, Khang YH, Kieling C, Kim D, Kim S, Kim Y, Kinfu Y, Kinge JM, Kivipelto M, Knibbs LD, Knudsen AK, Kokubo Y, Kosen S, Krishnaswami S, Kuate Defo B, Kucuk Bicer B, Kuipers EJ, Kulkarni C, Kulkarni VS, Kumar GA, Kyu HH, Lai T, Lalloo R, Lallukka T, Lam H, Lan Q, Lansingh VC, Larsson A, Lawrynowicz AE, Leasher JL, Leigh J, Leung R, Levitz CE, Li B, Li Y, Li Y, Lim SS, Lind M, Lipshultz SE, Liu S, Liu Y, Lloyd BK, Lofgren KT, Logroscino G, Looker KJ, Lortet-Tieulent J, Lotufo PA, Lozano R, Lucas RM, Lunevicius R, Lyons RA, Ma S, Macintyre MF, Mackay MT, Majdan M, Malekzadeh R, Marcenes W, Margolis DJ, Margono C, Marzan MB, Masci JR, Mashal MT, Matzopoulos R, Mayosi BM, Mazorodze TT, Mcgill NW, Mcgrath JJ, Mckee M, Mclain A, Meaney PA, Medina C, Mehndiratta MM, Mekonnen W, Melaku YA, Meltzer M, Memish ZA, Mensah GA, Meretoja A, Mhimbira FA, Micha R, Miller TR, Mills EJ, Mitchell PB, Mock CN, Mohamed Ibrahim N, Mohammad KA, Mokdad AH, Mola GL, Monasta L, Montañez Hernandez JC, Montico M, Montine TJ, Mooney MD, Moore AR, Moradi-Lakeh M, Moran AE, Mori R, Moschandreas J, Moturi WN, Moyer ML, Mozaffarian D, Msemburi WT, Mueller UO, Mukaigawara M, Mullany EC, Murdoch ME, Murray J, Murthy KS, Naghavi M, Naheed A, Naidoo KS, Naldi L, Nand D, Nangia V, Narayan KM, Nejjari C, Neupane SP, Newton CR, Ng M, Ngalesoni FN, Nguyen G, Nisar MI, Nolte S, Norheim OF, Norman RE, Norrving B, Nyakarahuka L, Oh IH, Ohkubo T, Ohno SL, Olusanya BO, Opio JN, Ortblad K, Ortiz A, Pain AW, Pandian JD, Panelo CI, Papachristou C, Park EK, Park JH, Patten SB, Patton GC, Paul VK, Pavlin BI, Pearce N, Pereira DM, Perez-Padilla R, Perez-Ruiz F, Perico N, Pervaiz A, Pesudovs K, Peterson CB, Petzold M, Phillips MR, Phillips BK, Phillips DE, Piel FB, Plass D, Poenaru D, Polinder S, Pope D, Popova S, Poulton RG, Pourmalek F, Prabhakaran D, Prasad NM, Pullan RL, Qato DM, Quistberg DA, Rafay A, Rahimi K, Rahman SU, Raju M, Rana SM, Razavi H, Reddy KS, Refaat A, Remuzzi G, Resnikoff S, Ribeiro AL, Richardson L, Richardus JH, Roberts DA, Rojas-Rueda D, Ronfani L, Roth GA, Rothenbacher D, Rothstein DH, Rowley JT, Roy N, Ruhago GM, Saeedi MY, Saha S, Sahraian MA, Sampson UK, Sanabria JR, Sandar L, Santos IS, Satpathy M, Sawhney M, Scarborough P, Schneider IJ, Schöttker B, Schumacher AE, Schwebel DC, Scott JG, Seedat S, Sepanlou SG, Serina PT, Servan-Mori EE, Shackelford KA, Shaheen A, Shahraz S, Shamah Levy T, Shangguan S, She J, Sheikhbahaei S, Shi P, Shibuya K, Shinohara Y, Shiri R, Shishani K, Shiue I, Shrime MG, Sigfusdottir ID, Silberberg DH, Simard EP, Sindi S, Singh A, Singh JA, Singh L, Skirbekk V, Slepak EL, Sliwa K, Soneji S, Søreide K, Soshnikov S, Sposato LA, Sreeramareddy CT, Stanaway JD, Stathopoulou V, Stein DJ, Stein MB, Steiner C, Steiner TJ, Stevens A, Stewart A, Stovner LJ, Stroumpoulis K, Sunguya BF, Swaminathan S, Swaroop M, Sykes BL, Tabb KM, Takahashi K, Tandon N, Tanne D, Tanner M, Tavakkoli M, Taylor HR, Te Ao BJ, Tediosi F, Temesgen AM, Templin T, Ten Have M, Tenkorang EY, Terkawi AS, Thomson B, Thorne-Lyman AL, Thrift AG, Thurston GD, Tillmann T, Tonelli M, Topouzis F, Toyoshima H, Traebert J, Tran BX, Trillini M, Truelsen T, Tsilimbaris M, Tuzcu EM, Uchendu US, Ukwaja KN, Undurraga EA, Uzun SB, Van Brakel WH, Van De Vijver S, van Gool CH, Van Os J, Vasankari TJ, Venketasubramanian N, Violante FS, Vlassov VV, Vollset SE, Wagner GR, Wagner J, Waller SG, Wan X, Wang H, Wang J, Wang L, Warouw TS, Weichenthal S, Weiderpass E, Weintraub RG, Wenzhi W, Werdecker A, Westerman R, Whiteford HA, Wilkinson JD, Williams TN, Wolfe CD, Wolock TM, Woolf AD, Wulf S, Wurtz B, Xu G, Yan LL, Yano Y, Ye P, Yentür GK, Yip P, Yonemoto N, Yoon SJ, Younis MZ, Yu C, Zaki ME, Zhao Y, Zheng Y, Zonies D, Zou X, Salomon JA, Lopez AD, and Vos T
Subjects: Aged, Female, Humans, Male, Middle Aged, Mortality, Premature, Quality-Adjusted Life Years, Socioeconomic Factors, Chronic Disease epidemiology, Communicable Diseases epidemiology, Global Health statistics & numerical data, Health Transition, Life Expectancy, Wounds and Injuries epidemiology
Abstract: Background: The Global Burden of Disease Study 2013 (GBD 2013) aims to bring together all available epidemiological data using a coherent measurement framework, standardised estimation methods, and transparent data sources to enable comparisons of health loss over time and across causes, age-sex groups, and countries. The GBD can be used to generate summary measures such as disability-adjusted life-years (DALYs) and healthy life expectancy (HALE) that make possible comparative assessments of broad epidemiological patterns across countries and time. These summary measures can also be used to quantify the component of variation in epidemiology that is related to sociodemographic development., Methods: We used the published GBD 2013 data for age-specific mortality, years of life lost due to premature mortality (YLLs), and years lived with disability (YLDs) to calculate DALYs and HALE for 1990, 1995, 2000, 2005, 2010, and 2013 for 188 countries. We calculated HALE using the Sullivan method; 95% uncertainty intervals (UIs) represent uncertainty in age-specific death rates and YLDs per person for each country, age, sex, and year. We estimated DALYs for 306 causes for each country as the sum of YLLs and YLDs; 95% UIs represent uncertainty in YLL and YLD rates. We quantified patterns of the epidemiological transition with a composite indicator of sociodemographic status, which we constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population. We applied hierarchical regression to DALY rates by cause across countries to decompose variance related to the sociodemographic status variable, country, and time., Findings: Worldwide, from 1990 to 2013, life expectancy at birth rose by 6·2 years (95% UI 5·6-6·6), from 65·3 years (65·0-65·6) in 1990 to 71·5 years (71·0-71·9) in 2013, HALE at birth rose by 5·4 years (4·9-5·8), from 56·9 years (54·5-59·1) to 62·3 years (59·7-64·8), total DALYs fell by 3·6% (0·3-7·4), and age-standardised DALY rates per 100 000 people fell by 26·7% (24·6-29·1). For communicable, maternal, neonatal, and nutritional disorders, global DALY numbers, crude rates, and age-standardised rates have all declined between 1990 and 2013, whereas for non-communicable diseases, global DALYs have been increasing, DALY rates have remained nearly constant, and age-standardised DALY rates declined during the same period. From 2005 to 2013, the number of DALYs increased for most specific non-communicable diseases, including cardiovascular diseases and neoplasms, in addition to dengue, food-borne trematodes, and leishmaniasis; DALYs decreased for nearly all other causes. By 2013, the five leading causes of DALYs were ischaemic heart disease, lower respiratory infections, cerebrovascular disease, low back and neck pain, and road injuries. Sociodemographic status explained more than 50% of the variance between countries and over time for diarrhoea, lower respiratory infections, and other common infectious diseases; maternal disorders; neonatal disorders; nutritional deficiencies; other communicable, maternal, neonatal, and nutritional diseases; musculoskeletal disorders; and other non-communicable diseases. However, sociodemographic status explained less than 10% of the variance in DALY rates for cardiovascular diseases; chronic respiratory diseases; cirrhosis; diabetes, urogenital, blood, and endocrine diseases; unintentional injuries; and self-harm and interpersonal violence. Predictably, increased sociodemographic status was associated with a shift in burden from YLLs to YLDs, driven by declines in YLLs and increases in YLDs from musculoskeletal disorders, neurological disorders, and mental and substance use disorders. In most country-specific estimates, the increase in life expectancy was greater than that in HALE. Leading causes of DALYs are highly variable across countries., Interpretation: Global health is improving. Population growth and ageing have driven up numbers of DALYs, but crude rates have remained relatively constant, showing that progress in health does not mean fewer demands on health systems. The notion of an epidemiological transition--in which increasing sociodemographic status brings structured change in disease burden--is useful, but there is tremendous variation in burden of disease that is not associated with sociodemographic status. This further underscores the need for country-specific assessments of DALYs and HALE to appropriately inform health policy decisions and attendant actions., Funding: Bill & Melinda Gates Foundation., (Copyright © 2015 Elsevier Ltd. All rights reserved.)
Published: 2015
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23. Cost-effectiveness of live oral attenuated human rotavirus vaccine in Tanzania.

Author: Ruhago GM, Ngalesoni FN, Robberstad B, and Norheim OF
Abstract: Background: Globally, diarrhoea is the second leading cause of morbidity and mortality, responsible for the annual loss of about 10% of the total global childhood disease burden. In Tanzania, Rotavirus infection is the major cause of severe diarrhoea and diarrhoeal mortality in children under five years. Immunisation can reduce the burden, and Tanzania added rotavirus vaccine to its national immunisation programme in January 2013. This study explores the cost effectiveness of introducing rotavirus vaccine within the Tanzania Expanded Programme on Immunisation (EPI)., Methods: We quantified all health system implementation costs, including programme costs, to calculate the cost effectiveness of adding rotavirus immunisation to EPI and the existing provision of diarrhoea treatment (oral rehydration salts and intravenous fluids) to children. We used ingredients and step down costing methods. Cost and coverage data were collected in 2012 at one urban and one rural district hospital and a health centre in Tanzania. We used Disability Adjusted Life Years (DALYs) as the outcome measure and estimated incremental costs and health outcomes using a Markov transition model with weekly cycles up to a five-year time horizon., Results: The average unit cost per vaccine dose at 93% coverage is US$ 8.4, with marked difference between the urban facility US$ 5.2; and the rural facility US$ 9.8. RV1 vaccine added to current diarrhoea treatment is highly cost effective compared to diarrhoea treatment given alone, with incremental cost effectiveness ratio of US$ 112 per DALY averted, varying from US$ 80-218 in sensitivity analysis. The intervention approaches a 100% probability of being cost effective at a much lower level of willingness-to-pay than the US$609 per capita Tanzania gross domestic product (GDP)., Conclusions: The combination of rotavirus immunisation with diarrhoea treatment is likely to be cost effective when willingness to pay for health is higher than USD 112 per DALY. Universal coverage of the vaccine will accelerate progress towards achievement of the child health Millennium Development Goals.
Published: 2015
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24. Addressing inequity to achieve the maternal and child health millennium development goals: looking beyond averages.

Author: Ruhago GM, Ngalesoni FN, and Norheim OF
Subjects: Adult, Child, Preschool, Female, Goals, Humans, Rural Population, Tanzania, Universal Health Insurance, Urban Population, Health Priorities, Health Promotion legislation & jurisprudence, Healthcare Disparities, Maternal-Child Health Centers standards, Program Development
Abstract: Background: Inequity in access to and use of child and maternal health interventions is impeding progress towards the maternal and child health Millennium Development Goals. This study explores the potential health gains and equity impact if a set of priority interventions for mothers and under fives were scaled up to reach national universal coverage targets for MDGs in Tanzania., Methods: We used the Lives Saved Tool (LiST) to estimate potential reductions in maternal and child mortality and the number of lives saved across wealth quintiles and between rural and urban settings. High impact maternal and child health interventions were modelled for a five-year scale up, by linking intervention coverage, effectiveness and cause of mortality using data from Tanzania. Concentration curves were drawn and the concentration index estimated to measure the equity impact of the scale up., Results: In the poorest population quintiles in Tanzania, the lives of more than twice as many mothers and under-fives were likely to be saved, compared to the richest quintile. Scaling up coverage to equal levels across quintiles would reduce inequality in maternal and child mortality from a pro rich concentration index of -0.11 (maternal) and -0.12 (children) to a more equitable concentration index of -0,03 and -0.03 respectively. In rural areas, there would likely be an eight times greater reduction in maternal deaths than in urban areas and a five times greater reduction in child deaths than in urban areas., Conclusions: Scaling up priority maternal and child health interventions to equal levels would potentially save far more lives in the poorest populations, and would accelerate equitable progress towards maternal and child health MDGs.
Published: 2012
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24 results on '"Ngalesoni FN"'

1. Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

2. Spending on health and HIV/AIDS: domestic health spending and development assistance in 188 countries, 1995–2015

3. Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40

4. 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

5. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015 : the Global Burden of Disease Study 2015

6. 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

7. Estimates of global, regional, and national incidence, prevalence, and mortality of HIV, 1980-2015: the Global Burden of Disease Study 2015

8. Global, regional, and national levels of maternal mortality, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

9. Measuring progress from 1990 to 2017 and projecting attainment to 2030 of the health-related Sustainable Development Goals for 195 countries and territories: a systematic analysis for the Global Burden of Disease Study 2017

10. 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

11. Population and fertility by age and sex for 195 countries and territories, 1950-2017: a systematic analysis for the Global Burden of Disease Study 2017

12. Global, regional, and national age-sex-specific mortality and life expectancy, 1950–2017: a systematic analysis for the Global Burden of Disease Study 2017

13. Early Initiation of Breastfeeding and Associated Factors Among Women of Reproductive age in Simiyu Region, Tanzania.

14. Understanding the implication of direct health facility financing on health commodities availability in Tanzania.

15. Strengthening financial management systems at primary health care: Performance assessment of the Facility Financial Accounting and Reporting System (FFARS) in Tanzania.

16. The public health sector supply chain costs in Tanzania.

17. Cost-Efficiency Analysis of the Improved Web-Based Planning, Budgeting, and Reporting System (PlanRep) in Tanzania.

18. Global Burden of Hypertension and Systolic Blood Pressure of at Least 110 to 115 mm Hg, 1990-2015.

19. Equity impact analysis of medical approaches to cardiovascular diseases prevention in Tanzania.

20. Cost-effectiveness of medical primary prevention strategies to reduce absolute risk of cardiovascular disease in Tanzania: a Markov modelling study.

21. Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks in 188 countries, 1990-2013: a systematic analysis for the Global Burden of Disease Study 2013.

22. Global, regional, and national disability-adjusted life years (DALYs) for 306 diseases and injuries and healthy life expectancy (HALE) for 188 countries, 1990-2013: quantifying the epidemiological transition.

23. Cost-effectiveness of live oral attenuated human rotavirus vaccine in Tanzania.

24. Addressing inequity to achieve the maternal and child health millennium development goals: looking beyond averages.

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