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1. Cost Analysis of High-Flow Oxygen Therapy Compared with Conventional Oxygen Therapy in Severe COVID-19 in Colombia: Data from a Randomized Clinical Trial

Author: Prada SI, Garcia-Garcia MP, Ospina-Tascón GA, and Rosselli D
Subjects: sars-cov-2, covid-19, cost analysis, economic evaluation, high-flow nasal oxygen, conventional oxygen therapy, high-flow oxygen therapy, clinical trial, cost, colombia., Medicine (General), R5-920, Therapeutics. Pharmacology, RM1-950
Abstract: Sergio I Prada,1,2 Maria P Garcia-Garcia,1 Gustavo A Ospina-Tascón,3,4 Diego Rosselli5 1Fundación Valle del Lili, Centro de Investigaciones Clínicas, Cali, Colombia; 2Universidad Icesi, Centro PROESA, Cali, Colombia; 3Department of Intensive Care, Fundación Valle del Lili, Cali, Colombia; 4Translational Medicine Laboratory in Critical Care (TransLab-CCM), Universidad Icesi, Cali, Colombia; 5Clinical Epidemiology and Biostatistics Department, Pontificia Universidad Javeriana, Bogota, ColombiaCorrespondence: Sergio I Prada, Centro de Investigaciones Clínicas, Fundación Valle del Lili, Cra. 98 18-49, Cali, Valle, Colombia, Email sergio.prada@fvl.org.coBackground: A randomized clinical trial (HiFlo-COVID-19 Trial) showed that among patients with severe COVID-19, treatment with high-flow oxygen therapy (HFOT) significantly reduced the need for invasive mechanical ventilation support and time for clinical recovery compared with conventional oxygen therapy (COT). However, the cost of this strategy is unknown.Objective: We examined total cost of HFOT treatment compared with COT in real-world setting.Methods: We conducted a post-trial-based cost analysis from the perspective of a managed competition healthcare system, using actual records of billed costs. Cost categories include general ward, intensive care unit, procedures, imaging, laboratories, medications, supplies, and others.Results: A total of 188 participants (mean age 60, 33% female) were included. Average costs (and standard deviation) in the HFOT group were USD &dollar;7992 (7394) and in the COT group USD &dollar; 10,190 (9402). Differences, however, did not reach statistical significance (P=0.093). However, resource use was always less costly for the HNFO group, with an overall percentage decrease of 27%. Two categories make up 72% of all savings: medications (41%) and intensive care unit (31%).Conclusion: For patients in ICU with severe COVID-19 the cost of treatment with HFOT as compared to COT is likely to be cost-saving due to less use of medications and length of stay in ICU.Keywords: SARS-CoV-2, COVID-19, cost analysis, economic evaluation, high-flow nasal oxygen, conventional oxygen therapy, high-flow oxygen therapy, clinical trial, cost, Colombia
Published: 2023

2. Burden of disease scenarios for 204 countries and territories, 2022-2050: a forecasting analysis for the Global Burden of Disease Study 2021

Author: Vollset, SE, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbastabar, H, Abd Al Magied, AHA, Abd ElHafeez, S, Abdelkader, A, Abdelmasseh, M, Abd-Elsalam, S, Abdi, P, Abdollahi, M, Abdoun, M, Abdullahi, A, Abebe, M, Abiodun, O, Aboagye, RG, Abolhassani, H, Abouzid, M, Aboye, GB, Abreu, LG, Absalan, A, Abualruz, H, Abubakar, B, Abukhadijah, HJJ, Addolorato, G, Adekanmbi, V, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adha, R, Adhikary, RK, Adnani, QES, Adzigbli, LA, Afrashteh, F, Afzal, MS, Afzal, S, Agbozo, F, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahlstrom, AJ, Ahmad, A, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmed, A, Ahmed, H, Ahmed, S, Ahmed, SA, Akinosoglou, K, Akkaif, MA, Akrami, AE, Akter, E, Al Awaidy, S, Al Hasan, SM, Al Mosa, AS, Al Ta'ani, O, Al Zaabi, OAM, Alahdab, F, Alajlani, MM, Al-Ajlouni, Y, Alalalmeh, SO, Al-Aly, Z, Alam, K, Alam, N, Alam, T, Alam, Z, Al-Amer, RM, Alanezi, FM, Alanzi, TM, Albakri, A, Aldhaleei, WA, Aldridge, RW, Alemohammad, SY, Alemu, YM, Al-Gheethi, AAS, Al-Hanawi, MK, Ali, A, Ali, I, Ali, MU, Ali, R, Ali, SSS, Ali, VE, Ali, W, Al-Ibraheem, A, Alicandro, G, Alif, SM, Aljunid, SM, Alla, F, Almazan, JU, Al-Mekhlafi, HM, Alqutaibi, AY, Alrawashdeh, A, Alrousan, SM, Al-Sabah, SK, Alsabri, MA, Altaany, Z, Al-Tammemi, AB, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Al-Wardat, MS, Al-Worafi, YM, Aly, H, Alyahya, MS, Alzoubi, KH, Al-Zyoud, W, Amani, R, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Andrews, EA, Anil, A, Anil, S, Anoushiravani, A, Antony, CM, Antriyandarti, E, Anuoluwa, BS, Anvari, S, Anyasodor, AE, Appiah, F, Aquilano, M, Arab, JP, Arabloo, J, Arafa, EA, Arafat, M, Aravkin, AY, Ardekani, A, Areda, D, Aregawi, BB, Aremu, A, Ariffin, H, Arkew, M, Armani, K, Artamonov, AA, Arumugam, A, Asghari-Jafarabadi, M, Ashbaugh, C, Astell-Burt, T, Athari, SS, Atorkey, P, Atout, MMW, Aujayeb, A, Ausloos, M, Awad, H, Awotidebe, AW, Ayatollahi, H, Ayuso-Mateos, JL, Azadnajafabad, S, Azeez, FK, Azevedo, RMS, Badar, M, Baghdadi, S, Bagheri, M, Bagheri, N, Bai, R, Baker, JL, Bako, AT, Balakrishnan, S, Balcha, WF, Baltatu, OC, Barchitta, M, Bardideh, E, Barker-Collo, SL, Barnighausen, TW, Barqawi, HJ, Barteit, S, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Bauckneht, M, Baune, BT, Bayati, M, Bayileyegn, NS, Behnoush, AH, Behzadi, P, Beiranvand, M, Bello, OO, Belo, L, Beloukas, A, Bemanalizadeh, M, Bensenor, IM, Benzian, H, Beran, A, Berezvai, Z, Bernstein, RS, Bettencourt, PJG, Beyene, KA, Beyene, MG, Bhagat, DS, Bhagavathula, AS, Bhala, N, Bhandari, D, Bharadwaj, R, Bhardwaj, N, Bhardwaj, P, Bhargava, A, Bhaskar, S, Bhat, V, Bhattacharjee, NV, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhuiyan, MA, Bisignano, C, Biswas, B, Bjorge, T, Bodolica, V, Bodunrin, AO, Hashemi, MB, Basara, BB, Borhany, H, Bosoka, SA, Carvajal, AB, Bouaoud, S, Boufous, S, Boxe, C, Boyko, EJ, Brady, OJ, Braithwaite, D, Brauer, M, Brazo-Sayavera, J, Brenner, H, Brown, CS, Browne, AJ, Brugha, T, Bryazka, D, Bulamu, NB, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, ZA, dos Santos, FLC, Barsbay, MC, Calina, D, Campos, LA, Cao, S, Capodici, A, Cardenas, R, Carreras, G, Carugno, A, Carvalho, M, Castaldelli-Maia, JM, Castelpietra, G, Cattaruzza, MS, Caye, A, Cegolon, L, Cembranel, F, Cenko, E, Cerin, E, Chadban, SJ, Chadwick, J, Chakraborty, C, Chakraborty, S, Chalek, J, Chan, JSK, Chandika, RM, Chandy, S, Charan, J, Chaudhary, AA, Chaurasia, A, Chen, A-T, Chen, H, Chen, MX, Chen, S, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, DY, Cho, WCS, Choi, D-W, Chong, B, Chong, CL, Chopra, H, Chu, D-T, Chung, E, Chutiyami, M, Clayton, JT, Cogen, RM, Cohen, AJ, Columbus, A, Comfort, H, Conde, J, Connolly, JT, Cooper, EEK, Cortese, S, Cruz-Martins, N, da Silva, AG, Dadras, O, Dai, X, Dai, Z, Dalton, BE, Damiani, G, Dandona, L, Dandona, R, Das, JK, Das, S, Dash, NR, Davletov, K, De la Hoz, FP, De Leo, D, Debopadhaya, S, Delgado-Enciso, I, Denova-Gutierrez, E, Dervenis, N, Desai, HD, Devanbu, VGC, Dewan, SMR, Dhama, K, Dhane, AS, Dhingra, S, da Silva, DD, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Do, THP, Do Prado, CB, Dodangeh, M, Doegah, PT, Dohare, S, Dong, W, D'Oria, M, Doshi, R, Dowou, RK, Dsouza, HL, Dsouza, V, Dube, J, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Durojaiye, OC, Dushpanova, A, Dutta, S, Dzianach, PA, Dziedzic, AM, Eboreime, E, Ebrahimi, A, Kalan, ME, Edinur, HA, Efendi, F, Eikemo, TA, Eini, E, Ekundayo, TC, El Arab, RA, El Sayed, I, Elamin, O, Elemam, NM, ElGohary, GMT, Elhadi, M, Elmeligy, OAA, Elmoselhi, AB, Elshaer, M, Elsohaby, I, Eltahir, ME, Emeto, TI, Eshrati, B, Eslami, M, Esmaeili, Z, Fabin, N, Fagbamigbe, AF, Fagbule, OF, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faro, A, Fasihi, K, Fatehizadeh, A, Fauk, NK, Fazylov, T, Feigin, VL, Fekadu, G, Feng, X, Fereshtehnejad, S-M, Ferrara, P, Ferreira, N, Firew, BS, Fischer, F, Fitriana, I, Flavel, J, Flor, LS, Folayan, MO, Foley, KM, Fonzo, M, Force, LM, Foschi, M, Freitas, A, Fridayani, NKY, Fukutaki, KG, Furtado, JM, Fux, B, Gaal, PA, Gadanya, MA, Gallus, S, Ganesan, B, Ganiyani, MA, Gautam, RK, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Getacher, L, Getahun, GKA, Gething, PW, Ghadimi, DJ, Ghadirian, F, Ghafarian, S, Ghailan, KY, Ghasemi, M, Dabaghi, GG, Ghazy, RM, Ghoba, S, Gholami, E, Gholamrezanezhad, A, Gholizadeh, N, Ghorbani, M, Vajargah, PG, Ghotbi, E, Gil, AU, Gill, TK, Girmay, A, Glasbey, JC, Glushkova, EV, Gnedovskaya, EV, Gobolos, L, Goldust, M, Goleij, P, Golinelli, D, Gopalani, SV, Goulart, AC, Gouravani, M, Goyal, A, Grivna, M, Grosso, G, Guarducci, G, Gubari, MIM, Guicciardi, S, Guimaraes, RA, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, R, Gupta, S, Gupta, VK, Haakenstad, A, Hadi, NR, Haep, N, Hafiz, A, Haghmorad, D, Haile, D, Ali, AH, Ali, HA, Haj-Mirzaian, A, Halboub, ES, Haller, S, Halwani, R, Abdullah, KH, Hamdy, NM, Hamoudi, R, Hanifi, N, Hankey, GJ, Haq, ZA, Haque, MR, Harapan, H, Hargono, A, Haro, JM, Hasaballah, AI, Hasan, SMM, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Hay, SI, Hebert, JJ, Hegazi, OE, Heidari, M, Hemmati, M, Henson, CA, Herrera-Serna, BY, Herteliu, C, Heydari, M, Hezam, K, Hidayana, I, Hiraike, Y, Hoan, NQ, Holla, R, Hoogar, P, Horita, N, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hu, C, Huang, J, Hultstrom, M, Hundie, TG, Hunt, AJ, Hushmandi, K, Hussain, J, Hussain, MA, Hussein, NR, Huynh, H-H, Hwang, B-F, Ibitoye, SE, Iftikhar, PM, Ikiroma, AI, Ikwegbue, PC, Ilic, IM, Ilic, MD, Immurana, M, Isa, MA, Islam, MR, Islam, SMS, Ismail, F, Ismail, NE, Isola, G, Iwagami, M, Iyamu, IO, Jacob, L, Jacobsen, KH, Jafarinia, M, Jahankhani, K, Jahanmehr, N, Jain, N, Jairoun, AA, Mani, DRJ, Jamil, S, Jamora, RDG, Jatau, AI, Javadov, S, Javaheri, T, Jayaram, S, Jee, SH, Jeganathan, J, Jiang, H, Jokar, M, Jonas, JB, Joseph, N, Joshua, CE, Jurisson, M, Vaishali, K, Kabir, A, Kabir, Z, Kadashetti, V, Kalankesh, LR, Kalra, S, Kamath, A, Kamath, R, Kamireddy, A, Kanaan, M, Kanchan, T, Kanmiki, EW, Kanmodi, KK, Kansal, SK, Karim, A, Karkhah, S, Kashoo, FZ, Kasraei, H, Kassel, MB, Katikireddi, SV, Kauppila, JH, Kaur, H, Kayode, GA, Kazemi, F, Kazemian, S, Kebede, F, Kendal, ES, Kesse-Guyot, E, Khademvatan, S, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Khan, F, Khan, MJ, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatatbeh, H, Khatatbeh, MM, Khatib, MN, Kashani, HRK, Kheirallah, KA, Khokhar, M, Khormali, M, Khorrami, Z, Khosla, AA, Khosravi, M, Khosrowjerdi, M, Khubchandani, J, Kifle, ZD, Kim, G, Kim, JS, Kim, MS, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Knibbs, LD, Knudsen, AKS, Kochhar, S, Kolahi, A-A, Kompani, F, Koren, G, Korzh, O, Krishan, K, Krishna, V, Krishnamoorthy, V, Bicer, BK, Kuddus, MA, Kuddus, M, Kuitunen, I, Kujan, O, Kulimbet, M, Kulkarni, V, Kumar, GA, Kumar, H, Kumar, N, Kumar, R, Kumar, V, Kundu, A, Kusuma, D, Kyei-Arthur, F, Kyto, V, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lahariya, C, Lai, DTC, Lalloo, R, Lallukka, T, Lam, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Lansingh, VC, Laplante-Levesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Lawlor, HR, Le, H-H, Le, LKD, Le, NHH, Le, TTT, Le, TDT, Leasher, JL, Lee, DW, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, SWH, Lee, YH, Leigh, J, Leong, E, Li, M-C, Libra, M, Ligade, VS, Lim, L-L, Lim, SS, Limenh, LW, Lindholm, D, Lindstedt, PA, Listl, S, Liu, G, Liu, S, Liu, X, Llanaj, E, Lopez-Bueno, R, Lopez-Gil, JF, Loreche, AM, Lotufo, PA, Lozano, R, Lubinda, J, Lucchetti, G, Luo, L, Lusk, JB, Lv, L, Amin, HIM, Ma, ZF, Maass, KL, Machairas, N, Machoy, M, Madureira-Carvalho, AM, Abd El Razek, HM, Maghazachi, AA, Prasad, DRM, Mahalleh, M, Mahasha, PW, Mahmoud, MA, Mahmoudi, E, Mahmoudvand, G, Makama, M, Rad, EM, Malhotra, K, Malik, AA, Malta, DC, Manla, Y, Mansour, A, Mansouri, MH, Mansouri, P, Mansouri, V, Mansourian, M, Mansournia, MA, Marasini, BP, Marateb, HR, Maravilla, JC, Mardi, P, Marjani, A, Moghadam, HM, Arnedo, CAM, Martinez, G, Martinez-Piedra, R, Martins-Melo, FR, Martorell, M, Marx, W, Marzo, RR, Masoudi, S, Mathangasinghe, Y, Mathioudakis, AG, Mathur, M, Mathur, N, Matozinhos, FP, Mattumpuram, J, Maude, RJ, Maugeri, A, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, Mckee, M, McKowen, ALW, McPhail, MA, McPhail, SM, Mehmood, A, Mehrabani-Zeinabad, K, Mehravar, S, Meto, TM, Melese, EB, Mendez-Lopez, MAM, Mendoza, W, Menezes, RG, Mensah, GA, Mensah, LG, Mentis, A-FA, Meo, SA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mestrovic, T, Mettananda, KCD, Mettananda, S, Mhlanga, A, Mhlanga, L, Miazgowski, T, Michalek, IM, de Sa, ACMGN, Miller, TR, Minh, LHN, Mirahmadi, A, Mirijello, A, Mirrakhimov, EM, Mirzaei, R, Mitchell, PB, Mittal, C, Moberg, ME, Fard, AM, Mohajelin, S, Mohamadkhani, A, Mohamed, AI, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammad, AM, Mohammadi, S, Mohammed, H, Mohammed, M, Mohammed, S, Mokdad, AH, Molokhia, M, Momani, SM, Momtazmanesh, S, Monasta, L, Mondello, S, Moni, MA, Montazeri, F, Ghalibaf, AM, Moradi, M, Moradi, Y, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Mosapour, A, Mosser, JF, Mossialos, E, Motappa, R, Mougin, V, Mousavi, P, Mrejen, M, Mubarik, S, Mueller, UO, Mulita, F, Munjal, K, Murillo-Zamora, E, Musallam, KM, Musina, A-M, Mustafa, G, Myung, W, Nafei, A, Nagarajan, AJ, Naghavi, P, Naik, GR, Naik, G, Nainu, F, Najdaghi, S, Ansari, NN, Nangia, V, Swamy, SN, Nargus, S, Davani, DN, Nascimento, BR, Nascimento, GG, Naser, AY, Nashwan, AJ, Natto, ZS, Nauman, J, Navaratna, SNK, Naveed, M, Nawsherwan, Nayak, BP, Nayak, VC, Negash, H, Negoi, I, Negoi, RI, Nejadghaderi, SA, Nejjari, C, Nematollahi, S, Netsere, HB, Ng, M, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, AH, Nguyen, DH, Nguyen, HTH, Nguyen, N, Nguyen, NNY, Nguyen, PT, Nguyen, QP, Nguyen, VT, Minh, DNT, Niazi, RK, Nigatu, YT, Niknam, M, Nikoobar, A, Nikpoor, AR, Nikravangolsefid, N, Noman, EA, Nomura, S, Noor, STA, Noroozi, N, Nouri, M, Nozari, M, Nri-Ezedi, CA, Ntaios, G, Nunemo, MH, Nurrika, D, Nutor, JJ, Nzoputam, CI, Nzoputam, OJ, Oancea, B, Obamiro, KO, Odetokun, IA, Oduro, MS, Ogundijo, OA, Ogunfowokan, AA, Ogunkoya, A, Oguntade, AS, Oh, I-H, Ojo-Akosile, TR, Okati-Aliabad, H, Okekunle, AP, Okonji, OC, Olagunju, AT, Olatubi, MI, Oliveira, GMM, Olusanya, BO, Olusanya, JO, Oluwafemi, YD, Omar, HA, Omer, GL, Ong, S, Onie, S, Onwujekwe, OE, Opejin, AO, Ordak, M, Orish, VN, Ortiz, A, Ortiz-Prado, E, Osman, WMS, Ostojic, SM, Ostroff, SM, Osuagwu, UL, Otoiu, A, Otstavnov, SS, Ouyahia, A, Owolabi, MO, Oyeyemi, OT, Ozair, A, Padukudru, MPA, Padron-Monedero, A, Padubidri, JR, Pal, PK, Palicz, T, Pan, F, Pan, H-F, Panda-Jonas, S, Pandey, A, Pando-Robles, V, Pangaribuan, HU, Panos, GD, Panos, LD, Pantazopoulos, I, Stoian, AMP, Parikh, RR, Park, E-K, Park, S, Parsons, N, Parthasarathi, A, Pasovic, M, Passera, R, Patel, J, Pathan, AR, Patil, S, Patoulias, D, Pawar, S, Toroudi, HP, Pease, SA, Peden, AE, Pedersini, P, Pensato, U, Pepito, VCF, Peprah, P, Pereira, M, Pereira, MO, Perianayagam, A, Perico, N, Perna, S, Pesudovs, K, Petermann-Rocha, FE, Pham, HT, Philip, AK, Phillips, MR, Pigeolet, M, Piradov, MA, Pisoni, E, Plotnikov, E, Poddighe, D, Polibin, RV, Poluru, R, Ponkilainen, VT, Popovic, DS, Postma, MJ, Pour-Rashidi, A, Prabhu, D, Prada, SI, Pradhan, J, Pradhan, PMS, Prashant, A, Prates, EJS, Priscilla, T, Purnobasuki, H, Purohit, BM, Puvvula, J, Qasim, NH, Qattea, I, Qazi, AS, Qian, G, Rad, MR, Radhakrishnan, V, Shahraki, HR, Rafferty, Q, Raggi, A, Raggi, C, Raheem, N, Rahim, F, Rahim, MJ, Rahimibarghani, S, Rahman, MMMR, Rahman, M, Rahman, MA, Rahman, T, Rahmani, AM, Rahmanian, M, Rahmanian, N, Rahmati, R, Rahmawaty, S, Raimondo, D, Raja, A, Rajput, P, Ramadan, M, Ramasamy, SK, Ramazanu, 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Abstract: BACKGROUND: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. METHODS: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects m
Published: 2024

3. Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Brauer, M, Roth, GA, Aravkin, AY, Zheng, P, Abate, KH, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasi, MA, Abbasian, M, Abbasifard, M, Moradi, Y, Bensenor, IM, Benzian, H, Beran, A, Abouzid, M, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Moraga, P, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Aboye, GB, Bhat, AN, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Morawska, L, Bhatti, R, Bhuiyan, MA, Bhutta, ZA, Bikbov, B, Bishai, JD, Abreu, LG, Bisignano, C, Biswas, A, Biswas, B, Biswas, RK, Moreira, RS, Bjørge, T, Boachie, MK, Boakye, H, Bockarie, MJ, Bodolica, V, Bodunrin, AO, Abualruz, H, Bogale, EK, Bolla, SR, Boloor, A, Morovatdar, N, Bonakdar Hashemi, M, Boppana, SH, Bora Basara, B, Borhany, H, Botero Carvajal, A, Bouaoud, S, Boufous, S, Abubakar, B, Bourne, R, Boxe, C, Morrison, SD, Braithwaite, D, Brant, LC, Brar, A, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Britton, G, Abu-Gharbieh, E, Brown, CS, Morze, J, Browne, AJ, Brunoni, AR, Bryazka, D, Bulamu, NB, Bulto, LN, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Abukhadijah, HJJ, Mosaddeghi Heris, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Cagney, J, Cahuana-Hurtado, L, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Mossialos, E, Aburuz, S, Cao, C, Cao, F, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Motappa, R, Carvalho, F, Abu-Zaid, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Caye, A, Alemayohu, MA, Ali, BA, Cederroth, CR, Cegolon, L, Adane, MM, Cenderadewi, M, Cercy, KM, Cerin, E, Chadwick, J, Chakraborty, C, Chakraborty, PA, Chakraborty, S, Mougin, V, Chan, JSK, Chan, RNC, Chandan, JS, Addo, IY, Chandika, RM, Chaturvedi, P, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Mousavi, P, Chen, M, Chen, S, Cheng, C-Y, Cheng, ETW, Addolorato, G, Cherbuin, N, Chi, G, Chichagi, F, Chimed-Ochir, O, Chimoriya, 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GS, Azizi, H, Abegaz, TM, Azzam, AY, Backhaus, IL, Mondello, S, Badar, M, Badiye, AD, Bagga, A, Baghdadi, S, Bagheri, N, Bagherieh, S, Bahrami Taghanaki, P, Bai, R, Abeldaño Zuñiga, RA, Baig, AA, Moni, MA, Baker, JL, Bakkannavar, SM, Balasubramanian, M, Baltatu, OC, Bam, K, Bandyopadhyay, S, Banik, B, Banik, PC, Banke-Thomas, A, Abiodun, O, Moodi Ghalibaf, A, Bansal, H, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Bärnighausen, TW, Barone-Adesi, F, Barqawi, HJ, Barrero, LH, Barrow, A, Moore, CE, Abiso, TL, Barteit, S, Basharat, Z, Basiru, A, Basso, JD, Bastan, M-M, Basu, S, Batchu, S, Batra, K, Batra, R, Moradi, M, Baune, BT, Aboagye, RG, Bayati, M, Bayileyegn, NS, Beaney, T, Behnoush, AH, Beiranvand, M, Béjot, Y, Bekele, A, Belgaumi, UI, Bell, AW, Bell, ML, Abolhassani, H, Bello, MB, Bello, OO, Belo, L, Beloukas, A, Bendak, S, Bennett, DA, and Bennitt, FB
Published: 2024

4. Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Naghavi, M, Ong, KL, Aali, A, Ababneh, HS, Abate, YH, Abbafati, C, Abbasgholizadeh, R, Abbasian, M, Abbasi-Kangevari, M, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdelwahab, A, Abdollahi, M, Abdollahifar, M-A, Abdoun, M, Abdulah, DM, Abdullahi, A, Abebe, M, Abebe, SS, Abedi, A, Abegaz, KH, Abhilash, ES, Abidi, H, Abiodun, O, Aboagye, RG, Abolhassani, H, Abolmaali, M, Abouzid, M, Aboye, GB, Abreu, LG, Abrha, WA, Abtahi, D, Abu Rumeileh, S, Abualruz, H, Abubakar, B, Abu-Gharbieh, E, Abu-Rmeileh, NME, Aburuz, S, Abu-Zaid, A, Accrombessi, MMK, Adal, TG, Adamu, AA, Addo, IY, Addolorato, G, Adebiyi, AO, Adekanmbi, V, Adepoju, AV, Adetunji, CO, Adetunji, JB, Adeyeoluwa, TE, Adeyinka, DA, Adeyomoye, OI, Admass, BAA, Adnani, QES, Adra, S, Afolabi, AA, Afzal, MS, Afzal, S, Agampodi, SB, Agasthi, P, Aggarwal, M, Aghamiri, S, Agide, FD, Agodi, A, Agrawal, A, Agyemang-Duah, W, Ahinkorah, BO, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, MM, Ahmad, S, Ahmad, T, Ahmadi, K, Ahmadzade, AM, Ahmed, A, Ahmed, H, Ahmed, LA, Ahmed, MS, Ahmed, MB, Ahmed, SA, Ajami, M, Aji, B, Akara, EM, Akbarialiabad, H, Akinosoglou, K, Akinyemiju, T, Akkaif, MA, Akyirem, S, Al Hamad, H, Al Hasan, SM, Alahdab, F, Alalalmeh, SO, Alalwan, TA, Al-Aly, Z, Alam, K, Alam, M, Alam, N, Al-amer, RM, Alanezi, FM, Alanzi, TM, Al-Azzam, S, Albakri, A, Albashtawy, M, AlBataineh, MT, Alcalde-Rabanal, JE, Aldawsari, KA, Aldhaleei, WA, Aldridge, RW, Alema, HB, Alemayohu, MA, Alemi, S, Alemu, YM, Al-Gheethi, AAS, Alhabib, KF, Alhalaiqa, FAN, Al-Hanawi, MK, Ali, A, Ali, L, Ali, MU, Ali, R, Ali, S, Ali, SSS, Alicandro, G, Alif, SM, Alikhani, R, Alimohamadi, Y, Aliyi, AA, Aljasir, MAM, Aljunid, SM, Alla, F, Allebeck, P, Al-Marwani, S, Al-Maweri, SAA, Almazan, JU, Al-Mekhlafi, HM, Almidani, L, Almidani, O, Alomari, MA, Al-Omari, B, Alonso, J, Alqahtani, JS, Alqalyoobi, S, Alqutaibi, AY, Al-Sabah, SK, Altaany, Z, Altaf, A, Al-Tawfiq, JA, Altirkawi, KA, Aluh, DO, Alvis-Guzman, N, Alwafi, H, Al-Worafi, YM, Aly, H, Aly, S, Alzoubi, KH, Amani, R, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amirzade-Iranaq, MH, Amu, H, Amugsi, DA, Amusa, GA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Andrei, T, Angus, C, Anil, A, Anil, S, Anoushiravani, A, Ansari, H, Ansariadi, A, Ansari-Moghaddam, A, Antony, CM, Antriyandarti, E, Anvari, D, Anvari, S, Anwar, S, Anwar, SL, Anwer, R, Anyasodor, AE, Aqeel, M, Arab, JP, Arabloo, J, Arafat, M, Aravkin, AY, Areda, D, Aremu, A, Aremu, O, Ariffin, H, Arkew, M, Armocida, B, Arndt, MB, Ärnlöv, J, Arooj, M, Artamonov, AA, Arulappan, J, Aruleba, RT, Arumugam, A, Asaad, M, Asadi-Lari, M, Asgedom, AA, Asghariahmadabad, M, Asghari-Jafarabadi, M, Ashraf, M, Aslani, A, Astell-Burt, T, Athar, M, Athari, SS, Atinafu, BTT, Atlaw, HW, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awedew, AF, Aweke, AM, Ayala Quintanilla, BP, Ayatollahi, H, Ayuso-Mateos, JL, Ayyoubzadeh, SM, Azadnajafabad, S, 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Bhagavathula, AS, Bhala, N, Bhalla, A, Bhandari, D, Bhangdia, K, Bhardwaj, N, Bhardwaj, P, Bhardwaj, PV, Bhargava, A, Bhaskar, S, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Bisulli, F, Biswas, A, Biswas, B, Bitaraf, S, Bitew, BD, Bitra, VR, Bjørge, T, Boachie, MK, Boampong, MS, Bobirca, AV, Bodolica, V, Bodunrin, AO, Bogale, EK, Bogale, KA, Bohlouli, S, Bolarinwa, OA, Boloor, A, Bonakdar Hashemi, M, Bonny, A, Bora, K, Bora Basara, B, Borhany, H, Borzutzky, A, Bouaoud, S, Boustany, A, Boxe, C, Boyko, EJ, Brady, OJ, Braithwaite, D, Brant, LC, Brauer, M, Brazinova, A, Brazo-Sayavera, J, Breitborde, NJK, Breitner, S, Brenner, H, Briko, AN, Briko, NI, Britton, G, Brown, J, Brugha, T, Bulamu, NB, Bulto, LN, Buonsenso, D, Burns, RA, Busse, R, Bustanji, Y, Butt, NS, Butt, ZA, Caetano dos Santos, FL, Calina, D, Cámera, LA, Campos, LA, Campos-Nonato, IR, Cao, C, Cao, Y, Capodici, A, Cárdenas, R, Carr, S, Carreras, G, Carrero, JJ, Carugno, A, Carvalheiro, CG, Carvalho, F, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Catapano, AL, Cattaruzza, MS, Cederroth, CR, Cegolon, L, Cembranel, F, Cenderadewi, M, Cercy, KM, Cerin, E, Cevik, M, Chadwick, J, Chahine, Y, Chakraborty, C, Chakraborty, PA, Chan, JSK, Chan, RNC, Chandika, RM, Chandrasekar, EK, Chang, C-K, Chang, J-C, Chanie, GS, Charalampous, P, Chattu, VK, Chaturvedi, P, Chatzimavridou-Grigoriadou, V, Chaurasia, A, Chen, AW, Chen, A-T, Chen, CS, Chen, H, Chen, MX, Chen, S, Cheng, C-Y, Cheng, ETW, Cherbuin, N, Cheru, WA, Chien, J-H, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Chirinos-Caceres, JL, Chitheer, A, Cho, WCS, Chong, B, Chopra, H, Choudhari, SG, Chowdhury, R, Christopher, DJ, Chukwu, IS, Chung, E, Chung, S-C, Chutiyami, M, Cindi, Z, Cioffi, I, Claassens, MM, Claro, RM, Coberly, K, Cogen, RM, Columbus, A, Comfort, H, Conde, J, Cortese, S, Cortesi, PA, Costa, VM, Costanzo, S, Cousin, E, Couto, RAS, Cowden, RG, Cramer, KM, Criqui, MH, Cruz-Martins, N, Cuadra-Hernández, SM, Culbreth, GT, Cullen, P, Cunningham, M, Curado, MP, Dadana, S, Dadras, O, Dai, S, Dai, X, Dai, Z, Dalli, LL, Damiani, G, Darega Gela, J, Das, JK, Das, S, Dascalu, AM, Dash, NR, Dashti, M, Dastiridou, A, Davey, G, Dávila-Cervantes, CA, Davis Weaver, N, Davletov, K, De Leo, D, de Luca, K, Debele, AT, Debopadhaya, S, Degenhardt, L, Dehghan, A, Deitesfeld, L, Del Bo', C, Delgado-Enciso, I, Demessa, BH, Demetriades, AK, Deng, K, Deng, X, Denova-Gutiérrez, E, Deravi, N, Dereje, N, Dervenis, N, Dervišević, E, Des Jarlais, DC, Desai, HD, Desai, R, Devanbu, VGC, Dewan, SMR, Dhali, A, Dhama, K, Dhimal, M, Dhingra, S, Dhulipala, VR, Dias da Silva, D, Diaz, D, Diaz, MJ, Dima, A, Ding, DD, Ding, H, Dinis-Oliveira, RJ, Dirac, MA, Djalalinia, S, Do, THP, do Prado, CB, Doaei, S, Dodangeh, M, Dohare, S, Dokova, KG, Dolecek, C, Dominguez, R-MV, Dong, W, Dongarwar, D, D'Oria, M, Dorostkar, F, Dorsey, ER, dos Santos, WM, Doshi, R, 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Zhu, L, Ziafati, M, Zielińska, M, Zitoun, OA, Zoladl, M, Zou, Z, Zuhlke, LJ, Zumla, A, Zweck, E, Zyoud, SH, Wool, EE, and Murray, CJL
Published: 2024

5. Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Author: Ferrari, AJ, Santomauro, DF, Aali, A, Abate, YH, Abbafati, C, Abbastabar, H, Abd ElHafeez, S, Abdelmasseh, M, Abd-Elsalam, S, Abdollahi, A, Abdullahi, A, Abegaz, KH, Abeldaño Zuñiga, RA, Aboagye, RG, Abolhassani, H, Abreu, LG, Abualruz, H, Abu-Gharbieh, E, Abu-Rmeileh, NME, Ackerman, IN, Addo, IY, Addolorato, G, Adebiyi, AO, Adepoju, AV, Adewuyi, HO, Afyouni, S, Afzal, S, Agodi, A, Ahmad, A, Ahmad, D, Ahmad, F, Ahmad, S, Ahmed, A, Ahmed, LA, Ahmed, MB, Ajami, M, Akinosoglou, K, Akkaif, MA, Al Hasan, SM, Alalalmeh, SO, Al-Aly, Z, Albashtawy, M, Aldridge, RW, Alemu, MD, Alemu, YM, Alene, KA, Al-Gheethi, AAS, Alharrasi, M, Alhassan, RK, Ali, MU, Ali, R, Ali, SSS, Alif, SM, Aljunid, SM, Al-Marwani, S, Almazan, JU, Alomari, MA, Al-Omari, B, Altaany, Z, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Alwafi, H, Al-Wardat, MS, Al-Worafi, YM, Aly, S, Alzoubi, KH, Amare, AT, Amegbor, PM, Ameyaw, EK, Amin, TT, Amindarolzarbi, A, Amiri, S, Amugsi, DA, Ancuceanu, R, Anderlini, D, Anderson, DB, Andrade, PP, Andrei, CL, Ansari, H, Antony, CM, Anwar, S, Anwar, SL, Anwer, R, Anyanwu, PE, Arab, JP, Arabloo, J, Arafat, M, Araki, DT, Aravkin, AY, Arkew, M, Armocida, B, Arndt, MB, Arooj, M, Artamonov, AA, Aruleba, RT, Arumugam, A, Ashbaugh, C, Ashemo, MY, Ashraf, M, Asika, MO, Askari, E, Astell-Burt, T, Athari, SS, Atorkey, P, Atout, MMW, Atreya, A, Aujayeb, A, Ausloos, M, Avan, A, Awotidebe, AW, Awuviry-Newton, K, Ayala Quintanilla, BP, Ayuso-Mateos, JL, Azadnajafabad, S, Azevedo, RMS, Babu, AS, Badar, M, Badiye, AD, Baghdadi, S, Bagheri, N, Bah, S, Bai, R, Baker, JL, Bakkannavar, SM, Bako, AT, Balakrishnan, S, Bam, K, Banik, PC, Barchitta, M, Bardhan, M, Bardideh, E, Barker-Collo, SL, Barqawi, HJ, Barrow, A, Barteit, S, Barua, L, Bashiri Aliabadi, S, Basiru, A, Basu, S, Bathini, PP, Batra, K, Baune, BT, Bayileyegn, NS, Behnam, B, Behnoush, AH, Beiranvand, M, Bejarano Ramirez, DF, Bell, ML, Bello, OO, Beloukas, A, Bensenor, IM, Berezvai, Z, Bernabe, E, Bernstein, RS, Bettencourt, PJG, Bhagavathula, AS, Bhala, N, Bhandari, D, Bhargava, A, Bhaskar, S, Bhat, V, Bhatti, GK, Bhatti, JS, Bhatti, MS, Bhatti, R, Bhutta, ZA, Bikbov, B, Bishai, JD, Bisignano, C, Bitra, VR, Bjørge, T, Bodolica, V, Bodunrin, AO, Bogale, EK, Bonakdar Hashemi, M, Bonny, A, Bora Basara, B, Borhany, H, Boxe, C, Brady, OJ, Bragazzi, NL, Braithwaite, D, Brant, LC, Brauer, M, Breitner, S, Brenner, H, Brown, J, Brugha, T, Bulamu, NB, Buonsenso, D, Burkart, K, Burns, RA, Busse, R, Bustanji, Y, Butt, ZA, Byun, J, Caetano dos Santos, FL, Calina, D, Cámera, LA, Campos-Nonato, IR, Cao, C, Capodici, A, Carr, S, Carreras, G, Carugno, A, Carvalho, M, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catapano, AL, Cattaruzza, MS, Caye, A, Cegolon, L, Cembranel, F, Cenderadewi, M, Cerin, E, Chakraborty, PA, Chan, JSK, Chan, RNC, Chandika, RM, Chandrasekar, EK, Charalampous, P, Chattu, VK, Chatzimavridou-Grigoriadou, V, Chen, AW, Chen, A-T, Chen, CS, Chen, H, Chen, NM, Cheng, ETW, Chimed-Ochir, O, Chimoriya, R, Ching, PR, Cho, WCS, Choi, S, Chong, B, Chong, YY, Choudhari, SG, Chowdhury, R, Christensen, SWM, Chu, D-T, Chukwu, IS, Chung, E, Chutiyami, M, Claassens, MM, Cogen, RM, Columbus, A, Conde, J, Cortesi, PA, Cousin, E, Criqui, MH, Cruz-Martins, N, Dadras, O, Dai, S, Dai, X, Dai, Z, Dalaba, MA, Damiani, G, Das, JK, Das, S, Dashti, M, Dávila-Cervantes, CA, Davletov, K, De Leo, D, Debele, AT, Debopadhaya, S, DeCleene, NK, Deeba, F, Degenhardt, L, Del Bo', C, Delgado-Enciso, I, Demetriades, AK, Denova-Gutiérrez, E, Dervenis, N, Desai, HD, Desai, R, Deuba, K, Dhama, K, Dharmaratne, SD, Dhingra, S, Dias da Silva, D, Diaz, D, Diaz, LA, Diaz, MJ, Dima, A, Ding, DD, Dirac, MA, Do, THP, do Prado, CB, Dohare, S, Dominguez, R-MV, Dong, W, Dongarwar, D, D'Oria, M, Dorsey, ER, Doshmangir, L, Dowou, RK, Driscoll, TR, Dsouza, HL, Dsouza, V, Dube, J, Dumith, SC, Duncan, BB, Duraes, AR, Duraisamy, S, Durojaiye, OC, Dzianach, PA, Dziedzic, AM, Eboreime, E, Ebrahimi, A, Edinur, HA, Edvardsson, D, Eikemo, TA, Eini, E, Ekholuenetale, M, Ekundayo, TC, El Sayed, I, El Tantawi, M, Elbarazi, I, Elemam, NM, ElGohary, GMT, Elhadi, M, Elmeligy, OAA, ELNahas, G, Elshaer, M, Elsohaby, I, Engelbert Bain, L, Erkhembayar, R, Eshrati, B, Estep, K, Fabin, N, Fagbamigbe, AF, Falzone, L, Fareed, M, Farinha, CSES, Faris, MEM, Faro, A, Farrokhi, P, Fatehizadeh, A, Fauk, NK, Feigin, VL, Feng, X, Fereshtehnejad, S-M, Feroze, AH, Ferreira, N, Ferreira, PH, Fischer, F, Flavel, J, Flood, D, Flor, LS, Foigt, NA, Folayan, MO, Force, LM, Fortuna, D, Foschi, M, Franklin, RC, Freitas, A, Fukumoto, T, Furtado, JM, Gaal, PA, Gadanya, MA, Gaidhane, AM, Gaihre, S, Galali, Y, Ganbat, M, Gandhi, AP, Ganesan, B, Ganie, MA, Ganiyani, MA, Gardner, WM, Gebi, TG, Gebregergis, MW, Gebrehiwot, M, Gebremariam, TBB, Gebremeskel, TG, Gela, YY, Georgescu, SR, Getachew Obsa, A, Gething, PW, Getie, M, Ghadiri, K, Ghadirian, F, Ghailan, KY, Ghajar, A, Ghasemi, M, Ghasempour Dabaghi, G, Ghasemzadeh, A, Ghazy, RM, Gholamrezanezhad, A, Ghorbani, M, Ghotbi, E, Gibson, RM, Gill, TK, Ginindza, TG, Girmay, A, Glasbey, JC, Göbölös, L, Godinho, MA, Goharinezhad, S, Goldust, M, Golechha, M, Goleij, P, Gona, PN, Gorini, G, Goulart, AC, Grada, A, Grivna, M, Guan, S-Y, Guarducci, G, Gubari, MIM, Gudeta, MD, Guha, A, Guicciardi, S, Gulati, S, Gulisashvili, D, Gunawardane, DA, Guo, C, Gupta, AK, Gupta, B, Gupta, I, Gupta, M, Gupta, R, Gupta, VB, Gupta, VK, Gutiérrez, RA, Habibzadeh, F, Habibzadeh, P, Haddadi, R, Hadi, NR, Haep, N, Hafezi-Nejad, N, Hafiz, A, Hagins, H, Halboub, ES, Halimi, A, Haller, S, Halwani, R, Hamilton, EB, Hankey, GJ, Hannan, MA, Haque, MN, Harapan, H, Haro, JM, Hartvigsen, J, Hasaballah, AI, Hasan, I, Hasanian, M, Hasnain, MS, Hassan, A, Haubold, J, Havmoeller, RJ, Hay, SI, Hayat, K, Hebert, JJ, Hegazi, OE, Heidari, G, Helfer, B, Hemmati, M, Hendrie, D, Henson, CA, Hezam, K, Hiraike, Y, Hoan, NQ, Holla, R, Hon, J, Hossain, MM, Hosseinzadeh, H, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Hsu, JM, Huang, J, Hugo, FN, Hushmandi, K, Hussain, J, Hussein, NR, Huynh, CK, Huynh, H-H, Hwang, B-F, Iannucci, VC, Ihler, AL, Ikiroma, AI, Ikuta, KS, Ilesanmi, OS, Ilic, IM, Ilic, MD, Imam, MT, Immurana, M, Irham, LM, Islam, MR, Islam, SMS, Islami, F, Ismail, F, Ismail, NE, Isola, G, Iwagami, M, Iwu, CCD, Iyer, M, Jaafari, J, Jacobsen, KH, Jadidi-Niaragh, F, Jafarinia, M, Jaggi, K, Jahankhani, K, Jahanmehr, N, Jahrami, H, Jain, A, Jain, N, Jairoun, AA, Jaiswal, A, Jakovljevic, M, Jatau, AI, Javadov, S, Javaheri, T, Jayapal, SK, Jayaram, S, Jee, SH, Jeganathan, J, Jeyakumar, A, Jha, AK, Jiang, H, Jin, Y, Jonas, JB, Joo, T, Joseph, A, Joseph, N, Joshua, CE, Jozwiak, JJ, Jürisson, M, K, V, Kaambwa, B, Kabir, A, Kabir, Z, Kadashetti, V, Kalani, R, Kalankesh, LR, Kaliyadan, F, Kalra, S, Kamenov, K, Kamyari, N, Kanagasabai, T, Kandel, H, Kanmanthareddy, AR, Kanmodi, KK, Kantar, RS, Karaye, IM, Karim, A, Karimi, SE, Karimi, Y, Kasraei, H, Kassel, MB, Kauppila, JH, Kawakami, N, Kayode, GA, Kazemi, F, Kazemian, S, Keikavoosi-Arani, L, Keller, C, Kempen, JH, Kerr, JA, Keshtkar, K, Kesse-Guyot, E, Keykhaei, M, Khajuria, H, Khalaji, A, Khalid, A, Khalid, N, Khalilian, A, Khamesipour, F, Khan, A, Khan, I, Khan, M, Khan, MAB, Khanmohammadi, S, Khatab, K, Khatami, F, Khatatbeh, MM, Khater, AM, Khayat Kashani, HR, Khidri, FF, Khodadoust, E, Khormali, M, Khorrami, Z, Kifle, ZD, Kim, MS, Kimokoti, RW, Kisa, A, Kisa, S, Knudsen, AKS, Kocarnik, JM, Kochhar, S, Koh, HY, Kolahi, A-A, Kompani, F, Koren, G, Korzh, O, Kosen, S, Koulmane Laxminarayana, SL, Krishan, K, Krishna, V, Krishnamoorthy, V, Kuate Defo, B, Kuddus, MA, Kuddus, M, Kuitunen, I, Kulkarni, V, Kumar, M, Kumar, N, Kumar, R, Kurmi, OP, Kusuma, D, Kyu, HH, La Vecchia, C, Lacey, B, Ladan, MA, Laflamme, L, Lafranconi, A, Lahariya, C, Lai, DTC, Lal, DK, Lalloo, R, Lallukka, T, Lám, J, Lan, Q, Lan, T, Landires, I, Lanfranchi, F, Langguth, B, Laplante-Lévesque, A, Larijani, B, Larsson, AO, Lasrado, S, Lauriola, P, Le, H-H, Le, LKD, Le, NHH, Le, TDT, Leasher, JL, Ledda, C, Lee, M, Lee, PH, Lee, S-W, Lee, SW, Lee, W-C, Lee, YH, LeGrand, KE, Lenzi, J, Leong, E, Leung, J, Li, M-C, Li, W, Li, X, Li, Y, Lim, L-L, Lim, SS, Lindstrom, M, Linn, S, Liu, G, Liu, R, Liu, S, Liu, W, Liu, X, Llanaj, E, Lo, C-H, López-Bueno, R, Loreche, AM, Lorenzovici, L, Lozano, R, Lubinda, J, Lucchetti, G, Lunevicius, R, Lusk, JB, lv, H, Ma, ZF, Machairas, N, Madureira-Carvalho, ÁM, Magaña Gómez, JA, Maghazachi, AA, Maharjan, P, Mahasha, PW, Maheri, M, Mahjoub, S, Mahmoud, MA, Mahmoudi, E, Majeed, A, Makris, KC, Malakan Rad, E, Malhotra, K, Malik, AA, Malik, I, Malta, DC, Manla, Y, Mansour, A, Mansouri, P, Mansournia, MA, Mantilla Herrera, AM, Mantovani, LG, Manu, E, Marateb, HR, Mardi, P, Martinez, G, Martinez-Piedra, R, Martini, D, Martins-Melo, FR, Martorell, M, Marx, W, Maryam, S, Marzo, RR, Mathangasinghe, Y, Mathieson, S, Mathioudakis, AG, Mattumpuram, J, Maugeri, A, Mayeli, M, Mazidi, M, Mazzotti, A, McGrath, JJ, McKee, M, McKowen, ALW, McPhail, MA, Mehrabani-Zeinabad, K, Mehrabi Nasab, E, Mekene Meto, T, Mendoza, W, Menezes, RG, Mensah, GA, Mentis, A-FA, Meo, SA, Meresa, HA, Meretoja, A, Meretoja, TJ, Mersha, AM, Mestrovic, T, Mettananda, KCD, Mettananda, S, Michalek, IM, Miller, PA, Miller, TR, Mills, EJ, Minh, LHN, Mirijello, A, Mirrakhimov, EM, Mirutse, MK, Mirza-Aghazadeh-Attari, M, Mirzaei, M, Mirzaei, R, Misganaw, A, Mishra, AK, Mitchell, PB, Mittal, C, Moazen, B, Moberg, ME, Mohamed, J, Mohamed, MFH, Mohamed, NS, Mohammadi, E, Mohammadi, S, Mohammed, H, Mohammed, S, Mohr, RM, Mokdad, AH, Molinaro, S, Momtazmanesh, S, Monasta, L, Mondello, S, Moodi Ghalibaf, A, Moradi, M, Moradi, Y, Moradi-Lakeh, M, Moraga, P, Morawska, L, Moreira, RS, Morovatdar, N, Morrison, SD, Morze, J, Mosapour, A, Mosser, JF, Mossialos, E, Motappa, R, Mougin, V, Mouodi, S, Mrejen, M, Msherghi, A, Mubarik, S, Mueller, UO, Mulita, F, Munjal, K, Murillo-Zamora, E, Murlimanju, BV, Mustafa, G, Muthu, S, Muzaffar, M, Myung, W, 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M, Shah, H, Shah, NS, Shah, PA, Shahbandi, A, Shahid, S, Shahid, W, Shahwan, MJ, Shaikh, MA, Shakeri, A, Shalash, AS, Sham, S, Shamim, MA, Shamshirgaran, MA, Shamsi, MA, Shanawaz, M, Shankar, A, Shannawaz, M, Sharath, M, Sharifan, A, Sharifi-Rad, J, Sharma, M, Sharma, R, Sharma, S, Sharma, U, Sharma, V, Shastry, RP, Shavandi, A, Shayan, AM, Shayan, M, Shehabeldine, AME, Shetty, PH, Shibuya, K, Shifa, JE, Shiferaw, D, Shiferaw, WS, Shigematsu, M, Shiri, R, Shitaye, NA, Shittu, A, Shivakumar, KM, Shivarov, V, Shokati Eshkiki, Z, Shool, S, Shrestha, S, Shuval, K, Sibhat, MM, Siddig, EE, Sigfusdottir, ID, Silva, DAS, Silva, JP, Silva, LMLR, Silva, S, Simpson, CR, Singal, A, Singh, A, Singh, BB, Singh, H, Singh, JA, Singh, M, Singh, P, Skou, ST, Sleet, DA, Slepak, ELN, Solanki, R, Soliman, SSM, Song, S, Song, Y, Sorensen, RJD, Soriano, JB, Soyiri, IN, Spartalis, M, Sreeramareddy, CT, Stark, BA, Starodubova, AV, Stein, C, Stein, DJ, Steiner, C, Steiner, TJ, Steinmetz, JD, Steiropoulos, P, Stockfelt, L, Stokes, MA, Subedi, NS, Subramaniyan, V, Suemoto, CK, Suleman, M, Suliankatchi Abdulkader, R, Sultana, A, Sundström, J, Swain, CK, Szarpak, L, Tabaee Damavandi, P, Tabarés-Seisdedos, R, Tabatabaei Malazy, O, Tabatabaeizadeh, S-A, Tabatabai, S, Tabche, C, Tabish, M, Tadakamadla, SK, Taheri Abkenar, Y, Taheri Soodejani, M, Taherkhani, A, Taiba, J, Talaat, IM, Talukder, A, Tampa, M, Tamuzi, JL, Tan, K-K, Tandukar, S, Tang, H, Tavakoli Oliaee, R, Tavangar, SM, Teimoori, M, Temsah, M-H, Teramoto, M, Thangaraju, P, Thankappan, KR, Thapar, R, Thayakaran, R, Thirunavukkarasu, S, Thomas, N, Thomas, NK, Thum, CCC, Tichopad, A, Ticoalu, JHV, Tillawi, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Torre, AE, Touvier, M, Tovani-Palone, MR, Tran, JT, Tran, MTN, Tran, NM, Tran, N-H, Trico, D, Tromans, SJ, Truyen, TTTT, Tsatsakis, A, Tsegay, GM, Tsermpini, EE, Tumurkhuu, M, Tyrovolas, S, Udoh, A, Umair, M, Umakanthan, S, Umar, TP, Undurraga, EA, Unim, B, Unnikrishnan, B, Unsworth, CA, Upadhyay, E, Urso, D, Usman, JS, Vahabi, SM, Vaithinathan, AG, Van den Eynde, J, Varga, O, Varma, RP, Vart, P, Vasankari, TJ, Vasic, M, Vaziri, S, Vellingiri, B, Venketasubramanian, N, Veroux, M, Verras, G-I, Vervoort, D, Villafañe, JH, Violante, FS, Vlassov, V, Vollset, SE, Volovat, SR, Vongpradith, A, Waheed, Y, Wang, C, Wang, F, Wang, N, Wang, S, Wang, Y, Wang, Y-P, Ward, P, Wassie, EG, Weaver, MR, Weerakoon, KG, Weintraub, RG, Weiss, DJ, Weldemariam, AH, Wells, KM, Wen, YF, Whisnant, JL, Whiteford, HA, Wiangkham, T, Wickramasinghe, DP, Wickramasinghe, ND, Wilandika, A, Wilkerson, C, Willeit, P, Wimo, A, Woldegebreal, DH, Wolf, AW, Wong, YJ, Woolf, AD, Wu, C, Wu, F, Wu, X, Wu, Z, Wulf Hanson, S, Xia, Y, Xiao, H, Xu, X, Xu, YY, Yadav, L, Yadollahpour, A, Yaghoubi, S, Yamagishi, K, Yang, L, Yano, Y, Yao, Y, Yaribeygi, H, Yazdanpanah, MH, Ye, P, Yehualashet, SS, Yesuf, SA, Yezli, S, Yiğit, A, Yiğit, V, Yigzaw, ZA, Yismaw, Y, Yon, DK, Yonemoto, N, Younis, MZ, Yu, C, Yu, Y, Yusuf, H, Zahid, MH, Zakham, F, Zaki, L, Zaki, N, Zaman, BA, Zamora, N, Zand, R, Zandieh, GGZ, Zar, HJ, Zarrintan, A, Zastrozhin, MS, Zhang, H, Zhang, N, Zhang, Y, Zhao, H, Zhong, C, Zhong, P, Zhou, J, Zhu, Z, Ziafati, M, Zielińska, M, Zimsen, SRM, Zoladl, M, Zumla, A, Zyoud, SH, Vos, T, and Murray, CJL
Published: 2024

6. Mapping inequalities in exclusive breastfeeding in low- and middle-income countries, 2000-2018

Author: Bhattacharjee, NV, Schaeffer, LE, Hay, SI, Lu, D, Schipp, MF, Lazzar-Atwood, A, Donkers, KM, Abady, GG, Abd-Allah, F, Abdelalim, A, Abebo, ZH, Abejie, AN, Abosetugn, AE, Abreu, LG, Abrigo, MRM, Abu-Gharbieh, E, Abushouk, AI, Adamu, AL, Adedeji, IA, Adegbosin, AE, Adekanmbi, V, Adetokunboh, OO, Agudelo-Botero, M, Aji, B, Akinyemi, OO, Alamneh, AA, Alanezi, FM, Alanzi, TM, Albright, J, Alcalde-Rabanal, JE, Alemu, BW, Alhassan, RK, Ali, BA, Ali, S, Alinia, C, Alipour, V, Amit, AML, Amugsi, DA, Anbesu, EW, Ancuceanu, R, Anjomshoa, M, Ansari, F, Antonio, CAT, Anvari, D, Arabloo, J, Arora, A, Artanti, KD, Asemahagn, MA, Asmare, WN, Atout, MMW, Ausloos, M, Awoke, N, Quintanilla, BPA, Ayanore, MA, Aynalem, YA, Ayza, MA, Azene, ZN, Darshan, BB, Badiye, AD, Baig, AA, Bakkannavar, SM, Banach, M, Banik, PC, Bärnighausen, TW, Basaleem, H, Bayati, M, Baye, BA, Bedi, N, Belay, SA, Bhagavathula, AS, Bhandari, D, Bhardwaj, N, Bhardwaj, P, Bhutta, ZA, Bijani, A, Birhan, TA, Birihane, BM, Bitew, ZW, Bohlouli, S, Bohluli, M, Bojia, HA, Boloor, A, Brady, OJ, Bragazzi, NL, Brunoni, AR, Budhathoki, SS, Nagaraja, SB, Butt, ZA, Cárdenas, R, Castaldelli-Maia, JM, Castro, F, Cernigliaro, A, Charan, J, Chatterjee, P, Chatterjee, S, Chattu, VK, Chaturvedi, S, Chowdhury, MAK, Chu, D-T, Collison, ML, Cook, AJ, Cork, MA, Couto, RAS, Dagnew, B, Dai, H, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Darwesh, AM, Darwish, AH, Daryani, A, Das, JK, Gupta, RD, Dávila-Cervantes, CA, Davis, AC, Weaver, ND, Denova-Gutiérrez, E, Deribe, K, Desalew, A, Deshpande, A, Dessie, A, Deuba, K, Dharmaratne, SD, Dhimal, M, Dhungana, GP, Diaz, D, Didarloo, A, Dipeolu, IO, Doan, LP, Duko, B, Duraes, AR, Dwyer-Lindgren, L, Earl, L, Zaki, MES, Tantawi, ME, Elema, TB, Elhabashy, HR, El-Jaafary, SI, Faris, PS, Faro, A, Farzadfar, F, Feigin, VL, Feleke, BE, Ferede, TY, Fischer, F, Foigt, NA, Folayan, MO, Franklin, RC, Gad, MM, Gaidhane, S, Gardner, WM, Geberemariyam, BS, Gebregiorgis, BG, Gebremedhin, KB, Gebremichael, B, Ghaffarpasand, F, Gilani, SA, Ginindza, TG, Glagn, M, Golechha, M, Gonfa, KB, Goulart, BNG, Gudi, N, Guido, D, Guled, RA, Guo, Y, Hamidi, S, Handiso, DW, Hasaballah, AI, Hassan, A, Hayat, K, Hegazy, MI, Heidari, B, Henry, NJ, Herteliu, C, de, Hidru, HD, Ho, HC, Hoang, CL, Holla, R, Hon, J, Hosseini, M, Hosseinzadeh, M, Househ, M, Hsairi, M, Hu, G, Huda, TM, Hwang, B-F, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Iqbal, U, Irvani, SSN, Islam, MM, Iwu, CCD, Iwu, CJ, Jain, A, Janodia, MD, Javaheri, T, John-Akinola, YO, Johnson, KB, Joukar, F, Jozwiak, JJ, Kabir, A, Kalankesh, LR, Kalhor, R, Kamath, A, Kamyari, N, Kanchan, OT, Kapoor, N, Matin, BK, Karimi, SE, Kasaye, HK, Kassahun, G, Kassebaum, NJ, Kayode, GA, Karyani, AK, Keiyoro, PN, Kelkay, B, Khalid, N, Khan, MN, Khatab, K, Khater, AM, Khater, MM, Khatib, MN, Kim, YJ, Kimokoti, RW, Kinyoki, DK, Kisa, A, Kisa, S, Kosen, S, Krishan, K, Kulkarni, V, Kumar, GA, Kumar, M, Kumar, N, Kumar, P, Kurmi, OP, Kusuma, D, Vecchia, CL, Lad, SD, Lami, FH, Landires, I, Lansingh, VC, Lasrado, S, Lee, PH, LeGrand, KE, Letourneau, ID, Lewycka, S, Li, B, Li, M-C, Li, S, Liu, X, Lodha, R, Lopez, JCF, Louie, C, Machado, DB, Maled, V, Maleki, S, Malta, DC, Mamun, AA, Manafi, N, Mansournia, MA, Mapoma, CC, Marczak, LB, Martins-Melo, FR, Mehndiratta, MM, Mejia-Rodriguez, F, Mekonnen, TC, Mendoza, W, Menezes, RG, Mengesha, EW, Mersha, AM, Miller, TR, Mini, GK, Mirrakhimov, EM, Misra, S, Moghadaszadeh, M, Mohammad, DK, Mohammadian-Hafshejani, A, Mohammed, JA, Mohammed, S, Mokdad, AH, Montero-Zamora, PA, Moradi, M, Moradzadeh, R, Moraga, P, Mosser, JF, Mousavi, SM, Khaneghah, AM, Munro, SB, Muriithi, MK, Mustafa, G, Muthupandian, S, Nagarajan, AJ, Naik, G, Naimzada, MD, Nangia, V, Nascimento, BR, Nayak, VC, Ndejjo, R, Ndwandwe, DE, Negoi, I, Nguefack-Tsague, G, Ngunjiri, JW, Nguyen, CT, Nguyen, DN, Nguyen, HLT, Nigussie, SN, Nigussie, TTN, Nikbakhsh, R, Nnaji, CA, Nunez-Samudio, V, Oancea, B, Oghenetega, OB, Olagunju, AT, Olusanya, BO, Olusanya, JO, Omer, MO, Onwujekwe, OE, Ortega-Altamirano, DV, Osgood-Zimmerman, AE, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Mahesh, PA, Padubidri, JR, Pana, A, Pandey, A, Pandi-Perumal, SR, Pangaribuan, HU, Parsekar, SS, Pasupula, DK, Patel, UK, Pathak, A, Pathak, M, Pattanshetty, SM, Patton, GC, Paulos, K, Pepito, VCF, Pickering, BV, Pinheiro, M, Piwoz, EG, Pokhrel, KN, Pourjafar, H, Prada, SI, Pribadi, DRA, Syed, ZQ, Rabiee, M, Rabiee, N, Rahim, F, Rahimzadeh, S, Rahman, A, Rahman, MHU, Rahmani, AM, Rai, RK, Ranabhat, CL, Rao, SJ, Rastogi, P, Rathi, P, Rawaf, DL, Rawaf, S, Rawassizadeh, R, Rawat, R, Regassa, LD, Rego, MAS, Reiner, RC, Reshmi, B, Rezapour, A, Ribeiro, AI, Rickard, J, Roever, L, Rumisha, SF, Rwegerera, GM, Sagar, R, Sajadi, SM, Salem, MR, Samy, AM, Santric-Milicevic, MM, Saraswathy, SYI, Sarker, AR, Sartorius, B, Sathian, B, Saxena, D, Sbarra, AN, Sengupta, D, Senthilkumaran, S, Sha, F, Shafaat, O, Shaheen, AA, Shaikh, MA, Shalash, AS, Shannawaz, M, Sheikh, A, Shetty, BSK, Shetty, RS, Shibuya, K, Shiferaw, WS, Shin, JI, Silva, DAS, Singh, NP, Singh, P, Singh, S, Sintayehu, Y, Skryabin, VY, Skryabina, AA, Soheili, A, Soltani, S, Sorrie, MB, Spurlock, EE, Steuben, KM, Sudaryanto, A, Sufiyan, MB, Swartz, SJ, Tadesse, EG, Tamiru, AT, Tapak, L, Tareque, MI, Tarigan, IU, Tesema, GA, Tesfay, FH, Teshome, A, Tessema, ZT, Thankappan, KR, Thapar, R, Thomas, N, Topor-Madry, R, Tovani-Palone, MR, Traini, E, Tran, BX, Truong, PN, Tsegaye, BTBT, Ullah, I, Umeokonkwo, CD, Unnikrishnan, B, Upadhyay, E, Uzochukwu, BSC, VanderHeide, JD, Violante, FS, Vo, B, Wado, YD, Waheed, Y, Wamai, RG, Wang, F, Wang, Y, Wang, Y-P, Wickramasinghe, ND, Wiens, KE, Wiysonge, CS, Woyczynski, L, Wu, A-M, Wu, C, Yamada, T, Yaya, S, Yeshaneh, A, Yeshaw, Y, Yeshitila, YG, Yilma, MT, Yip, P, Yonemoto, N, Yosef, T, Younis, MZ, Yousuf, AY, Yu, C, Yu, Y, Yuce, D, Zafar, S, Zaidi, SS, Zaki, L, Zakzuk, J, Zamanian, M, Zar, HJ, Zastrozhin, MS, Zastrozhina, A, Zelellw, DA, Zhang, Y, Zhang, Z-J, Zhao, X-JG, Zodpey, S, Zuniga, YMH, Local Burden of Disease Exclusive Breastfeeding Collaborators, Bhattacharjee, Natalia V, Schaeffer, Lauren E, Hay, Simon I, Duko, Bereket, Yeshaw, Yigizie, Local Burden of Disease Exclusive Breastfeeding Collaborators, Bhattacharjee N.V., Schaeffer L.E., Hay S.I., Lu D., Schipp M.F., Lazzar-Atwood A., Donkers K.M., Abady G.G., Abd-Allah F., Abdelalim A., Abebo Z.H., Abejie A.N., Abosetugn A.E., Abreu L.G., Abrigo M.R.M., Abu-Gharbieh E., Abushouk A.I., Adamu A.L., Adedeji I.A., Adegbosin A.E., Adekanmbi V., Adetokunboh O.O., Agudelo-Botero M., Aji B., Akinyemi O.O., Alamneh A.A., Alanezi F.M., Alanzi T.M., Albright J., Alcalde-Rabanal J.E., Alemu B.W., Alhassan R.K., Ali B.A., Ali S., Alinia C., Alipour V., Amit A.M.L., Amugsi D.A., Anbesu E.W., Ancuceanu R., Anjomshoa M., Ansari F., Antonio C.A.T., Anvari D., Arabloo J., Arora A., Artanti K.D., Asemahagn M.A., Asmare W.N., Atout M.M.W., Ausloos M., Awoke N., Quintanilla B.P.A., Ayanore M.A., Aynalem Y.A., Ayza M.A., Azene Z.N., Darshan B.B., Badiye A.D., Baig A.A., Bakkannavar S.M., Banach M., Banik P.C., Barnighausen T.W., Basaleem H., Bayati M., Baye B.A., Bedi N., Belay S.A., Bhagavathula A.S., Bhandari D., Bhardwaj N., Bhardwaj P., Bhutta Z.A., Bijani A., Birhan T.A., Birihane B.M., Bitew Z.W., Bohlouli S., Bohluli M., Bojia H.A., Boloor A., Brady O.J., Bragazzi N.L., Brunoni A.R., Budhathoki S.S., Nagaraja S.B., Butt Z.A., Cardenas R., Castaldelli-Maia J.M., Castro F., Cernigliaro A., Charan J., Chatterjee P., Chatterjee S., Chattu V.K., Chaturvedi S., Chowdhury M.A.K., Chu D.-T., Collison M.L., Cook A.J., Cork M.A., Couto R.A.S., Dagnew B., Dai H., Dandona L., Dandona R., Daneshpajouhnejad P., Darwesh A.M., Darwish A.H., Daryani A., Das J.K., Gupta R.D., Davila-Cervantes C.A., Davis A.C., Weaver N.D., Denova-Gutierrez E., Deribe K., Desalew A., Deshpande A., Dessie A., Deuba K., Dharmaratne S.D., Dhimal M., Dhungana G.P., Diaz D., Didarloo A., Dipeolu I.O., Doan L.P., Duko B., Duraes A.R., Dwyer-Lindgren L., Earl L., Zaki M.E.S., Tantawi M.E., Elema T.B., Elhabashy H.R., El-Jaafary S.I., Faris P.S., Faro A., Farzadfar F., Feigin V.L., Feleke B.E., Ferede T.Y., Fischer F., Foigt N.A., Folayan M.O., Franklin R.C., Gad M.M., Gaidhane S., Gardner W.M., Geberemariyam B.S., Gebregiorgis B.G., Gebremedhin K.B., Gebremichael B., Ghaffarpasand F., Gilani S.A., Ginindza T.G., Glagn M., Golechha M., Gonfa K.B., Goulart B.N.G., Gudi N., Guido D., Guled R.A., Guo Y., Hamidi S., Handiso D.W., Hasaballah A.I., Hassan A., Hayat K., Hegazy M.I., Heidari B., Henry N.J., Herteliu C., de Hidru H.D., Ho H.C., Hoang C.L., Holla R., Hon J., Hosseini M., Hosseinzadeh M., Househ M., Hsairi M., Hu G., Huda T.M., Hwang B.-F., Ibitoye S.E., Ilesanmi O.S., Ilic I.M., Ilic M.D., Inbaraj L.R., Iqbal U., Irvani S.S.N., Islam M.M., Iwu C.C.D., Iwu C.J., Jain A., Janodia M.D., Javaheri T., John-Akinola Y.O., Johnson K.B., Joukar F., Jozwiak J.J., Kabir A., Kalankesh L.R., Kalhor R., Kamath A., Kamyari N., Kanchan O.T., Kapoor N., Matin B.K., Karimi S.E., Kasaye H.K., Kassahun G., Kassebaum N.J., Kayode G.A., Karyani A.K., Keiyoro P.N., Kelkay B., Khalid N., Khan M.N., Khatab K., Khater A.M., Khater M.M., Khatib M.N., Kim Y.J., Kimokoti R.W., Kinyoki D.K., Kisa A., Kisa S., Kosen S., Krishan K., Kulkarni V., Kumar G.A., Kumar M., Kumar N., Kumar P., Kurmi O.P., Kusuma D., Vecchia C.L., Lad S.D., Lami F.H., Landires I., Lansingh V.C., Lasrado S., Lee P.H., LeGrand K.E., Letourneau I.D., Lewycka S., Li B., Li M.-C., Li S., Liu X., Lodha R., Lopez J.C.F., Louie C., Machado D.B., Maled V., Maleki S., Malta D.C., Mamun A.A., Manafi N., Mansournia M.A., Mapoma C.C., Marczak L.B., Martins-Melo F.R., Mehndiratta M.M., Mejia-Rodriguez F., Mekonnen T.C., Mendoza W., Menezes R.G., Mengesha E.W., Mersha A.M., Miller T.R., Mini G.K., Mirrakhimov E.M., Misra S., Moghadaszadeh M., Mohammad D.K., Mohammadian-Hafshejani A., Mohammed J.A., Mohammed S., Mokdad A.H., Montero-Zamora P.A., Moradi M., Moradzadeh R., Moraga P., Mosser J.F., Mousavi S.M., Khaneghah A.M., Munro S.B., Muriithi M.K., Mustafa G., Muthupandian S., Nagarajan A.J., Naik G., Naimzada M.D., Nangia V., Nascimento B.R., Nayak V.C., Ndejjo R., Ndwandwe D.E., Negoi I., Nguefack-Tsague G., Ngunjiri J.W., Nguyen C.T., Nguyen D.N., Nguyen H.L.T., Nigussie S.N., Nigussie T.T.N., Nikbakhsh R., Nnaji C.A., Nunez-Samudio V., Oancea B., Oghenetega O.B., Olagunju A.T., Olusanya B.O., Olusanya J.O., Omer M.O., Onwujekwe O.E., Ortega-Altamirano D.V., Osgood-Zimmerman A.E., Otstavnov N., Otstavnov S.S., Owolabi M.O., Mahesh P.A., Padubidri J.R., Pana A., Pandey A., Pandi-Perumal S.R., Pangaribuan H.U., Parsekar S.S., Pasupula D.K., Patel U.K., Pathak A., Pathak M., Pattanshetty S.M., Patton G.C., Paulos K., Pepito V.C.F., Pickering B.V., Pinheiro M., Piwoz E.G., Pokhrel K.N., Pourjafar H., Prada S.I., Pribadi D.R.A., Syed Z.Q., Rabiee M., Rabiee N., Rahim F., Rahimzadeh S., Rahman A., Rahman M.H.U., Rahmani A.M., Rai R.K., Ranabhat C.L., Rao S.J., Rastogi P., Rathi P., Rawaf D.L., Rawaf S., Rawassizadeh R., Rawat R., Regassa L.D., Rego M.A.S., Reiner R.C., Reshmi B., Rezapour A., Ribeiro A.I., Rickard J., Roever L., Rumisha S.F., Rwegerera G.M., Sagar R., Sajadi S.M., Salem M.R., Samy A.M., Santric-Milicevic M.M., Saraswathy S.Y.I., Sarker A.R., Sartorius B., Sathian B., Saxena D., Sbarra A.N., Sengupta D., Senthilkumaran S., Sha F., Shafaat O., Shaheen A.A., Shaikh M.A., Shalash A.S., Shannawaz M., Sheikh A., Shetty B.S.K., Shetty R.S., Shibuya K., Shiferaw W.S., Shin J.I., Silva D.A.S., Singh N.P., Singh P., Singh S., Sintayehu Y., Skryabin V.Y., Skryabina A.A., Soheili A., Soltani S., Sorrie M.B., Spurlock E.E., Steuben K.M., Sudaryanto A., Sufiyan M.B., Swartz S.J., Tadesse E.G., Tamiru A.T., Tapak L., Tareque M.I., Tarigan I.U., Tesema G.A., Tesfay F.H., Teshome A., Tessema Z.T., Thankappan K.R., Thapar R., Thomas N., Topor-Madry R., Tovani-Palone M.R., Traini E., Tran B.X., Truong P.N., Tsegaye B.T.B.T., Ullah I., Umeokonkwo C.D., Unnikrishnan B., Upadhyay E., Uzochukwu B.S.C., VanderHeide J.D., Violante F.S., Vo B., Wado Y.D., Waheed Y., Wamai R.G., Wang F., Wang Y., Wang Y.-P., Wickramasinghe N.D., Wiens K.E., Wiysonge C.S., Woyczynski L., Wu A.-M., Wu C., Yamada T., Yaya S., Yeshaneh A., Yeshaw Y., Yeshitila Y.G., Yilma M.T., Yip P., Yonemoto N., Yosef T., Younis M.Z., Yousuf A.Y., Yu C., Yu Y., Yuce D., Zafar S., Zaidi S.S., Zaki L., Zakzuk J., Zamanian M., Zar H.J., Zastrozhin M.S., Zastrozhina A., Zelellw D.A., Zhang Y., Zhang Z.-J., Zhao X.-J.G., Zodpey S., Zuniga Y.M.H., Collaborators, Local Burden of Disease Exclusive Breastfeeding, and Instituto de Saúde Pública da Universidade do Porto
Subjects: RJ101, Psychological intervention, Breastfeeding, Social Sciences, geography, Behavioral Neuroscience, 0302 clinical medicine, RA0421, Prevalence, Psychology, policy making, 030212 general & internal medicine, Policy Making, humans, media_common, CHILD GROWTH FAILURE, Developing world, 0303 health sciences, education.field_of_study, Psychology, Biological, Geography, Psychology, Experimental, Health Status Disparitie, Multidisciplinary Sciences, Breast Feeding, breast feeding, Scale (social sciences), Science & Technology - Other Topics, Life Sciences & Biomedicine, Human, AFRICA, Social Psychology, Inequality, spatial analysis, media_common.quotation_subject, public policy, Population, prevalence, Public policy, Developing country, Experimental and Cognitive Psychology, Public Policy, Local Burden of Disease Exclusive Breastfeeding Collaborators, Article, Developing Countrie, 03 medical and health sciences, Environmental health, Humans, Nutrition disorders, education, Developing Countries, 030304 developmental biology, Spatial Analysis, Science & Technology, Neurosciences, Health Status Disparities, developing countries, health status disparities, Risk factors, Neurosciences & Neurology, Breast feeding
Abstract: Exclusive breastfeeding (EBF)—giving infants only breast-milk for the first 6 months of life—is a component of optimal breastfeeding practices effective in preventing child morbidity and mortality. EBF practices are known to vary by population and comparable subnational estimates of prevalence and progress across low- and middle-income countries (LMICs) are required for planning policy and interventions. Here we present a geospatial analysis of EBF prevalence estimates from 2000 to 2018 across 94 LMICs mapped to policy-relevant administrative units (for example, districts), quantify subnational inequalities and their changes over time, and estimate probabilities of meeting the World Health Organization’s Global Nutrition Target (WHO GNT) of ≥70% EBF prevalence by 2030. While six LMICs are projected to meet the WHO GNT of ≥70% EBF prevalence at a national scale, only three are predicted to meet the target in all their district-level units by 2030., Bhattacharjee and Schaeffer et al. map exclusive breastfeeding (EBF) in 94 low- and middle-income countries (LMICs), finding increased EBF practice and reduced subnational variation across the majority of LMICs from 2000 to 2018. However, only six LMICs will meet WHO’s target of ≥70% EBF by 2030 nationally, and only three will achieve this in all districts.
Published: 2021

7. Global, regional, and national mortality among young people aged 10–24 years, 1950–2019: a systematic analysis for the Global Burden of Disease Study 2019

Author: Collaborators, GAM, Ward, JL, Azzopardi, PS, Francis, KL, Santelli, JS, Skirbekk, V, Sawyer, SM, Kassebaum, NJ, Mokdad, AH, Hay, SI, Abd-Allah, F, Abdoli, A, Abdollahi, M, Abedi, A, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abu-Gharbieh, E, Abushouk, AI, Adebayo, OM, Adekanmbi, V, Adham, D, Advani, SM, Afshari, K, Agrawal, A, Ahmad, T, Ahmadi, K, Ahmed, AE, Aji, B, Akombi-Inyang, B, Alahdab, F, Al-Aly, Z, Alam, K, Alanezi, FM, Alanzi, TM, Alcalde-Rabanal, JE, Alemu, BW, Al-Hajj, S, Alhassan, RK, Ali, S, Alicandro, G, Alijanzadeh, M, Aljunid, SM, Almasi-Hashiani, A, Almasri, NA, Al-Mekhlafi, HM, Alonso, J, Al-Raddadi, RM, Altirkawi, KA, Alvis-Guzman, N, Amare, AT, Amini, S, Aminorroaya, A, Amit, AML, Amugsi, DA, Ancuceanu, R, Anderlini, D, Andrei, CL, Androudi, S, Ansari, F, Ansari, I, Antonio, CAT, Anvari, D, Anwer, R, Appiah, SCY, Arabloo, J, Arab-Zozani, M, Ärnlöv, J, Asaad, M, Asadi-Aliabadi, M, Asadi-Pooya, AA, Atout, MMW, Ausloos, M, Avenyo, EK, Avila-Burgos, L, Quintanilla, BPA, Ayano, G, Aynalem, YA, Azari, S, Azene, ZN, Bakhshaei, MH, Bakkannavar, SM, Banach, M, Banik, PC, Barboza, MA, Barker-Collo, SL, Bärnighausen, TW, Basu, S, Baune, BT, Bayati, M, Bedi, N, Beghi, E, Bekuma, TT, Bell, AW, Bell, ML, Benjet, C, Bensenor, IM, Berhe, AK, Berhe, K, Berman, AE, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bhattarai, S, Bhutta, ZA, Bijani, A, Bikbov, B, Biondi, A, Birhanu, TTM, Biswas, RK, Bohlouli, S, Bolla, SR, Boloor, A, Borschmann, R, Boufous, S, Bragazzi, NL, Braithwaite, D, Breitborde, NJK, Brenner, H, Britton, GB, Burns, RA, Nagaraja, SB, Butt, ZA, dos Santos, FLC, Cámera, LA, Campos-Nonato, IR, Rincon, JCC, Cárdenas, R, Carreras, G, Carrero, JJ, Carvalho, F, Castaldelli-Maia, JM, Castañeda-Orjuela, CA, Castelpietra, G, Catalá-López, F, Cerin, E, Chandan, JS, Chang, H-Y, Chang, J-C, Charan, J, Chattu, VK, Chaturvedi, S, Choi, J-YJ, Chowdhury, MAK, Christopher, DJ, Chu, D-T, Chung, MT, Chung, S-C, Cicuttini, FM, Constantin, TV, Costa, VM, Dahlawi, SMA, Dai, H, Dai, X, Damiani, G, Dandona, L, Dandona, R, Daneshpajouhnejad, P, Darwesh, AM, Dávila-Cervantes, CA, Davletov, K, De la Hoz, FP, De Leo, D, Dervenis, N, Desai, R, Desalew, A, Deuba, K, Dharmaratne, SD, Dhungana, GP, Dianatinasab, M, da Silva, DD, Diaz, D, Didarloo, A, Djalalinia, S, Dorostkar, F, Doshi, CP, Doshmangir, L, Doyle, KE, Duraes, AR, Kalan, ME, Ebtehaj, S, Edvardsson, D, Tantawi, ME, Elgendy, IY, El-Jaafary, SI, Elsharkawy, A, Eshrati, B, Eskandarieh, S, Esmaeilnejad, S, Esmaeilzadeh, F, Esteghamati, S, Faro, A, Farzadfar, F, Fattahi, N, Feigin, VL, Ferede, TY, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Filip, I, Fischer, F, Fisher, JL, Foigt, NA, Folayan, MO, Fomenkov, AA, Foroutan, M, Fukumoto, T, Gad, MM, Gaidhane, AM, Gallus, S, Gebre, T, Gebremedhin, KB, Gebremeskel, GG, Gebremeskel, L, Gebreslassie, AA, Gesesew, HA, Ghadiri, K, Ghafourifard, M, Ghamari, F, Ghashghaee, A, Gilani, SA, Gnedovskaya, EV, Godinho, MA, Golechha, M, Goli, S, Gona, PN, Gopalani, SV, Gorini, G, Grivna, M, Gubari, MIM, Gugnani, HC, Guimarães, RA, Guo, Y, Gupta, R, Haagsma, JA, Hafezi-Nejad, N, Haile, TG, Haj-Mirzaian, A, Hall, BJ, Hamadeh, RR, Abdullah, KH, Hamidi, S, Handiso, DW, Hanif, A, Hankey, GJ, Haririan, H, Haro, JM, Hasaballah, AI, Hashi, A, Hassan, A, Hassanipour, S, Hassankhani, H, Hayat, K, Heidari-Soureshjani, R, Herteliu, C, Heydarpour, F, Ho, HC, Hole, MK, Holla, R, Hoogar, P, Hosseini, M, Hosseinzadeh, M, Hostiuc, M, Hostiuc, S, Househ, M, Hsairi, M, Huda, TM, Humayun, A, Hussain, R, Hwang, B-F, Iavicoli, I, Ibitoye, SE, Ilesanmi, OS, Ilic, IM, Ilic, MD, Inbaraj, LR, Intarut, N, Iqbal, U, Irvani, SSN, Islam, MM, Islam, MS, Iso, H, Ivers, RQ, Jahani, MA, Jakovljevic, M, Jalali, A, Janodia, MD, Javaheri, T, Jeemon, P, Jenabi, E, Jha, RP, Jha, V, Ji, JS, Jonas, JB, Jones, KM, Joukar, F, Jozwiak, JJ, Juliusson, PB, Jürisson, M, Kabir, A, Kabir, Z, Kalankesh, LR, Kalhor, R, Kamyari, N, Kanchan, T, Karch, A, Karimi, SE, Kaur, S, Kayode, GA, Keiyoro, PN, Khalid, N, Khammarnia, M, Khan, M, Khan, N, Khatab, K, Khater, MM, Khatib, MN, Khayamzadeh, M, Khazaie, H, Khoja, AT, Kieling, C, Kim, Y-E, Kim, YJ, Kimokoti, RW, Kisa, A, Kisa, S, Kivimäki, M, Koolivand, A, Kosen, S, Koyanagi, A, Krishan, K, Kugbey, N, Kumar, GA, Kumar, M, Kumar, N, Kurmi, OP, Kusuma, D, La Vecchia, C, Lacey, B, Lal, DK, Lalloo, R, Lan, Q, Landires, I, Van Charles Lansingh, Larsson, AO, Lasrado, S, Lassi, ZS, Lauriola, P, Lee, PH, Lee, SWH, Leigh, J, Leonardi, M, Leung, J, Levi, M, Lewycka, S, Li, B, Li, M-C, Li, S, Lim, L-L, Lim, SS, Liu, X, Lorkowski, S, Lotufo, PA, Lunevicius, R, Maddison, R, Mahasha, PW, Mahdavi, MM, Mahmoudi, M, Majeed, A, Maleki, A, Malekzadeh, R, Malta, DC, Mamun, AA, Mansouri, B, Mansournia, MA, Martinez, G, Martinez-Raga, J, Martins-Melo, FR, Mason-Jones, AJ, Masoumi, SZ, Mathur, MR, Maulik, PK, McGrath, JJ, Mehndiratta, MM, Mehri, F, Memiah, PTN, Mendoza, W, Menezes, RG, Mengesha, EW, Meretoja, A, Meretoja, TJ, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, IM, Miller, TR, Mini, G, Mirica, A, Mirrakhimov, EM, Mirzaei, H, Mirzaei, M, Moazen, B, Mohammad, DK, Mohammadi, S, Mohammadian-Hafshejani, A, Mohammadifard, N, Mohammadpourhodki, R, Mohammed, S, Monasta, L, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Moraga, P, Morrison, SD, Mosapour, A, Khaneghah, AM, Mueller, UO, Muriithi, MK, Murray, CJL, Muthupandian, S, Naderi, M, Nagarajan, AJ, Naghavi, M, Naimzada, MD, Nangia, V, Nayak, VC, Nazari, J, Ndejjo, R, Negoi, I, Negoi, RI, Netsere, HB, Nguefack-Tsague, G, Nguyen, DN, Nguyen, HLT, Nie, J, Ningrum, DNA, Nnaji, CA, Nomura, S, Noubiap, JJ, Nowak, C, Nuñez-Samudio, V, Ogbo, FA, Oghenetega, OB, Oh, I-H, Oladnabi, M, Olagunju, AT, Olusanya, BO, Olusanya, JO, Bali, AO, Omer, MO, Onwujekwe, OE, Ortiz, A, Otoiu, A, Otstavnov, N, Otstavnov, SS, Øverland, S, Owolabi, MO, Mahesh, PA, Padubidri, JR, Pakshir, K, Palladino, R, Pana, A, Panda-Jonas, S, Pandey, A, Panelo, CIA, Park, E-K, Patten, SB, Peden, AE, Pepito, VCF, Peprah, EK, Pereira, J, Pesudovs, K, Pham, HQ, Phillips, MR, Piradov, MA, Pirsaheb, M, Postma, MJ, Pottoo, FH, Pourjafar, H, Pourshams, A, Prada, SI, Pupillo, E, Syed, ZQ, Rabiee, MH, Rabiee, N, Radfar, A, Rafiee, A, Raggi, A, Rahim, F, Rahimi-Movaghar, V, Rahman, MHU, Rahman, MA, Ramezanzadeh, K, Ranabhat, CL, Rao, SJ, Rashedi, V, Rastogi, P, Rathi, P, Rawaf, DL, Rawaf, S, Rawal, L, Rawassizadeh, R, Renzaho, AMN, Rezaei, N, Rezai, MS, Riahi, SM, Rickard, J, Roever, L, Ronfani, L, Roth, GA, Rubagotti, E, Rumisha, SF, Rwegerera, GM, Sabour, S, Sachdev, PS, Saddik, B, Sadeghi, E, Moghaddam, SS, Sagar, R, Sahebkar, A, Sahraian, MA, Sajadi, SM, Salem, MR, Salimzadeh, H, Samy, AM, Sanabria, J, Santric-Milicevic, MM, Saraswathy, SYI, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sattin, D, Saxena, D, Saxena, S, Schiavolin, S, Schwebel, DC, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Sha, F, Shafaat, O, Shahabi, S, Shaheen, AA, Shaikh, MA, Shakiba, S, Shamsi, M, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shetty, BSK, Shi, P, Shigematsu, M, Shin, JI, Shiri, R, Shuval, K, Siabani, S, Sigfusdottir, ID, Sigurvinsdottir, R, Silva, DAS, Silva, JP, Simonetti, B, Singh, JA, Singh, V, Sinke, AH, Skryabin, VY, Slater, H, Smith, EUR, Sobhiyeh, MR, Sobngwi, E, Soheili, A, Somefun, OD, Sorrie, MB, Soyiri, IN, Sreeramareddy, CT, Stein, DJ, Stokes, MA, Sudaryanto, A, Sultan, I, Tabarés-Seisdedos, R, Tabuchi, T, Tadakamadla, SK, Taherkhani, A, Tamiru, AT, Tareque, I, Thankappan, KR, Thapar, R, Thomas, N, Titova, MV, Tonelli, M, Tovani-Palone, MR, Tran, BX, Travillian, RS, Tsai, AC, Tsatsakis, A, Car, LT, Uddin, R, Unim, B, Unnikrishnan, B, Upadhyay, E, Vacante, M, Tahbaz, SV, Valdez, PR, Varughese, S, Vasankari, TJ, Venketasubramanian, N, Villeneuve, PJ, Violante, FS, Vlassov, V, Vos, T, Vu, GT, Waheed, Y, Wamai, RG, Wang, Y, Wang, Y-P, Westerman, R, Wickramasinghe, ND, Wu, A-M, Wu, C, Jabbari, SHY, Yamagishi, K, Yano, Y, Yaya, S, Yazdi-Feyzabadi, V, Yeshitila, YG, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yousefinezhadi, T, Yu, C, Yu, Y, Yuce, D, Zaidi, SS, Bin Zaman, S, Zamani, M, Zamanian, M, Zarafshan, H, Zarei, A, Zastrozhin, MS, Zhang, Y, Zhang, Z-J, Zhao, X-JG, Zhu, C, Patton, GC, Viner, RM, Collaborators, GBD 2019 Adolescent Mortality, Ward, J. L., Azzopardi, P. S., Francis, K. L., Santelli, J. S., Skirbekk, V., Sawyer, S. M., Kassebaum, N. J., Mokdad, A. H., Hay, S. I., Abd-Allah, F., Abdoli, A., Abdollahi, M., Abedi, A., Abolhassani, H., Abreu, L. G., Abrigo, M. R. M., Abu-Gharbieh, E., Abushouk, A. I., Adebayo, O. M., Adekanmbi, V., Adham, D., Advani, S. M., Afshari, K., Agrawal, A., Ahmad, T., Ahmadi, K., Ahmed, A. E., Aji, B., Akombi-Inyang, B., Alahdab, F., Al-Aly, Z., Alam, K., Alanezi, F. M., Alanzi, T. M., Alcalde-Rabanal, J. E., Alemu, B. W., Al-Hajj, S., Alhassan, R. K., Ali, S., Alicandro, G., Alijanzadeh, M., Aljunid, S. M., Almasi-Hashiani, A., Almasri, N. A., Al-Mekhlafi, H. M., Alonso, J., Al-Raddadi, R. M., Altirkawi, K. A., Alvis-Guzman, N., Amare, A. T., Amini, S., Aminorroaya, A., Amit, A. M. L., Amugsi, D. A., Ancuceanu, R., Anderlini, D., Andrei, C. L., Androudi, S., Ansari, F., Ansari, I., Antonio, C. A. T., Anvari, D., Anwer, R., Appiah, S. C. Y., Arabloo, J., Arab-Zozani, M., Arnlov, J., Asaad, M., Asadi-Aliabadi, M., Asadi-Pooya, A. A., Atout, M. M. W., Ausloos, M., Avenyo, E. K., Avila-Burgos, L., Ayala Quintanilla, B. P., Ayano, G., Aynalem, Y. A., Azari, S., Azene, Z. N., Bakhshaei, M. H., Bakkannavar, S. M., Banach, M., Banik, P. C., Barboza, M. A., Barker-Collo, S. L., Barnighausen, T. W., Basu, S., Baune, B. T., Bayati, M., Bedi, N., Beghi, E., Bekuma, T. T., Bell, A. W., Bell, M. L., Benjet, C., Bensenor, I. M., Berhe, A. K., Berhe, K., Berman, A. E., Bhagavathula, A. S., Bhardwaj, N., Bhardwaj, P., Bhattacharyya, K., Bhattarai, S., Bhutta, Z. A., Bijani, A., Bikbov, B., Biondi, A., Birhanu, T. T. M., Biswas, R. K., Bohlouli, S., Bolla, S. R., Boloor, A., Borschmann, R., Boufous, S., Bragazzi, N. L., Braithwaite, D., Breitborde, N. J. K., Brenner, H., Britton, G. B., Burns, R. A., Burugina Nagaraja, S., Butt, Z. A., Caetano dos Santos, F. L., Camera, L. A., Campos-Nonato, I. R., Campuzano Rincon, J. C., Cardenas, R., Carreras, G., Carrero, J. J., Carvalho, F., Castaldelli-Maia, J. M., Castaneda-Orjuela, C. A., Castelpietra, G., Catala-Lopez, F., Cerin, E., Chandan, J. S., Chang, H. -Y., Chang, J. -C., Charan, J., Chattu, V. K., Chaturvedi, S., Choi, J. -Y. J., Chowdhury, M. A. K., Christopher, D. J., Chu, D. -T., Chung, M. T., Chung, S. -C., Cicuttini, F. M., Constantin, T. V., Costa, V. M., Dahlawi, S. M. A., Dai, H., Dai, X., Damiani, G., Dandona, L., Dandona, R., Daneshpajouhnejad, P., Darwesh, A. M., Davila-Cervantes, C. A., Davletov, K., De la Hoz, F. P., De Leo, D., Dervenis, N., Desai, R., Desalew, A., Deuba, K., Dharmaratne, S. D., Dhungana, G. P., Dianatinasab, M., Dias da Silva, D., Diaz, D., Didarloo, A., Djalalinia, S., Dorostkar, F., Doshi, C. P., Doshmangir, L., Doyle, K. E., Duraes, A. R., Ebrahimi Kalan, M., Ebtehaj, S., Edvardsson, D., El Tantawi, M., Elgendy, I. Y., El-Jaafary, S. I., Elsharkawy, A., Eshrati, B., Eskandarieh, S., Esmaeilnejad, S., Esmaeilzadeh, F., Esteghamati, S., Faro, A., Farzadfar, F., Fattahi, N., Feigin, V. L., Ferede, T. Y., Fereshtehnejad, S. -M., Fernandes, E., Ferrara, P., Filip, I., Fischer, F., Fisher, J. L., Foigt, N. A., Folayan, M. O., Fomenkov, A. A., Foroutan, M., Fukumoto, T., Gad, M. M., Gaidhane, A. M., Gallus, S., Gebre, T., Gebremedhin, K. B., Gebremeskel, G. G., Gebremeskel, L., Gebreslassie, A. A., Gesesew, H. A., Ghadiri, K., Ghafourifard, M., Ghamari, F., Ghashghaee, A., Gilani, S. A., Gnedovskaya, E. V., Godinho, M. A., Golechha, M., Goli, S., Gona, P. N., Gopalani, S. V., Gorini, G., Grivna, M., Gubari, M. I. M., Gugnani, H. C., Guimaraes, R. A., Guo, Y., Gupta, R., Haagsma, J. A., Hafezi-Nejad, N., Haile, T. G., Haj-Mirzaian, A., Hall, B. J., Hamadeh, R. R., Hamagharib Abdullah, K., Hamidi, S., Handiso, D. W., Hanif, A., Hankey, G. J., Haririan, H., Haro, J. M., Hasaballah, A. I., Hashi, A., Hassan, A., Hassanipour, S., Hassankhani, H., Hayat, K., Heidari-Soureshjani, R., Herteliu, C., Heydarpour, F., Ho, H. C., Hole, M. K., Holla, R., Hoogar, P., Hosseini, M., Hosseinzadeh, M., Hostiuc, M., Hostiuc, S., Househ, M., Hsairi, M., Huda, T. M., Humayun, A., Hussain, R., Hwang, B. -F., Iavicoli, I., Ibitoye, S. E., Ilesanmi, O. S., Ilic, I. M., Ilic, M. D., Inbaraj, L. R., Intarut, N., Iqbal, U., Irvani, S. S. N., Islam, M. M., Islam, S. M. S., Iso, H., Ivers, R. Q., Jahani, M. A., Jakovljevic, M., Jalali, A., Janodia, M. D., Javaheri, T., Jeemon, P., Jenabi, E., Jha, R. P., Jha, V., Ji, J. S., Jonas, J. B., Jones, K. M., Joukar, F., Jozwiak, J. J., Juliusson, P. B., Jurisson, M., Kabir, A., Kabir, Z., Kalankesh, L. R., Kalhor, R., Kamyari, N., Kanchan, T., Karch, A., Karimi, S. E., Kaur, S., Kayode, G. A., Keiyoro, P. N., Khalid, N., Khammarnia, M., Khan, M., Khan, M. N., Khatab, K., Khater, M. M., Khatib, M. N., Khayamzadeh, M., Khazaie, H., Khoja, A. T., Kieling, C., Kim, Y. -E., Kim, Y. J., Kimokoti, R. W., Kisa, A., Kisa, S., Kivimaki, M., Koolivand, A., Kosen, S., Koyanagi, A., Krishan, K., Kugbey, N., Kumar, G. A., Kumar, M., Kumar, N., Kurmi, O. P., Kusuma, D., La Vecchia, C., Lacey, B., Lal, D. K., Lalloo, R., Lan, Q., Landires, I., Lansingh, V. C., Larsson, A. O., Lasrado, S., Lassi, Z. S., Lauriola, P., Lee, P. H., Lee, S. W. H., Leigh, J., Leonardi, M., Leung, J., Levi, M., Lewycka, S., Li, B., Li, M. -C., Li, S., Lim, L. -L., Lim, S. S., Liu, X., Lorkowski, S., Lotufo, P. A., Lunevicius, R., Maddison, R., Mahasha, P. W., Mahdavi, M. M., Mahmoudi, M., Majeed, A., Maleki, A., Malekzadeh, R., Malta, D. C., Mamun, A. A., Mansouri, B., Mansournia, M. A., Martinez, G., Martinez-Raga, J., Martins-Melo, F. R., Mason-Jones, A. J., Masoumi, S. Z., Mathur, M. R., Maulik, P. K., Mcgrath, J. J., Mehndiratta, M. M., Mehri, F., Memiah, P. T. N., Mendoza, W., Menezes, R. G., Mengesha, E. W., Meretoja, A., Meretoja, T. J., Mestrovic, T., Miazgowski, B., Miazgowski, T., Michalek, I. M., Miller, T. R., Mini, G. K., Mirica, A., Mirrakhimov, E. M., Mirzaei, H., Mirzaei, M., Moazen, B., Mohammad, D. K., Mohammadi, S., Mohammadian-Hafshejani, A., Mohammadifard, N., Mohammadpourhodki, R., Mohammed, S., Monasta, L., Moradi, G., Moradi-Lakeh, M., Moradzadeh, R., Moraga, P., Morrison, S. D., Mosapour, A., Mousavi Khaneghah, A., Mueller, U. O., Muriithi, M. K., Murray, C. J. L., Muthupandian, S., Naderi, M., Nagarajan, A. J., Naghavi, M., Naimzada, M. D., Nangia, V., Nayak, V. C., Nazari, J., Ndejjo, R., Negoi, I., Negoi, R. I., Netsere, H. B., Nguefack-Tsague, G., Nguyen, D. N., Nguyen, H. L. T., Nie, J., Ningrum, D. N. A., Nnaji, C. A., Nomura, S., Noubiap, J. J., Nowak, C., Nunez-Samudio, V., Ogbo, F. A., Oghenetega, O. B., Oh, I. -H., Oladnabi, M., Olagunju, A. T., Olusanya, B. O., Olusanya, J. O., Omar Bali, A., Omer, M. O., Onwujekwe, O. E., Ortiz, A., Otoiu, A., Otstavnov, N., Otstavnov, S. S., Overland, S., Owolabi, M. O., P A, M., Padubidri, J. R., Pakshir, K., Palladino, R., Pana, A., Panda-Jonas, S., Pandey, A., Panelo, C. I. A., Park, E. -K., Patten, S. B., Peden, A. E., Pepito, V. C. F., Peprah, E. K., Pereira, J., Pesudovs, K., Pham, H. Q., Phillips, M. R., Piradov, M. A., Pirsaheb, M., Postma, M. J., Pottoo, F. H., Pourjafar, H., Pourshams, A., Prada, S. I., Pupillo, E., Quazi Syed, Z., Rabiee, M. H., Rabiee, N., Radfar, A., Rafiee, A., Raggi, A., Rahim, F., Rahimi-Movaghar, V., Rahman, M. H. U., Rahman, M. A., Ramezanzadeh, K., Ranabhat, C. L., Rao, S. J., Rashedi, V., Rastogi, P., Rathi, P., Rawaf, D. L., Rawaf, S., Rawal, L., Rawassizadeh, R., Renzaho, A. M. N., Rezaei, N., Rezai, M. S., Riahi, S. M., Rickard, J., Roever, L., Ronfani, L., Roth, G. A., Rubagotti, E., Rumisha, S. F., Rwegerera, G. M., Sabour, S., Sachdev, P. S., Saddik, B., Sadeghi, E., Saeedi Moghaddam, S., Sagar, R., Sahebkar, A., Sahraian, M. A., Sajadi, S. M., Salem, M. R., Salimzadeh, H., Samy, A. M., Sanabria, J., Santric-Milicevic, M. M., Saraswathy, S. Y. I., Sarrafzadegan, N., Sarveazad, A., Sathish, T., Sattin, D., Saxena, D., Saxena, S., Schiavolin, S., Schwebel, D. C., Schwendicke, F., Senthilkumaran, S., Sepanlou, S. G., Sha, F., Shafaat, O., Shahabi, S., Shaheen, A. A., Shaikh, M. A., Shakiba, S., Shamsi, M., Shannawaz, M., Sharafi, K., Sheikh, A., Sheikhbahaei, S., Shetty, B. S. K., Shi, P., Shigematsu, M., Shin, J. I., Shiri, R., Shuval, K., Siabani, S., Sigfusdottir, I. D., Sigurvinsdottir, R., Silva, D. A. S., Silva, J. P., Simonetti, B., Singh, J. A., Singh, V., Sinke, A. H., Skryabin, V. Y., Slater, H., Smith, E. U. R., Sobhiyeh, M. R., Sobngwi, E., Soheili, A., Somefun, O. D., Sorrie, M. B., Soyiri, I. N., Sreeramareddy, C. T., Stein, D. J., Stokes, M. A., Sudaryanto, A., Sultan, I., Tabares-Seisdedos, R., Tabuchi, T., Tadakamadla, S. K., Taherkhani, A., Tamiru, A. T., Tareque, M. I., Thankappan, K. 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M., Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Bill & Melinda Gates Foundation, Ward J.L., Azzopardi P.S., Francis K.L., Santelli J.S., Skirbekk V., Sawyer S.M., Kassebaum N.J., Mokdad A.H., Hay S.I., Abd-Allah F., Abdoli A., Abdollahi M., Abedi A., Abolhassani H., Abreu L.G., Abrigo M.R.M., Abu-Gharbieh E., Abushouk A.I., Adebayo O.M., Adekanmbi V., Adham D., Advani S.M., Afshari K., Agrawal A., Ahmad T., Ahmadi K., Ahmed A.E., Aji B., Akombi-Inyang B., Alahdab F., Al-Aly Z., Alam K., Alanezi F.M., Alanzi T.M., Alcalde-Rabanal J.E., Alemu B.W., Al-Hajj S., Alhassan R.K., Ali S., Alicandro G., Alijanzadeh M., Aljunid S.M., Almasi-Hashiani A., Almasri N.A., Al-Mekhlafi H.M., Alonso J., Al-Raddadi R.M., Altirkawi K.A., Alvis-Guzman N., Amare A.T., Amini S., Aminorroaya A., Amit A.M.L., Amugsi D.A., Ancuceanu R., Anderlini D., Andrei C.L., Androudi S., Ansari 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F., Castaldelli-Maia J.M., Castaneda-Orjuela C.A., Castelpietra G., Catala-Lopez F., Cerin E., Chandan J.S., Chang H.-Y., Chang J.-C., Charan J., Chattu V.K., Chaturvedi S., Choi J.-Y.J., Chowdhury M.A.K., Christopher D.J., Chu D.-T., Chung M.T., Chung S.-C., Cicuttini F.M., Constantin T.V., Costa V.M., Dahlawi S.M.A., Dai H., Dai X., Damiani G., Dandona L., Dandona R., Daneshpajouhnejad P., Darwesh A.M., Davila-Cervantes C.A., Davletov K., De la Hoz F.P., De Leo D., Dervenis N., Desai R., Desalew A., Deuba K., Dharmaratne S.D., Dhungana G.P., Dianatinasab M., Dias da Silva D., Diaz D., Didarloo A., Djalalinia S., Dorostkar F., Doshi C.P., Doshmangir L., Doyle K.E., Duraes A.R., Ebrahimi Kalan M., Ebtehaj S., Edvardsson D., El Tantawi M., Elgendy I.Y., El-Jaafary S.I., Elsharkawy A., Eshrati B., Eskandarieh S., Esmaeilnejad S., Esmaeilzadeh F., Esteghamati S., Faro A., Farzadfar F., Fattahi N., Feigin V.L., Ferede T.Y., Fereshtehnejad S.-M., Fernandes E., Ferrara P., Filip I., Fischer F., Fisher J.L., Foigt N.A., Folayan M.O., Fomenkov A.A., Foroutan M., Fukumoto T., Gad M.M., Gaidhane A.M., Gallus S., Gebre T., Gebremedhin K.B., Gebremeskel G.G., Gebremeskel L., Gebreslassie A.A., Gesesew H.A., Ghadiri K., Ghafourifard M., Ghamari F., Ghashghaee A., Gilani S.A., Gnedovskaya E.V., Godinho M.A., Golechha M., Goli S., Gona P.N., Gopalani S.V., Gorini G., Grivna M., Gubari M.I.M., Gugnani H.C., Guimaraes R.A., Guo Y., Gupta R., Haagsma J.A., Hafezi-Nejad N., Haile T.G., Haj-Mirzaian A., Hall B.J., Hamadeh R.R., Hamagharib Abdullah K., Hamidi S., Handiso D.W., Hanif A., Hankey G.J., Haririan H., Haro J.M., Hasaballah A.I., Hashi A., Hassan A., Hassanipour S., Hassankhani H., Hayat K., Heidari-Soureshjani R., Herteliu C., Heydarpour F., Ho H.C., Hole M.K., Holla R., Hoogar P., Hosseini M., Hosseinzadeh M., Hostiuc M., Hostiuc S., Househ M., Hsairi M., Huda T.M., Humayun A., Hussain R., Hwang B.-F., Iavicoli I., Ibitoye S.E., Ilesanmi O.S., Ilic I.M., Ilic M.D., Inbaraj 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Lorkowski S., Lotufo P.A., Lunevicius R., Maddison R., Mahasha P.W., Mahdavi M.M., Mahmoudi M., Majeed A., Maleki A., Malekzadeh R., Malta D.C., Mamun A.A., Mansouri B., Mansournia M.A., Martinez G., Martinez-Raga J., Martins-Melo F.R., Mason-Jones A.J., Masoumi S.Z., Mathur M.R., Maulik P.K., McGrath J.J., Mehndiratta M.M., Mehri F., Memiah P.T.N., Mendoza W., Menezes R.G., Mengesha E.W., Meretoja A., Meretoja T.J., Mestrovic T., Miazgowski B., Miazgowski T., Michalek I.M., Miller T.R., Mini G.K., Mirica A., Mirrakhimov E.M., Mirzaei H., Mirzaei M., Moazen B., Mohammad D.K., Mohammadi S., Mohammadian-Hafshejani A., Mohammadifard N., Mohammadpourhodki R., Mohammed S., Monasta L., Moradi G., Moradi-Lakeh M., Moradzadeh R., Moraga P., Morrison S.D., Mosapour A., Mousavi Khaneghah A., Mueller U.O., Muriithi M.K., Murray C.J.L., Muthupandian S., Naderi M., Nagarajan A.J., Naghavi M., Naimzada M.D., Nangia V., Nayak V.C., Nazari J., Ndejjo R., Negoi I., Negoi R.I., Netsere H.B., 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Krishan, K, Kugbey, N, Kumar, G, Kumar, M, Kumar, N, Kurmi, O, Kusuma, D, La Vecchia, C, Lacey, B, Lal, D, Lalloo, R, Lan, Q, Landires, I, Lansingh, V, Larsson, A, Lasrado, S, Lassi, Z, Lauriola, P, Lee, P, Lee, S, Leigh, J, Leonardi, M, Leung, J, Levi, M, Lewycka, S, Li, B, Li, M, Li, S, Lim, L, Lim, S, Liu, X, Lorkowski, S, Lotufo, P, Lunevicius, R, Maddison, R, Mahasha, P, Mahdavi, M, Mahmoudi, M, Majeed, A, Maleki, A, Malekzadeh, R, Malta, D, Mamun, A, Mansouri, B, Mansournia, M, Martinez, G, Martinez-Raga, J, Martins-Melo, F, Mason-Jones, A, Masoumi, S, Mathur, M, Maulik, P, Mcgrath, J, Mehndiratta, M, Mehri, F, Memiah, P, Mendoza, W, Menezes, R, Mengesha, E, Meretoja, A, Meretoja, T, Mestrovic, T, Miazgowski, B, Miazgowski, T, Michalek, I, Miller, T, Mini, G, Mirica, A, Mirrakhimov, E, Mirzaei, H, Mirzaei, M, Moazen, B, Mohammad, D, Mohammadi, S, Mohammadian-Hafshejani, A, Mohammadifard, N, Mohammadpourhodki, R, Mohammed, S, Monasta, L, Moradi, G, Moradi-Lakeh, M, Moradzadeh, R, Moraga, P, Morrison, S, Mosapour, A, Mousavi Khaneghah, A, Mueller, U, Muriithi, M, Murray, C, Muthupandian, S, Naderi, M, Nagarajan, A, Naghavi, M, Naimzada, M, Nangia, V, Nayak, V, Nazari, J, Ndejjo, R, Negoi, I, Negoi, R, Netsere, H, Nguefack-Tsague, G, Nguyen, D, Nguyen, H, Nie, J, Ningrum, D, Nnaji, C, Nomura, S, Noubiap, J, Nowak, C, Nunez-Samudio, V, Ogbo, F, Oghenetega, O, Oh, I, Oladnabi, M, Olagunju, A, Olusanya, B, Olusanya, J, Omar Bali, A, Omer, M, Onwujekwe, O, Ortiz, A, Otoiu, A, Otstavnov, N, Otstavnov, S, Overland, S, Owolabi, M, P A, M, Padubidri, J, Pakshir, K, Palladino, R, Pana, A, Panda-Jonas, S, Pandey, A, Panelo, C, Park, E, Patten, S, Peden, A, Pepito, V, Peprah, E, Pereira, J, Pesudovs, K, Pham, H, Phillips, M, Piradov, M, Pirsaheb, M, Postma, M, Pottoo, F, Pourjafar, H, Pourshams, A, Prada, S, Pupillo, E, Quazi Syed, Z, Rabiee, M, Rabiee, N, Radfar, A, Rafiee, A, Raggi, A, Rahim, F, Rahimi-Movaghar, V, Rahman, M, Ramezanzadeh, K, Ranabhat, C, Rao, S, Rashedi, V, Rastogi, P, Rathi, P, Rawaf, D, Rawaf, S, Rawal, L, Rawassizadeh, R, Renzaho, A, Rezaei, N, Rezai, M, Riahi, S, Rickard, J, Roever, L, Ronfani, L, Roth, G, Rubagotti, E, Rumisha, S, Rwegerera, G, Sabour, S, Sachdev, P, Saddik, B, Sadeghi, E, Saeedi Moghaddam, S, Sagar, R, Sahebkar, A, Sahraian, M, Sajadi, S, Salem, M, Salimzadeh, H, Samy, A, Sanabria, J, Santric-Milicevic, M, Saraswathy, S, Sarrafzadegan, N, Sarveazad, A, Sathish, T, Sattin, D, Saxena, D, Saxena, S, Schiavolin, S, Schwebel, D, Schwendicke, F, Senthilkumaran, S, Sepanlou, S, Sha, F, Shafaat, O, Shahabi, S, Shaheen, A, Shaikh, M, Shakiba, S, Shamsi, M, Shannawaz, M, Sharafi, K, Sheikh, A, Sheikhbahaei, S, Shetty, B, Shi, P, Shigematsu, M, Shin, J, Shiri, R, Shuval, K, Siabani, S, Sigfusdottir, I, Sigurvinsdottir, R, Silva, D, Silva, J, Simonetti, B, Singh, J, Singh, V, Sinke, A, Skryabin, V, Slater, H, Smith, E, Sobhiyeh, M, Sobngwi, E, Soheili, A, Somefun, O, Sorrie, M, Soyiri, I, Sreeramareddy, C, Stein, D, Stokes, M, Sudaryanto, A, Sultan, I, Tabares-Seisdedos, R, Tabuchi, T, Tadakamadla, S, Taherkhani, A, Tamiru, A, Tareque, M, Thankappan, K, Thapar, R, Thomas, N, Titova, M, Tonelli, M, Tovani-Palone, M, Tran, B, Travillian, R, Tsai, A, Tsatsakis, A, Tudor Car, L, Uddin, R, Unim, B, Unnikrishnan, B, Upadhyay, E, Vacante, M, Valadan Tahbaz, S, Valdez, P, Varughese, S, Vasankari, T, Venketasubramanian, N, Villeneuve, P, Violante, F, Vlassov, V, Vos, T, Vu, G, Waheed, Y, Wamai, R, Wang, Y, Westerman, R, Wickramasinghe, N, Wu, A, Wu, C, Yahyazadeh Jabbari, S, Yamagishi, K, Yano, Y, Yaya, S, Yazdi-Feyzabadi, V, Yeshitila, Y, Yip, P, Yonemoto, N, Yoon, S, Younis, M, Yousefinezhadi, T, Yu, C, Yu, Y, Yuce, D, Zaidi, S, Zaman, S, Zamani, M, Zamanian, M, Zarafshan, H, Zarei, A, Zastrozhin, M, Zhang, Y, Zhang, Z, Zhao, X, Zhu, C, Patton, G, and Viner, R
Subjects: Male, Joves -- Mortalitat, ADOLESCENT HEALTH, CHILDREN, Socioeconomic Factor, Global Burden of Disease, RA0421, Cause of Death, Medicine, Young adult, Child, 11 Medical and Health Sciences, Cause of death, education.field_of_study, Adolescent, Age Distribution, Female, Humans, Mortality, Sex Distribution, Socioeconomic Factors, Young Adult, Mortality rate, Public Health, Global Health, Social Medicine and Epidemiology, General Medicine, Articles, Hälsovetenskaper, MIDDLE-INCOME, MENTAL-HEALTH, Adolescent health, INTERVENTIONS, Human, SUICIDE, Total fertility rate, Population, Adolescent Health, Adolescents -- Mortalitat, General & Internal Medicine, Health Sciences, QUALITY, Medicine [Science], Social determinants of health, INCOME COUNTRIES, education, business.industry, TRENDS, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Years of potential life lost, INJURIES, business, Demography
Abstract: Background Documentation of patterns and long-term trends in mortality in young people, which reflect huge changes in demographic and social determinants of adolescent health, enables identification of global investment priorities for this age group. We aimed to analyse data on the number of deaths, years of life lost, and mortality rates by sex and age group in people aged 10–24 years in 204 countries and territories from 1950 to 2019 by use of estimates from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019. Methods We report trends in estimated total numbers of deaths and mortality rate per 100 000 population in young people aged 10–24 years by age group (10–14 years, 15–19 years, and 20–24 years) and sex in 204 countries and territories between 1950 and 2019 for all causes, and between 1980 and 2019 by cause of death. We analyse variation in outcomes by region, age group, and sex, and compare annual rate of change in mortality in young people aged 10–24 years with that in children aged 0–9 years from 1990 to 2019. We then analyse the association between mortality in people aged 10–24 years and socioeconomic development using the GBD Socio-demographic Index (SDI), a composite measure based on average national educational attainment in people older than 15 years, total fertility rate in people younger than 25 years, and income per capita. We assess the association between SDI and all-cause mortality in 2019, and analyse the ratio of observed to expected mortality by SDI using the most recent available data release (2017). Findings In 2019 there were 1·49 million deaths (95% uncertainty interval 1·39–1·59) worldwide in people aged 10–24 years, of which 61% occurred in males. 32·7% of all adolescent deaths were due to transport injuries, unintentional injuries, or interpersonal violence and conflict; 32·1% were due to communicable, nutritional, or maternal causes; 27·0% were due to non-communicable diseases; and 8·2% were due to self-harm. Since 1950, deaths in this age group decreased by 30·0% in females and 15·3% in males, and sex-based differences in mortality rate have widened in most regions of the world. Geographical variation has also increased, particularly in people aged 10–14 years. Since 1980, communicable and maternal causes of death have decreased sharply as a proportion of total deaths in most GBD super-regions, but remain some of the most common causes in sub-Saharan Africa and south Asia, where more than half of all adolescent deaths occur. Annual percentage decrease in all-cause mortality rate since 1990 in adolescents aged 15–19 years was 1·3% in males and 1·6% in females, almost half that of males aged 1–4 years (2·4%), and around a third less than in females aged 1–4 years (2·5%). The proportion of global deaths in people aged 0–24 years that occurred in people aged 10–24 years more than doubled between 1950 and 2019, from 9·5% to 21·6%. Interpretation Variation in adolescent mortality between countries and by sex is widening, driven by poor progress in reducing deaths in males and older adolescents. Improving global adolescent mortality will require action to address the specific vulnerabilities of this age group, which are being overlooked. Furthermore, indirect effects of the COVID-19 pandemic are likely to jeopardise efforts to improve health outcomes including mortality in young people aged 10–24 years. There is an urgent need to respond to the changing global burden of adolescent mortality, address inequities where they occur, and improve the availability and quality of primary mortality data in this age group. Funding Bill & Melinda Gates Foundation.
Published: 2021

8. Mapping routine measles vaccination in low- and middle-income countries

Author: Sbarra, AN, Rolfe, S, Nguyen, JQ, Earl, L, Galles, NC, Marks, A, Abbas, KM, Abbasi-Kangevari, M, Abbastabar, H, Abd-Allah, F, Abdelalim, A, Abdollahi, M, Abegaz, KH, Abiy, HAA, Abolhassani, H, Abreu, LG, Abrigo, MRM, Abushouk, AI, Accrombessi, MMK, Adabi, M, Adebayo, OM, Adekanmbi, V, Adetokunboh, OO, Adham, D, Afarideh, M, Aghaali, M, Ahmad, T, Ahmadi, R, Ahmadi, K, Ahmed, MB, Alanezi, FM, Alanzi, TM, Alcalde-Rabanal, JE, Alemnew, BT, Ali, BA, Ali, M, Alijanzadeh, M, Alinia, C, Alipoor, R, Alipour, V, Alizade, H, Aljunid, SM, Almasi, A, Almasi-Hashiani, A, Al-Mekhlafi, HM, Altirkawi, KA, Amare, B, Amini, S, Amini-Rarani, M, Amiri, F, Amit, AML, Amugsi, DA, Ancuceanu, R, Andrei, CL, Anjomshoa, M, Ansari, F, Ansari-Moghaddam, A, Ansha, MG, Antonio, CAT, Antriyandarti, E, Anvari, D, Arabloo, J, Arab-Zozani, M, Aremu, O, Armoon, B, Aryal, KK, Arzani, A, Asadi-Aliabadi, M, Asgari, S, Atafar, Z, Ausloos, M, Awoke, N, Quintanilla, BPA, Ayanore, MA, Aynalem, YA, Azadmehr, A, Azari, S, Babaee, E, Badawi, A, Badiye, AD, Bahrami, MA, Baig, AA, Bakhtiari, A, Balakrishnan, S, Banach, M, Banik, PC, Barac, A, Baradaran-Seyed, Z, Baraki, AG, Basu, S, Bayati, M, Bayou, YT, Bedi, N, Behzadifar, M, Bell, ML, Berbada, DA, Berhe, K, Bhattarai, S, Bhutta, ZA, Bijani, A, Birhanu, M, Bisanzio, D, Biswas, A, Bohlouli, S, Bolla, SR, Borzouei, S, Brady, OJ, Bragazzi, NL, Briko, AN, Briko, NI, Nagaraja, SB, Butt, ZA, Cámera, LA, Campos-Nonato, IR, Car, J, Cárdenas, R, Carvalho, F, Castaldelli-Maia, JM, Castro, F, Chattu, VK, Chehrazi, M, Chin, KL, Chu, D-T, Cook, AJ, Cormier, NM, Cunningham, B, Dahlawi, SMA, Damiani, G, Dandona, R, Dandona, L, Danovaro, MC, Dansereau, E, Daoud, F, Darwesh, AM, Darwish, AH, Das, JK, Weaver, ND, De Neve, J-W, Demeke, FM, Demis, AB, Denova-Gutiérrez, E, Desalew, A, Deshpande, A, Desta, DM, Dharmaratne, SD, Dhungana, GP, Dianatinasab, M, Diaz, D, Dipeolu, IO, Djalalinia, S, Do, HT, Dorostkar, F, Doshmangir, L, Doyle, KE, Dunachie, SJ, Duraes, AR, Kalan, ME, Leylabadlo, HE, Edinur, HA, Effiong, A, Eftekhari, A, El, Sayed, I, El, Sayed, Zaki, M, Elema, TB, Elhabashy, HR, El-Jaafary, SI, Elsharkawy, A, Emamian, MH, Enany, S, Eshrati, B, Eskandari, K, Eskandarieh, S, Esmaeilnejad, S, Esmaeilzadeh, F, Esteghamati, A, Etisso, AE, Farahmand, M, Faraon, EJA, Fareed, M, Faridnia, R, Farioli, A, Farzadfar, F, Fattahi, N, Fazlzadeh, M, Fereshtehnejad, S-M, Fernandes, E, Filip, I, Fischer, F, Foigt, NA, Folayan, MO, Foroutan, M, Fukumoto, T, Fullman, N, Gad, MM, Geberemariyam, BS, Gebrehiwot, TT, Gebrehiwot, AM, Gebremariam, KT, Gebremedhin, KB, Gebremeskel, GG, Gebreslassie, AA, Gedefaw, GA, Gezae, KE, Ghadiri, K, Ghaffari, R, Ghaffarifar, F, Ghajarzadeh, M, Gheshlagh, RG, Ghashghaee, A, Ghiasvand, H, Gholamian, A, Gilani, SA, Gill, PS, Girmay, A, Gomes, NGM, Gopalani, SV, Goulart, BNG, Grada, A, Guimarães, RA, Guo, Y, Gupta, R, Hafezi-Nejad, N, Haj-Mirzaian, A, Handiso, DW, Hanif, A, Haririan, H, Hasaballah, AI, Hasan, MM, Hasanpoor, E, Hasanzadeh, A, Hassanipour, S, Hassankhani, H, Heidari-Soureshjani, R, Henry, NJ, Herteliu, C, Heydarpour, F, Hollerich, GI, Rad, EH, Hoogar, P, Hossain, N, Hosseini, M, Hosseinzadeh, M, Househ, M, Hu, G, Huda, TM, Humayun, A, Ibitoye, SE, Ikilezi, G, Ilesanmi, OS, Ilic, IM, Ilic, MD, Imani-Nasab, MH, Inbaraj, LR, Iqbal, U, Irvani, SSN, Islam, SMS, Islam, MM, Iwu, CJ, Iwu, CCD, Jadidi-Niaragh, F, Jafarinia, M, Jahanmehr, N, Jakovljevic, M, Jalali, A, Jalilian, F, Javidnia, J, Jenabi, E, Jha, V, Ji, JS, John, O, Johnson, KB, Joukar, F, Jozwiak, JJ, Kabir, Z, Kabir, A, Kalani, H, Kalankesh, LR, Kalhor, R, Kamal, Z, Kanchan, T, Kapoor, N, Karami, M, Matin, BK, Karch, A, Karimi, SE, Kayode, GA, Karyani, AK, Keiyoro, PN, Khader, YS, Khafaie, MA, Khammarnia, M, Khan, MS, Khan, EA, Khan, J, Khan, MN, Khatab, K, Khater, MM, Khatib, MN, Khayamzadeh, M, Khazaei, M, Khazaei, S, Khosravi, A, Khubchandani, J, Kianipour, N, Kim, YJ, Kimokoti, RW, Kinyoki, DK, Kisa, A, Kisa, S, Kolola, T, Komaki, H, Kosen, S, Koul, PA, Koyanagi, A, Kraemer, MUG, Krishan, K, Kuate Defo, B, Kumar, M, Kumar, P, Kumar, GA, Kusuma, D, La Vecchia, C, Lacey, B, Lad, SD, Lal, DK, Lam, F, Lami, FH, Lansingh, VC, Larson, HJ, Lasrado, S, Lee, SWH, Lee, PH, LeGrand, KE, Lenjebo, TL, Li, S, Liang, X, Liu, PY, Lopukhov, PD, Machado, DB, Mahasha, PW, Mahdavi, MM, Maheri, M, Mahotra, NB, Maled, V, Maleki, S, Malik, MA, Malta, DC, Mansour-Ghanaei, F, Mansouri, B, Mansourian, M, Mansournia, MA, Martins-Melo, FR, Masaka, A, Mayala, BK, Mehndiratta, MM, Mehri, F, Mehta, KM, Memiah, PTN, Mendoza, W, Menezes, RG, Mengesha, MB, Mengesha, EW, Mestrovic, T, Mihretie, KM, Miller-Petrie, MK, Mills, EJ, Milne, GJ, Mirabi, P, Mirrakhimov, EM, Mirzaei, R, Mirzaei, M, Mirzaei, HR, Mirzaei, H, Mirzaei-Alavijeh, M, Moazen, B, Moghadaszadeh, M, Mohamadi, E, Mohammad, DK, Mohammad, Y, Mohammad, KA, Mohammad Gholi Mezerji, N, Mohammadbeigi, A, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, S, Mohammed, AS, Mohammed, H, Mohebi, F, Mokdad, AH, Monasta, L, Moosavi, MA, Moosazadeh, M, Moradi, G, Moradi, M, Moradi-Joo, M, Moradi-Lakeh, M, Moradzadeh, R, Moraga, P, Mosapour, A, Mouodi, S, Mousavi, SM, Khaneghah, AM, Mueller, UO, Muluneh, AG, Munro, SB, Murray, CJL, Murthy, GVS, Muthupandian, S, Naderi, M, Nagarajan, AJ, Naghavi, M, Nangia, V, Nansseu, JR, Nayak, VC, Nazari, J, Ndwandwe, DE, Negoi, I, Ngunjiri, JW, Nguyen, HLT, Nguyen, CTK, Nguyen, TH, Nigatu, YT, Nikbakhsh, R, Nikfar, S, Nikpoor, AR, Ningrum, DNA, Nnaji, CA, Oh, I-H, Oladnabi, M, Olagunju, AT, Olusanya, JO, Olusanya, BO, Bali, AO, Omer, MO, Onwujekwe, OE, Osgood-Zimmerman, AE, Owolabi, MO, P, A, M, Padubidri, JR, Pakshir, K, Pana, A, Pandey, A, Pando-Robles, V, Pashaei, T, Pasupula, DK, Paternina-Caicedo, AJ, Patton, GC, Pazoki Toroudi, H, Pepito, VCF, Pescarini, JM, Pigott, DM, Pilgrim, T, Pirsaheb, M, Poljak, M, Postma, MJ, Pourjafar, H, Pourmalek, F, Pourmirza, Kalhori, R, Prada, SI, Prakash, S, Quazi Syed, Z, Quintana, H, Rabiee, N, Rabiee, M, Radfar, A, Rafiei, A, Rahim, F, Rajati, F, Rameto, MA, Ramezanzadeh, K, Ranabhat, CL, Rao, SJ, Rasella, D, Rastogi, P, Rathi, P, Rawaf, S, Rawaf, DL, Rawal, L, Rawassizadeh, R, Rawat, R, Renjith, V, Renzaho, AMN, Reshmi, B, Reta, MA, Rezaei, N, Rezai, MS, Rezapour, A, Riahi, SM, Ribeiro, AI, Rickard, J, Rios-Blancas, M, Rios-González, CM, Roever, L, Rostamian, M, Rubino, S, Rwegerera, GM, Saad, AM, Saadatagah, S, Sabour, S, Sadeghi, E, Moghaddam, SS, Saeidi, S, Sagar, R, Sahebkar, A, Sahraian, MA, Sajadi, SM, Salahshoor, MR, Salam, N, Salem, H, Salem, MR, Salomon, JA, Kafil, HS, Sambala, EZ, Samy, AM, Saraswathy, SYI, Sarmiento-Suárez, R, Saroshe, S, Sartorius, B, Sarveazad, A, Sathian, B, Sathish, T, Schaeffer, LE, Schwebel, DC, Senthilkumaran, S, Shabaninejad, H, Shahabi, S, Shaheen, AA, Shaikh, MA, Shalash, AS, Shams-Beyranvand, M, Shamsi, MB, Shamsizadeh, M, Sharafi, K, Sharifi, H, Sheikh, A, Sheikhtaheri, A, Shetty, RS, Shiferaw, WS, Shigematsu, M, Shin, JI, Shirkoohi, R, Siabani, S, Siddiqi, TJ, Silverberg, JIS, Simonetti, B, Singh, JA, Sinha, DN, Sinke, AH, Soheili, A, Sokhan, A, Soltani, S, Soofi, M, Sorrie, MB, Soyiri, IN, Spotin, A, Spurlock, EE, Sreeramareddy, CT, Sudaryanto, A, Sufiyan, MB, Suleria, HAR, Abdulkader, RS, Taherkhani, A, Tapak, L, Taveira, N, Taymoori, P, Tefera, YM, Tehrani-Banihashemi, A, Teklehaimanot, BF, Tekulu, GH, Tesfay, BE, Tessema, ZT, Tessema, B, Thankappan, KR, Tohidinik, HR, Topor-Madry, R, Tovani-Palone, MR, Tran, BX, Uddin, R, Ullah, I, Umeokonkwo, CD, Unnikrishnan, B, Upadhyay, E, Usman, MS, Vaezi, M, Valadan, Tahbaz, S, Valdez, PR, Vasseghian, Y, Veisani, Y, Violante, FS, Vollmer, S, Waheed, Y, Wakefield, J, Wang, Y, Wang, Y-P, Weldesamuel, GT, Werdecker, A, Westerman, R, Wiangkham, T, Wiens, KE, Wiysonge, CS, Woldu, G, Wondafrash, DZ, Wonde, TE, Wu, A-M, Yadollahpour, A, Jabbari, SHY, Yamada, T, Yaya, S, Yazdi-Feyzabadi, V, Yeheyis, TY, Yeshaw, Y, Yilgwan, CS, Yip, P, Yonemoto, N, Younis, MZ, Yousefi, Z, Yousefifard, M, Yousefinezhadi, T, Yu, C, Yusefzadeh, H, Zadey, S, Zahirian, Moghadam, T, Zaki, L, Zaman, SB, Zamani, M, Zamanian, M, Zandian, H, Zangeneh, A, Zarei, F, Zerfu, TA, Zhang, Y, Zhang, Z-J, Zhao, X-JG, Zhou, M, Ziapour, A, Hay, SI, Lim, SS, Mosser, JF, Local Burden of Disease Vaccine Coverage Collaborators, Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Value, Affordability and Sustainability (VALUE), Microbes in Health and Disease (MHD), HUS Comprehensive Cancer Center, Clinicum, Department of Oncology, Sbarra, Alyssa N., Rolfe, Sam, Nguyen, Jason Q., Earl, Lucas, Ahmed, MB, Mosser, Jonathan F, Collaborators, Local Burden of Disease Vaccine Coverage, Bill & Melinda Gates Foundation, Alexander von Humboldt-Stiftung, Unión Europea. Fondo Europeo de Desarrollo Regional (FEDER/ERDF), Universiti Sains Malaysia (Malasia), Panjab University (India), NIHR - Oxford Biomedical Research Centre (Reino Unido), Australian Research Council, Instituto de Saúde Pública da Universidade do Porto, Local Burden Dis Educ Attainment C, Local Burden of Disease Vaccine Coverage Collaborator, and Violante FS
Subjects: and promotion of well-being, Vacunación Masiva, Internationality, Disease prevention, children under 5 years old, Geographic Mapping, Rural Health, medicine.disease_cause, Cross-reactivity, 0302 clinical medicine, RA0421, Vaccination Refusal, 030212 general & internal medicine, Child, immunity patterns, Pediatric, 0303 health sciences, Public health, Multidisciplinary, biology, Vaccination, Uncertainty, IMMUNIZATION, 3142 Public health care science, environmental and occupational health, COVERAGE, 3. Good health, TIME, 3.4 Vaccines, Child, Preschool, Infectious diseases, A990 Medicine and Dentistry not elsewhere classified, Antibody, Engineering sciences. Technology, AFRICA, General Science & Technology, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), COVID-19, 610 Medicine & health, Global Vaccine Action Plan (GVAP), Local Burden of Disease Vaccine Coverage Collaborators, Article, Vaccine Related, 03 medical and health sciences, measles vaccine, Measels, Low- and middle-income countries, Local burden of disease, Clinical Research, medicine, Humans, Healthcare Disparities, Preschool, PROGRESS, 030304 developmental biology, business.industry, MORTALITY, Developed Countries, Prevention, Comment, Vacunación, Urban Health, Prevention of disease and conditions, Virology, Coronavirus, Good Health and Well Being, Cobertura de Vacunación, biology.protein, Immunization, business, Measles
Abstract: The safe, highly effective measles vaccine has been recommended globally since 1974, yet in 2017 there were more than 17 million cases of measles and 83,400 deaths in children under 5 years old, and more than 99% of both occurred in low- and middle-income countries (LMICs)1–4. Globally comparable, annual, local estimates of routine first-dose measles-containing vaccine (MCV1) coverage are critical for understanding geographically precise immunity patterns, progress towards the targets of the Global Vaccine Action Plan (GVAP), and high-risk areas amid disruptions to vaccination programmes caused by coronavirus disease 2019 (COVID-19)5–8. Here we generated annual estimates of routine childhood MCV1 coverage at 5 × 5-km2 pixel and second administrative levels from 2000 to 2019 in 101 LMICs, quantified geographical inequality and assessed vaccination status by geographical remoteness. After widespread MCV1 gains from 2000 to 2010, coverage regressed in more than half of the districts between 2010 and 2019, leaving many LMICs far from the GVAP goal of 80% coverage in all districts by 2019. MCV1 coverage was lower in rural than in urban locations, although a larger proportion of unvaccinated children overall lived in urban locations; strategies to provide essential vaccination services should address both geographical contexts. These results provide a tool for decision-makers to strengthen routine MCV1 immunization programmes and provide equitable disease protection for all children., Although progress in the coverage of routine measles vaccination in children in low- and middle-income countries was made during 2000–2019, many countries remain far from the goal of 80% coverage in all districts by 2019.
Published: 2021

9. Mapping subnational HIV mortality in six Latin American countries with incomplete vital registration systems

Author: Cork, MA, Henry, NJ, Watson, S, Croneberger, AJ, Baumann, M, Letourneau, ID, Yang, M, Serfes, AL, Abbas, J, Abbasi, N, Abbastabar, H, Abreu, LG, Abu-Gharbieh, E, Achappa, B, Adabi, M, Adal, TG, Adegbosin, AE, Adekanmbi, V, Adetokunboh, OO, Agudelo-Botero, M, Ahinkorah, BO, Ahmadi, K, Ahmed, MB, Alhassan, RK, Alipour, V, Almasi-Hashiani, A, Alvis-Guzman, N, Ancuceanu, R, Andrei, T, Anvari, D, Aqeel, M, Arabloo, J, Aremu, O, Asaad, M, Atnafu, DD, Atreya, A, Quintanilla, BPA, Azari, S, Darshan, BB, Baig, AA, Banach, M, Bante, SA, Barboza, MA, Basu, S, Bedi, N, Bejarano Ramirez, DF, Bensenor, IM, Beyene, FY, Bezabih, YM, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bhutta, ZA, Bijani, A, Birlik, SM, Bitew, ZW, Bohlouli, S, Boloor, A, Brunoni, AR, Butt, ZA, Cardenas, R, Carvalho, F, Castaldelli-Maia, JM, Castaneda-Orjuela, CA, Charan, J, Chatterjee, S, Chattu, VK, Chattu, SK, Chowdhury, MAK, Christopher, DJ, Chu, D-T, Cook, AJ, Cormier, NM, Dahlawi, SMA, Daoud, F, Davila Cervantes, CA, Weaver, ND, De la Hoz, FP, Demeke, FM, Denova-Gutierrez, E, Deribe, K, Deuba, K, Dharmaratne, SD, Dhungana, GP, Diaz, D, Djalalinia, S, Duraes, AR, Eagan, AW, Earl, L, Effiong, A, Zaki, MES, El Tantawi, M, Elayedath, R, El-Jaafary, SI, Faraon, EJA, Faro, A, Fattahi, N, Fauk, NK, Fernandes, E, Filip, I, Fischer, F, Foigt, NA, Foroutan, M, Fukumoto, T, Gad, MM, Gebremariam, TBB, Gebremedhin, KB, Gebremeskel, GG, Gesesew, HA, Ghadiri, K, Ghashghaee, A, Gilani, SA, Golechha, M, Gori, U, Goulart, AC, Goulart, BNG, Gugnani, HC, Guimaraes, MDC, Guimaraes, RA, Guo, Y, Gupta, R, Haeuser, E, Haider, MR, Haile, TG, Haj-Mirzaian, A, Hanif, A, Hargono, A, Hariyani, N, Hassanipour, S, Hassankhani, H, Hayat, K, Herteliu, C, Ho, HC, Holla, R, Hosseinzadeh, M, Househ, M, Hwang, BF, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, MD, Ilic, IM, Iqbal, U, Jahagirdar, D, Jain, V, Jakovljevic, M, Jha, RP, Johnson, KB, Joseph, N, Joukar, F, Kalankesh, LR, Kalhor, R, Kanchan, T, Matin, BK, Karch, A, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keramati, M, Khalid, N, Khan, EA, Khan, G, Khan, MNN, Khatab, K, Kianipour, N, Kim, YJ, Kisa, S, Kisa, A, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Defo, BK, Kuchenbecker, RS, Kulkarni, V, Kumar, N, Kumar, M, Kurmi, OP, Kusuma, D, La Vecchia, C, Lal, DK, Landires, I, Lasrado, S, Lee, PH, LeGrand, KE, Li, B, Li, S, Liu, X, Amin, HIM, Machado, DB, Madi, D, Magis-Rodriguez, C, Malta, DC, Mansournia, MA, Manzar, MD, Marrugo Arnedo, CA, Martins-Melo, FR, Masoumi, SZ, Mayala, BK, Medina-Solis, CE, Memish, ZA, Mendoza, W, Menezes, RG, Mestrovic, T, Mirica, A, Moazen, B, Mohammad, Y, Mezerji, NMG, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, S, Mokdad, AH, Moni, MA, Moradi, M, Moradi, Y, Moradzadeh, R, Moraga, P, Khaneghah, AM, Mustafa, G, Mwanri, L, Nagaraja, R, Nagarajan, AJ, Naimzada, MD, Nascimento, BR, Naveed, M, Nayak, VC, Nazari, J, Negash, H, Negoi, I, Nepal, S, Nguefack-Tsague, G, Nguyen, CT, Nguyen, HLT, Nikbakhsh, R, Noubiap, JJ, Nunez-Samudio, V, Oancea, B, Ogbo, FA, Olagunju, AT, Otstavnov, N, Mahesh, PA, Padubidri, JR, Perumal, SRP, Pardo-Montano, AM, Patel, UK, Pawar, S, Peprah, EK, Pereira, A, Perkins, S, Pescarini, JM, Pokhrel, KN, Postma, MJ, Pottoo, FH, Prada, SI, Preotescu, L, Pribadi, DRA, Radfar, A, Rahim, F, Rahman, MHU, Rahmani, AM, Ramezanzadeh, K, Rana, J, Ranabhat, CL, Rao, SJ, Rathi, P, Rawaf, S, Rawaf, DL, Rawassizadeh, R, Renjith, V, Rezaei, N, Rezapour, A, Ribeiro, AI, Roever, L, Rubagotti, E, Rumisha, SF, Rwegerera, GM, Sagar, R, Sajadi, SM, Salem, MR, Samy, AM, Sarmiento-Suarez, R, Sathian, B, Schaeffer, LE, Schneider, IJC, Seidu, A-A, Sha, F, Shaikh, MA, Sharafi, K, Sheikh, A, Shibuya, K, Shin, JI, Silva, DAS, Singh, JA, Skryabin, VY, Skryabina, AA, Sligar, A, Soheili, A, Steuben, KM, Sufiyan, MB, Tadesse, EG, Tesema, AKT, Tesfay, FH, Thapar, R, Thompson, RL, Tovani-Palone, MR, Tran, BX, Tsegaye, GW, Umeokonkwo, CD, Unnikrishnan, B, Vasseghian, Y, Violante, FS, Vo, B, Vu, GT, Waheed, Y, Wang, Y-P, Wang, Y, Ward, P, Welay, FT, Westerman, R, Wickramasinghe, ND, Yaya, S, Yip, P, Yonemoto, N, Yu, C, Yuce, D, Yusefzadeh, H, Zamanian, M, Zastrozhin, MS, Zhang, Z-J, Zhang, Y, Ziapour, A, Hay, SI, Dwyer-Lindgren, L, Cork, MA, Henry, NJ, Watson, S, Croneberger, AJ, Baumann, M, Letourneau, ID, Yang, M, Serfes, AL, Abbas, J, Abbasi, N, Abbastabar, H, Abreu, LG, Abu-Gharbieh, E, Achappa, B, Adabi, M, Adal, TG, Adegbosin, AE, Adekanmbi, V, Adetokunboh, OO, Agudelo-Botero, M, Ahinkorah, BO, Ahmadi, K, Ahmed, MB, Alhassan, RK, Alipour, V, Almasi-Hashiani, A, Alvis-Guzman, N, Ancuceanu, R, Andrei, T, Anvari, D, Aqeel, M, Arabloo, J, Aremu, O, Asaad, M, Atnafu, DD, Atreya, A, Quintanilla, BPA, Azari, S, Darshan, BB, Baig, AA, Banach, M, Bante, SA, Barboza, MA, Basu, S, Bedi, N, Bejarano Ramirez, DF, Bensenor, IM, Beyene, FY, Bezabih, YM, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhattacharyya, K, Bhutta, ZA, Bijani, A, Birlik, SM, Bitew, ZW, Bohlouli, S, Boloor, A, Brunoni, AR, Butt, ZA, Cardenas, R, Carvalho, F, Castaldelli-Maia, JM, Castaneda-Orjuela, CA, Charan, J, Chatterjee, S, Chattu, VK, Chattu, SK, Chowdhury, MAK, Christopher, DJ, Chu, D-T, Cook, AJ, Cormier, NM, Dahlawi, SMA, Daoud, F, Davila Cervantes, CA, Weaver, ND, De la Hoz, FP, Demeke, FM, Denova-Gutierrez, E, Deribe, K, Deuba, K, Dharmaratne, SD, Dhungana, GP, Diaz, D, Djalalinia, S, Duraes, AR, Eagan, AW, Earl, L, Effiong, A, Zaki, MES, El Tantawi, M, Elayedath, R, El-Jaafary, SI, Faraon, EJA, Faro, A, Fattahi, N, Fauk, NK, Fernandes, E, Filip, I, Fischer, F, Foigt, NA, Foroutan, M, Fukumoto, T, Gad, MM, Gebremariam, TBB, Gebremedhin, KB, Gebremeskel, GG, Gesesew, HA, Ghadiri, K, Ghashghaee, A, Gilani, SA, Golechha, M, Gori, U, Goulart, AC, Goulart, BNG, Gugnani, HC, Guimaraes, MDC, Guimaraes, RA, Guo, Y, Gupta, R, Haeuser, E, Haider, MR, Haile, TG, Haj-Mirzaian, A, Hanif, A, Hargono, A, Hariyani, N, Hassanipour, S, Hassankhani, H, Hayat, K, Herteliu, C, Ho, HC, Holla, R, Hosseinzadeh, M, Househ, M, Hwang, BF, Ibeneme, CU, Ibitoye, SE, Ilesanmi, OS, Ilic, MD, Ilic, IM, Iqbal, U, Jahagirdar, D, Jain, V, Jakovljevic, M, Jha, RP, Johnson, KB, Joseph, N, Joukar, F, Kalankesh, LR, Kalhor, R, Kanchan, T, Matin, BK, Karch, A, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keramati, M, Khalid, N, Khan, EA, Khan, G, Khan, MNN, Khatab, K, Kianipour, N, Kim, YJ, Kisa, S, Kisa, A, Kosen, S, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Defo, BK, Kuchenbecker, RS, Kulkarni, V, Kumar, N, Kumar, M, Kurmi, OP, Kusuma, D, La Vecchia, C, Lal, DK, Landires, I, Lasrado, S, Lee, PH, LeGrand, KE, Li, B, Li, S, Liu, X, Amin, HIM, Machado, DB, Madi, D, Magis-Rodriguez, C, Malta, DC, Mansournia, MA, Manzar, MD, Marrugo Arnedo, CA, Martins-Melo, FR, Masoumi, SZ, Mayala, BK, Medina-Solis, CE, Memish, ZA, Mendoza, W, Menezes, RG, Mestrovic, T, Mirica, A, Moazen, B, Mohammad, Y, Mezerji, NMG, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, S, Mokdad, AH, Moni, MA, Moradi, M, Moradi, Y, Moradzadeh, R, Moraga, P, Khaneghah, AM, Mustafa, G, Mwanri, L, Nagaraja, R, Nagarajan, AJ, Naimzada, MD, Nascimento, BR, Naveed, M, Nayak, VC, Nazari, J, Negash, H, Negoi, I, Nepal, S, Nguefack-Tsague, G, Nguyen, CT, Nguyen, HLT, Nikbakhsh, R, Noubiap, JJ, Nunez-Samudio, V, Oancea, B, Ogbo, FA, Olagunju, AT, Otstavnov, N, Mahesh, PA, Padubidri, JR, Perumal, SRP, Pardo-Montano, AM, Patel, UK, Pawar, S, Peprah, EK, Pereira, A, Perkins, S, Pescarini, JM, Pokhrel, KN, Postma, MJ, Pottoo, FH, Prada, SI, Preotescu, L, Pribadi, DRA, Radfar, A, Rahim, F, Rahman, MHU, Rahmani, AM, Ramezanzadeh, K, Rana, J, Ranabhat, CL, Rao, SJ, Rathi, P, Rawaf, S, Rawaf, DL, Rawassizadeh, R, Renjith, V, Rezaei, N, Rezapour, A, Ribeiro, AI, Roever, L, Rubagotti, E, Rumisha, SF, Rwegerera, GM, Sagar, R, Sajadi, SM, Salem, MR, Samy, AM, Sarmiento-Suarez, R, Sathian, B, Schaeffer, LE, Schneider, IJC, Seidu, A-A, Sha, F, Shaikh, MA, Sharafi, K, Sheikh, A, Shibuya, K, Shin, JI, Silva, DAS, Singh, JA, Skryabin, VY, Skryabina, AA, Sligar, A, Soheili, A, Steuben, KM, Sufiyan, MB, Tadesse, EG, Tesema, AKT, Tesfay, FH, Thapar, R, Thompson, RL, Tovani-Palone, MR, Tran, BX, Tsegaye, GW, Umeokonkwo, CD, Unnikrishnan, B, Vasseghian, Y, Violante, FS, Vo, B, Vu, GT, Waheed, Y, Wang, Y-P, Wang, Y, Ward, P, Welay, FT, Westerman, R, Wickramasinghe, ND, Yaya, S, Yip, P, Yonemoto, N, Yu, C, Yuce, D, Yusefzadeh, H, Zamanian, M, Zastrozhin, MS, Zhang, Z-J, Zhang, Y, Ziapour, A, Hay, SI, and Dwyer-Lindgren, L
Abstract: BACKGROUND: Human immunodeficiency virus (HIV) remains a public health priority in Latin America. While the burden of HIV is historically concentrated in urban areas and high-risk groups, subnational estimates that cover multiple countries and years are missing. This paucity is partially due to incomplete vital registration (VR) systems and statistical challenges related to estimating mortality rates in areas with low numbers of HIV deaths. In this analysis, we address this gap and provide novel estimates of the HIV mortality rate and the number of HIV deaths by age group, sex, and municipality in Brazil, Colombia, Costa Rica, Ecuador, Guatemala, and Mexico. METHODS: We performed an ecological study using VR data ranging from 2000 to 2017, dependent on individual country data availability. We modeled HIV mortality using a Bayesian spatially explicit mixed-effects regression model that incorporates prior information on VR completeness. We calibrated our results to the Global Burden of Disease Study 2017. RESULTS: All countries displayed over a 40-fold difference in HIV mortality between municipalities with the highest and lowest age-standardized HIV mortality rate in the last year of study for men, and over a 20-fold difference for women. Despite decreases in national HIV mortality in all countries-apart from Ecuador-across the period of study, we found broad variation in relative changes in HIV mortality at the municipality level and increasing relative inequality over time in all countries. In all six countries included in this analysis, 50% or more HIV deaths were concentrated in fewer than 10% of municipalities in the latest year of study. In addition, national age patterns reflected shifts in mortality to older age groups-the median age group among decedents ranged from 30 to 45 years of age at the municipality level in Brazil, Colombia, and Mexico in 2017. CONCLUSIONS: Our subnational estimates of HIV mortality revealed significant spatial variation and divergi
Published: 2021

10. Tracking development assistance for health and for COVID-19: a review of development assistance, government, out-of-pocket, and other private spending on health for 204 countries and territories, 1990-2050

Author: Micah, AE, Cogswell, IE, Cunningham, B, Ezoe, S, Harle, AC, Maddison, ER, McCracken, D, Nomura, S, Simpson, KE, Stutzman, HN, Tsakalos, G, Wallace, LE, Zhao, Y, Zende, RR, Abbafati, C, Abdelmasseh, M, Abedi, A, Abegaz, KH, Abhilash, ES, Abolhassani, H, Abrigo, MRM, Adhikari, TB, Afzal, S, Ahinkorah, BO, Ahmadi, S, Ahmed, H, Ahmed, MB, Rashid, TA, Ajami, M, Aji, B, Akalu, Y, Akunna, CJ, Al Hamad, H, Alam, K, Alanezi, FM, Alanzi, TM, Alemayehu, Y, Alhassan, RK, Alinia, C, Aljunid, SM, Almustanyir, SA, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amini, S, Amini-Rarani, M, Amu, H, Ancuceanu, R, Andrei, CL, Andrei, T, Angell, B, Anjomshoa, M, Antonio, CAT, Antony, CM, Aqeel, M, Arabloo, J, Arab-Zozani, M, Aripov, T, Arrigo, A, Ashraf, T, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Awan, AT, Ayano, G, Ayanore, MA, Azari, S, Azhar, GS, Babalola, TK, Bahrami, MA, Baig, AA, Banach, M, Barati, N, Barnighausen, TW, Barrow, A, Basu, S, Baune, BT, Bayati, M, Benzian, H, Berman, AE, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bibi, S, Bijani, A, Bodolica, V, Bragazzi, NL, Braithwaite, D, Breitborde, NJK, Breusov, AV, Briko, NI, Busse, R, Cahuana-Hurtado, L, Callander, EJ, Camera, LA, Castaneda-Orjuela, CA, Catala-Lopez, F, Charan, J, Chatterjee, S, Chattu, SK, Chattu, VK, Chen, S, Cicero, AFG, Dadras, O, Dahlawi, SMA, Dai, X, Dalal, K, Dandona, L, Dandona, R, Davitoiu, DV, De Neve, J-W, de Sa-Junior, AR, Denova-Gutierrez, E, Dhamnetiya, D, Dharmaratne, SD, Doshmangir, L, Dube, J, Ehsani-Chimeh, E, Zaki, MES, El Tantawi, M, Eskandarieh, S, Farzadfar, F, Ferede, TY, Fischer, F, Foigt, NA, Freitas, A, Friedman, SD, Fukumoto, T, Fullman, N, Gaal, PA, Gad, MM, Garcia-Gordillo, MA, Garg, T, Ghafourifard, M, Ghashghaee, A, Gholamian, A, Gholamrezanezhad, A, Ghozali, G, Gilani, SA, Glavan, I-R, Glushkova, EV, Goharinezhad, S, Golechha, M, Goli, S, Guha, A, Gupta, VB, Gupta, VK, Haakenstad, A, Haider, MR, Hailu, A, Hamidi, S, Hanif, A, Harapan, H, Hartono, RK, Hasaballah, AI, Hassan, S, Hassanein, MH, Hayat, K, Hegazy, MI, Heidari, G, Hendrie, D, Heredia-Pi, I, Herteliu, C, Hezam, K, Holla, R, Hossain, SJ, Hosseinzadeh, M, Hostiuc, S, Huda, TM, Hwang, B-F, Iavicoli, I, Idrisov, B, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ismail, NE, Isola, G, Jahani, MA, Jahanmehr, N, Jakovljevic, M, Janodia, MD, Javaheri, T, Jayapal, SK, Jayawardena, R, Jazayeri, SB, Jha, RP, Jonas, JB, Joo, T, Joukar, F, Jurisson, M, Kaambwa, B, Kalhor, R, Kanchan, T, Kandel, H, Matin, BK, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keikavoosi-Arani, L, Khader, YS, Khajuria, H, Khalilov, R, Khammarnia, M, Khan, J, Khubchandani, J, Kianipour, N, Kim, GR, Kim, YJ, Kisa, A, Kisa, S, Kohler, S, Kosen, S, Koteeswaran, R, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kumar, GA, Kusuma, D, Lamnisos, D, Lansingh, VC, Larsson, AO, Lasrado, S, Le, LKD, Lee, SWH, Lee, YY, Lim, SS, Lobo, SW, Lozano, R, Abd El Razek, HM, Abd El Razek, MM, Mahdavi, MM, Majeed, A, Makki, A, Maleki, A, Malekzadeh, R, Manda, AL, Mansour-Ghanaei, F, Mansournia, MA, Arnedo, CAM, Martinez-Valle, A, Masoumi, SZ, Maude, RJ, Mckee, M, Medina-Solis, CE, Menezes, RG, Meretoja, A, Meretoja, TJ, Mesregah, MK, Mestrovic, T, Kostova, NM, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Mohajer, B, Mohamed, TA, Mohammadi, M, Mohammadian-Hafshejani, A, Mohammed, S, Moitra, M, Mokdad, AH, Molokhia, M, Moni, MA, Moradi, Y, Morze, J, Mousavi, SM, Mpundu-Kaambwa, C, Muriithi, MK, Muthupandian, S, Nagarajan, AJ, Naimzada, MD, Nangia, V, Naqvi, AA, Narayana, AI, Nascimento, BR, Naveed, M, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, I, Kandel, SN, Trang, HN, Nonvignon, J, Noubiap, JJ, Nwatah, VE, Oancea, B, Ojelabi, FAO, Olagunju, AT, Olakunde, BO, Olgiati, S, Olusanya, JO, Onwujekwe, OE, Otoiu, A, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Padubidri, JR, Palladino, R, Panda-Jonas, S, Park, E-C, Kan, FP, Pawar, S, Toroudi, HP, Pereira, DM, Perianayagam, A, Pesudovs, K, Piccinelli, C, Postma, MJ, Prada, SI, Rabiee, M, Rabiee, N, Rahim, F, Rahimi-Movaghar, V, Rahman, MHU, Rahman, M, Rahmani, AM, Ram, U, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rathi, P, Rawaf, DL, Rawaf, S, Rawal, L, Rawassizadeh, R, Reiner, RC, Renzaho, AMN, Reshmi, B, Riaz, MA, Ripon, RK, Saad, AM, Sahraian, MA, Sahu, M, Salama, JS, Salehi, S, Samy, AM, Sanabria, J, Sanmarchi, F, Santos, JV, Santric-Milicevic, MM, Sathian, B, Savic, M, Saxena, D, Sayyah, M, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Seylani, A, Shahabi, S, Shaikh, MA, Sheikh, A, Shetty, A, Shetty, PH, Shibuya, K, Shrime, MG, Shuja, KH, Singh, JA, Skryabin, VY, Skryabina, AA, Soltani, S, Soofi, M, Spurlock, EE, Stefan, SC, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Taddele, BW, Tefera, YG, Thavamani, A, Tobe-Gai, R, Topor-Madry, R, Tovani-Palone, MR, Bach, XT, Car, LT, Ullah, A, Ullah, S, Umar, N, Undurraga, EA, Valdez, PR, Vasankari, TJ, Villafane, JH, Violante, FS, Vlassov, V, Bay, V, Vollmer, S, Theo, V, Giang, TV, Linh, GV, Wamai, RG, Werdecker, A, Woldekidan, MA, Wubishet, BL, Xu, G, Yaya, S, Yazdi-Feyzabadi, V, Yigit, V, Yip, P, Yirdaw, BW, Yonemoto, N, Younis, MZ, Yu, C, Yunusa, I, Moghadam, TZ, Zandian, H, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Ziapour, A, Zuniga, YMH, Hay, SI, Murray, CJL, Dieleman, JL, Micah, AE, Cogswell, IE, Cunningham, B, Ezoe, S, Harle, AC, Maddison, ER, McCracken, D, Nomura, S, Simpson, KE, Stutzman, HN, Tsakalos, G, Wallace, LE, Zhao, Y, Zende, RR, Abbafati, C, Abdelmasseh, M, Abedi, A, Abegaz, KH, Abhilash, ES, Abolhassani, H, Abrigo, MRM, Adhikari, TB, Afzal, S, Ahinkorah, BO, Ahmadi, S, Ahmed, H, Ahmed, MB, Rashid, TA, Ajami, M, Aji, B, Akalu, Y, Akunna, CJ, Al Hamad, H, Alam, K, Alanezi, FM, Alanzi, TM, Alemayehu, Y, Alhassan, RK, Alinia, C, Aljunid, SM, Almustanyir, SA, Alvis-Guzman, N, Alvis-Zakzuk, NJ, Amini, S, Amini-Rarani, M, Amu, H, Ancuceanu, R, Andrei, CL, Andrei, T, Angell, B, Anjomshoa, M, Antonio, CAT, Antony, CM, Aqeel, M, Arabloo, J, Arab-Zozani, M, Aripov, T, Arrigo, A, Ashraf, T, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Awan, AT, Ayano, G, Ayanore, MA, Azari, S, Azhar, GS, Babalola, TK, Bahrami, MA, Baig, AA, Banach, M, Barati, N, Barnighausen, TW, Barrow, A, Basu, S, Baune, BT, Bayati, M, Benzian, H, Berman, AE, Bhagavathula, AS, Bhardwaj, N, Bhardwaj, P, Bhaskar, S, Bibi, S, Bijani, A, Bodolica, V, Bragazzi, NL, Braithwaite, D, Breitborde, NJK, Breusov, AV, Briko, NI, Busse, R, Cahuana-Hurtado, L, Callander, EJ, Camera, LA, Castaneda-Orjuela, CA, Catala-Lopez, F, Charan, J, Chatterjee, S, Chattu, SK, Chattu, VK, Chen, S, Cicero, AFG, Dadras, O, Dahlawi, SMA, Dai, X, Dalal, K, Dandona, L, Dandona, R, Davitoiu, DV, De Neve, J-W, de Sa-Junior, AR, Denova-Gutierrez, E, Dhamnetiya, D, Dharmaratne, SD, Doshmangir, L, Dube, J, Ehsani-Chimeh, E, Zaki, MES, El Tantawi, M, Eskandarieh, S, Farzadfar, F, Ferede, TY, Fischer, F, Foigt, NA, Freitas, A, Friedman, SD, Fukumoto, T, Fullman, N, Gaal, PA, Gad, MM, Garcia-Gordillo, MA, Garg, T, Ghafourifard, M, Ghashghaee, A, Gholamian, A, Gholamrezanezhad, A, Ghozali, G, Gilani, SA, Glavan, I-R, Glushkova, EV, Goharinezhad, S, Golechha, M, Goli, S, Guha, A, Gupta, VB, Gupta, VK, Haakenstad, A, Haider, MR, Hailu, A, Hamidi, S, Hanif, A, Harapan, H, Hartono, RK, Hasaballah, AI, Hassan, S, Hassanein, MH, Hayat, K, Hegazy, MI, Heidari, G, Hendrie, D, Heredia-Pi, I, Herteliu, C, Hezam, K, Holla, R, Hossain, SJ, Hosseinzadeh, M, Hostiuc, S, Huda, TM, Hwang, B-F, Iavicoli, I, Idrisov, B, Ilesanmi, OS, Irvani, SSN, Islam, SMS, Ismail, NE, Isola, G, Jahani, MA, Jahanmehr, N, Jakovljevic, M, Janodia, MD, Javaheri, T, Jayapal, SK, Jayawardena, R, Jazayeri, SB, Jha, RP, Jonas, JB, Joo, T, Joukar, F, Jurisson, M, Kaambwa, B, Kalhor, R, Kanchan, T, Kandel, H, Matin, BK, Karimi, SE, Kassahun, G, Kayode, GA, Karyani, AK, Keikavoosi-Arani, L, Khader, YS, Khajuria, H, Khalilov, R, Khammarnia, M, Khan, J, Khubchandani, J, Kianipour, N, Kim, GR, Kim, YJ, Kisa, A, Kisa, S, Kohler, S, Kosen, S, Koteeswaran, R, Laxminarayana, SLK, Koyanagi, A, Krishan, K, Kumar, GA, Kusuma, D, Lamnisos, D, Lansingh, VC, Larsson, AO, Lasrado, S, Le, LKD, Lee, SWH, Lee, YY, Lim, SS, Lobo, SW, Lozano, R, Abd El Razek, HM, Abd El Razek, MM, Mahdavi, MM, Majeed, A, Makki, A, Maleki, A, Malekzadeh, R, Manda, AL, Mansour-Ghanaei, F, Mansournia, MA, Arnedo, CAM, Martinez-Valle, A, Masoumi, SZ, Maude, RJ, Mckee, M, Medina-Solis, CE, Menezes, RG, Meretoja, A, Meretoja, TJ, Mesregah, MK, Mestrovic, T, Kostova, NM, Miller, TR, Mini, GK, Mirica, A, Mirrakhimov, EM, Mohajer, B, Mohamed, TA, Mohammadi, M, Mohammadian-Hafshejani, A, Mohammed, S, Moitra, M, Mokdad, AH, Molokhia, M, Moni, MA, Moradi, Y, Morze, J, Mousavi, SM, Mpundu-Kaambwa, C, Muriithi, MK, Muthupandian, S, Nagarajan, AJ, Naimzada, MD, Nangia, V, Naqvi, AA, Narayana, AI, Nascimento, BR, Naveed, M, Nayak, BP, Nazari, J, Ndejjo, R, Negoi, I, Kandel, SN, Trang, HN, Nonvignon, J, Noubiap, JJ, Nwatah, VE, Oancea, B, Ojelabi, FAO, Olagunju, AT, Olakunde, BO, Olgiati, S, Olusanya, JO, Onwujekwe, OE, Otoiu, A, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Padubidri, JR, Palladino, R, Panda-Jonas, S, Park, E-C, Kan, FP, Pawar, S, Toroudi, HP, Pereira, DM, Perianayagam, A, Pesudovs, K, Piccinelli, C, Postma, MJ, Prada, SI, Rabiee, M, Rabiee, N, Rahim, F, Rahimi-Movaghar, V, Rahman, MHU, Rahman, M, Rahmani, AM, Ram, U, Ranabhat, CL, Ranasinghe, P, Rao, CR, Rathi, P, Rawaf, DL, Rawaf, S, Rawal, L, Rawassizadeh, R, Reiner, RC, Renzaho, AMN, Reshmi, B, Riaz, MA, Ripon, RK, Saad, AM, Sahraian, MA, Sahu, M, Salama, JS, Salehi, S, Samy, AM, Sanabria, J, Sanmarchi, F, Santos, JV, Santric-Milicevic, MM, Sathian, B, Savic, M, Saxena, D, Sayyah, M, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Seylani, A, Shahabi, S, Shaikh, MA, Sheikh, A, Shetty, A, Shetty, PH, Shibuya, K, Shrime, MG, Shuja, KH, Singh, JA, Skryabin, VY, Skryabina, AA, Soltani, S, Soofi, M, Spurlock, EE, Stefan, SC, Szerencses, V, Szocska, M, Tabares-Seisdedos, R, Taddele, BW, Tefera, YG, Thavamani, A, Tobe-Gai, R, Topor-Madry, R, Tovani-Palone, MR, Bach, XT, Car, LT, Ullah, A, Ullah, S, Umar, N, Undurraga, EA, Valdez, PR, Vasankari, TJ, Villafane, JH, Violante, FS, Vlassov, V, Bay, V, Vollmer, S, Theo, V, Giang, TV, Linh, GV, Wamai, RG, Werdecker, A, Woldekidan, MA, Wubishet, BL, Xu, G, Yaya, S, Yazdi-Feyzabadi, V, Yigit, V, Yip, P, Yirdaw, BW, Yonemoto, N, Younis, MZ, Yu, C, Yunusa, I, Moghadam, TZ, Zandian, H, Zastrozhin, MS, Zastrozhina, A, Zhang, Z-J, Ziapour, A, Zuniga, YMH, Hay, SI, Murray, CJL, and Dieleman, JL
Abstract: BACKGROUND: The rapid spread of COVID-19 renewed the focus on how health systems across the globe are financed, especially during public health emergencies. Development assistance is an important source of health financing in many low-income countries, yet little is known about how much of this funding was disbursed for COVID-19. We aimed to put development assistance for health for COVID-19 in the context of broader trends in global health financing, and to estimate total health spending from 1995 to 2050 and development assistance for COVID-19 in 2020. METHODS: We estimated domestic health spending and development assistance for health to generate total health-sector spending estimates for 204 countries and territories. We leveraged data from the WHO Global Health Expenditure Database to produce estimates of domestic health spending. To generate estimates for development assistance for health, we relied on project-level disbursement data from the major international development agencies' online databases and annual financial statements and reports for information on income sources. To adjust our estimates for 2020 to include disbursements related to COVID-19, we extracted project data on commitments and disbursements from a broader set of databases (because not all of the data sources used to estimate the historical series extend to 2020), including the UN Office of Humanitarian Assistance Financial Tracking Service and the International Aid Transparency Initiative. We reported all the historic and future spending estimates in inflation-adjusted 2020 US$, 2020 US$ per capita, purchasing-power parity-adjusted US$ per capita, and as a proportion of gross domestic product. We used various models to generate future health spending to 2050. FINDINGS: In 2019, health spending globally reached $8·8 trillion (95% uncertainty interval [UI] 8·7-8·8) or $1132 (1119-1143) per person. Spending on health varied within and across income groups and geographical regions. Of this t
Published: 2021

11. Global mortality from dementia: Application of a new method and results from the Global Burden of Disease Study 2019

Author: Nichols, E, Abd-Allah, F, Abdoli, A, Abosetugn, AE, Abrha, WA, Abualhasan, A, Abu-Gharbieh, E, Akinyemi, RO, Alahdab, F, Alanezi, FM-H, Alipour, V, Ansari, I, Arabloo, J, Ashraf-Ganjouei, A, Avan, A, Ayano, G, Babar, Z-U-D, Baig, AA, Banach, M, Barboza, MA, Barker-Collo, SL, Baune, BT, Bhagavathula, AS, Bhattacharyya, K, Bijani, A, Biondi, A, Birhan, TA, Biswas, A, Bolla, SR, Boloor, A, Brayne, C, Brenner, H, Burkart, K, Burns, RA, Nagaraja, SB, Carvalho, F, Castro-de-Araujo, LFS, Catala-Lopez, F, Cerin, E, Cernigliaro, A, Cherbuin, N-L, Choi, J-YJ, Chu, D-T, Dagnew, B, Dai, X, Dandona, L, Dandona, R, Diaz, D, Forooshani, ZSD, Douiri, A, Duncan, BB, Edvardsson, D, El-Jaafary, SI, Eskandari, K, Eskandarieh, S, Feigin, VL, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Filip, I, Fischer, F, Gaidhane, S, Gebregzabiher, KZ, Ghashghaee, A, Gholamian, A, Gnedovskaya, EV, Golechha, M, Gupta, R, Hachinski, V, Hamidi, S, Hankey, GJ, Maria Haro, J, Hassan, A, Hay, SI, Heidari, G, Heidari-Soureshjani, R, Househ, M, Hussain, R, Hwang, B-F, Ilic, IM, Ilic, MD, Irvani, SSN, Iso, H, Iwagami, M, Jha, RP, Kalani, R, Kandel, H, Karch, A, Kasa, AS, Kengne, AP, Kim, Y-E, Kim, YJ, Kisa, S, Kisa, A, Kivimaki, M, Komaki, H, Koyanagi, A, Kukull, WA, Kumar, GA, Kumar, M, Landires, I, Leonardi, M, Lim, SS, Liu, X, Logroscino, G, Lopez, AD, Lorkowski, S, Loy, CT, Amin, HIM, Manafi, N, Manjunatha, N, Mehndiratta, MM, Menezes, RG, Meretoja, A, Merkin, A, Metekiya, WM, Misganaw, AT, Mohajer, B, Ibrahim, NM, Mohammad, Y, Mohapatra, A, Mohebi, F, Mokdad, AH, Mondello, S, Mossie, TB, Mulugeta, A, Nagel, G, Naveed, M, Nayak, VC, Kandel, SN, Son, HN, Huong, LTN, Nunez-Samudio, V, Ogbo, FA, Olagunju, AT, Orru, H, Ostojic, SM, Ostroff, SM, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Pathak, M, Toroudi, HP, Peterson, CB, Hai, QP, Phillips, MR, Piradov, MA, Pottoo, FH, Prada, SI, Pribadi, DRA, Radfar, A, Raggi, A, Rahim, F, Ram, P, Rana, J, Rashedi, V, Rawaf, S, Rawaf, DL, Reinig, N, Rezaei, N, Robinson, SR, Romoli, M, Sachdev, PS, Sahathevan, R, Sahebkar, A, Sahraian, MA, Sattin, D, Saylan, M, Sayyah, M, Schiavolin, S, Schmidt, MI, Shahid, I, Shaikh, MA, Shigematsu, M, Shin, JI, Shiri, R, Siddiqi, TJ, Silva, JP, Singh, JA, Soheili, A, Spurlock, EE, Szoeke, CEI, Tabares-Seisdedos, R, Taddele, BW, Thakur, B, ThekkePurakkal, AS, Tovani-Palone, MR, Tran, BX, Travillian, RS, Tripathi, M, Tsegaye, GW, Usman, MS, Vacante, M, Zuleika Velazquez, D, Venketasubramanian, N, Vidale, S, Vlassov, V, Wang, Y-P, Wei, J, Weiss, J, Weldemariam, AH, Wimo, A, Wu, C, Yadollahpour, A, Yamagishi, K, Yeshitila, YG, Yonemoto, N, Zadey, S, Zhang, Z-J, Murray, CJL, Vos, T, Nichols, E, Abd-Allah, F, Abdoli, A, Abosetugn, AE, Abrha, WA, Abualhasan, A, Abu-Gharbieh, E, Akinyemi, RO, Alahdab, F, Alanezi, FM-H, Alipour, V, Ansari, I, Arabloo, J, Ashraf-Ganjouei, A, Avan, A, Ayano, G, Babar, Z-U-D, Baig, AA, Banach, M, Barboza, MA, Barker-Collo, SL, Baune, BT, Bhagavathula, AS, Bhattacharyya, K, Bijani, A, Biondi, A, Birhan, TA, Biswas, A, Bolla, SR, Boloor, A, Brayne, C, Brenner, H, Burkart, K, Burns, RA, Nagaraja, SB, Carvalho, F, Castro-de-Araujo, LFS, Catala-Lopez, F, Cerin, E, Cernigliaro, A, Cherbuin, N-L, Choi, J-YJ, Chu, D-T, Dagnew, B, Dai, X, Dandona, L, Dandona, R, Diaz, D, Forooshani, ZSD, Douiri, A, Duncan, BB, Edvardsson, D, El-Jaafary, SI, Eskandari, K, Eskandarieh, S, Feigin, VL, Fereshtehnejad, S-M, Fernandes, E, Ferrara, P, Filip, I, Fischer, F, Gaidhane, S, Gebregzabiher, KZ, Ghashghaee, A, Gholamian, A, Gnedovskaya, EV, Golechha, M, Gupta, R, Hachinski, V, Hamidi, S, Hankey, GJ, Maria Haro, J, Hassan, A, Hay, SI, Heidari, G, Heidari-Soureshjani, R, Househ, M, Hussain, R, Hwang, B-F, Ilic, IM, Ilic, MD, Irvani, SSN, Iso, H, Iwagami, M, Jha, RP, Kalani, R, Kandel, H, Karch, A, Kasa, AS, Kengne, AP, Kim, Y-E, Kim, YJ, Kisa, S, Kisa, A, Kivimaki, M, Komaki, H, Koyanagi, A, Kukull, WA, Kumar, GA, Kumar, M, Landires, I, Leonardi, M, Lim, SS, Liu, X, Logroscino, G, Lopez, AD, Lorkowski, S, Loy, CT, Amin, HIM, Manafi, N, Manjunatha, N, Mehndiratta, MM, Menezes, RG, Meretoja, A, Merkin, A, Metekiya, WM, Misganaw, AT, Mohajer, B, Ibrahim, NM, Mohammad, Y, Mohapatra, A, Mohebi, F, Mokdad, AH, Mondello, S, Mossie, TB, Mulugeta, A, Nagel, G, Naveed, M, Nayak, VC, Kandel, SN, Son, HN, Huong, LTN, Nunez-Samudio, V, Ogbo, FA, Olagunju, AT, Orru, H, Ostojic, SM, Ostroff, SM, Otstavnov, N, Otstavnov, SS, Owolabi, MO, Pathak, M, Toroudi, HP, Peterson, CB, Hai, QP, Phillips, MR, Piradov, MA, Pottoo, FH, Prada, SI, Pribadi, DRA, Radfar, A, Raggi, A, Rahim, F, Ram, P, Rana, J, Rashedi, V, Rawaf, S, Rawaf, DL, Reinig, N, Rezaei, N, Robinson, SR, Romoli, M, Sachdev, PS, Sahathevan, R, Sahebkar, A, Sahraian, MA, Sattin, D, Saylan, M, Sayyah, M, Schiavolin, S, Schmidt, MI, Shahid, I, Shaikh, MA, Shigematsu, M, Shin, JI, Shiri, R, Siddiqi, TJ, Silva, JP, Singh, JA, Soheili, A, Spurlock, EE, Szoeke, CEI, Tabares-Seisdedos, R, Taddele, BW, Thakur, B, ThekkePurakkal, AS, Tovani-Palone, MR, Tran, BX, Travillian, RS, Tripathi, M, Tsegaye, GW, Usman, MS, Vacante, M, Zuleika Velazquez, D, Venketasubramanian, N, Vidale, S, Vlassov, V, Wang, Y-P, Wei, J, Weiss, J, Weldemariam, AH, Wimo, A, Wu, C, Yadollahpour, A, Yamagishi, K, Yeshitila, YG, Yonemoto, N, Zadey, S, Zhang, Z-J, Murray, CJL, and Vos, T
Abstract: INTRODUCTION: Dementia is currently one of the leading causes of mortality globally, and mortality due to dementia will likely increase in the future along with corresponding increases in population growth and population aging. However, large inconsistencies in coding practices in vital registration systems over time and between countries complicate the estimation of global dementia mortality. METHODS: We meta-analyzed the excess risk of death in those with dementia and multiplied these estimates by the proportion of dementia deaths occurring in those with severe, end-stage disease to calculate the total number of deaths that could be attributed to dementia. RESULTS: We estimated that there were 1.62 million (95% uncertainty interval [UI]: 0.41-4.21) deaths globally due to dementia in 2019. More dementia deaths occurred in women (1.06 million [0.27-2.71]) than men (0.56 million [0.14-1.51]), largely but not entirely due to the higher life expectancy in women (age-standardized female-to-male ratio 1.19 [1.10-1.26]). Due to population aging, there was a large increase in all-age mortality rates from dementia between 1990 and 2019 (100.1% [89.1-117.5]). In 2019, deaths due to dementia ranked seventh globally in all ages and fourth among individuals 70 and older compared to deaths from other diseases estimated in the Global Burden of Disease (GBD) study. DISCUSSION: Mortality due to dementia represents a substantial global burden, and is expected to continue to grow into the future as an older, aging population expands globally.
Published: 2021

12. Health sector spending and spending on HIV/AIDS, tuberculosis, and malaria, and development assistance for health: progress towards Sustainable Development Goal 3

Author: Micah, AE, Su, Y, Bachmeier, SD, Chapin, A, Cogswell, IE, Crosby, SW, Cunningham, B, Harle, AC, Maddison, ER, Moitra, M, Sahu, M, Schneider, MT, Simpson, KE, Stutzman, HN, Tsakalos, G, Zende, RR, Zlavog, BS, Abbafati, C, Abebo, ZH, Abolhassani, H, Abrigo, MRM, Ahmed, MB, Akinyemi, RO, Alam, K, Ali, S, Alinia, C, Alipour, V, Aljunid, SM, Almasi, A, Alvis-Guzman, N, Ancuceanu, R, Andrei, T, Andrei, CL, Anjomshoa, M, Antonio, CAT, Arabloo, J, Arab-Zozani, M, Aremu, O, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Ayanore, MA, Azari, S, Babalola, TK, Bagherzadeh, M, Baig, AA, Bakhtiari, A, Banach, M, Banerjee, SK, Barnighausen, TW, Basu, S, Baune, BT, Bayati, M, Berman, AE, Bhageerathy, R, Bhardwaj, P, Bohluli, M, Busse, R, Cahuana-Hurtado, L, Camera, LLAA, Castaneda-Orjuela, CA, Catala-Lopez, F, Cevik, M, Chattu, VK, Dandona, L, Dandona, R, Dianatinasab, M, Hoa, TD, Doshmangir, L, El Tantawi, M, Eskandarieh, S, Esmaeilzadeh, F, Faraj, A, Farzadfar, F, Fischer, F, Foigt, NA, Fullman, N, Gad, MM, Ghafourifard, M, Ghashghaee, A, Gholamian, A, Goharinezhad, S, Grada, A, Bidgoli, HH, Hamidi, S, Harb, HL, Hasanpoor, E, Hay, SI, Hendrie, D, Henry, NJ, Herteliu, C, Hole, MK, Hosseinzadeh, M, Hostiuc, S, Huda, TM, Humayun, A, Hwang, B-F, Ilesanmi, OS, Iqbal, U, Irvani, SS, Islam, SMS, Islam, MM, Jahani, MA, Jakovljevic, M, James, SL, Javaheri, Z, Jonas, JB, Joukar, F, Jozwiak, JJ, Jurisson, M, Kalhor, R, Matin, BK, Karimi, SE, Kayode, GA, Karyani, AK, Kinfu, Y, Kisa, A, Kohler, S, Komaki, H, Kosen, S, Kotlo, A, Koyanagi, A, Kumar, GA, Kusuma, D, Lansingh, VC, Larsson, AO, Lasrado, S, Lee, SWH, Lim, L-L, Lozano, R, Abd El Razek, HM, Mahdavi, MM, Maleki, S, Malekzadeh, R, Mansour-Ghanaei, F, Mansournia, MA, Mantovani, LG, Martinez, G, Masoumi, SZ, Massenburg, BB, Menezes, RG, Mengesha, EW, Meretoja, TJ, Meretoja, A, Mestrovic, T, Kostova, NM, Miller, TR, Mirica, A, Mirrakhimov, EM, Moghadaszadeh, M, Mohajer, B, Mohamadi, E, Darwesh, AM, Mohammadian-Hafshejani, A, Mohammadpourhodki, R, Mohammed, S, Mohebi, F, Mokdad, AH, Morrison, SD, Mosser, JF, Mousavi, SM, Muriithi, MK, Muthupandian, S, Myint, C-Y, Naderi, M, Nagarajan, AJ, Cuong, TN, Huong, LTN, Nonvignon, J, Noubiap, JJ, Oh, I-H, Olagunju, AT, Olusanya, JO, Olusanya, BO, Bali, AO, Onwujekwe, OE, Otstavnov, SS, Otstavnov, N, Owolabi, MO, Padubidri, JR, Palladino, R, Panda-Jonas, S, Pandey, A, Postma, MJ, Prada, SI, Pribadi, DRA, Rabiee, M, Rabiee, N, Rahim, F, Ranabhat, CL, Rao, SJ, Rathi, P, Rawaf, S, Rawaf, DL, Rawal, L, Rawassizadeh, R, Rezapour, A, Sabour, S, Sahraian, MA, Salman, OM, Salomon, JA, Samy, AM, Sanabria, J, Santos, JV, Milicevic, MMS, Jose, BPS, Savic, M, Schwendicke, F, Senthilkumaran, S, Sepanlou, SG, Servan-Mori, E, Setayesh, H, Shaikh, MA, Sheikh, A, Shibuya, K, Shrime, MG, Simonetti, B, Singh, JA, Singh, P, Skryabin, VY, Soheili, A, Soltani, S, Stefan, SC, Tabares-Seisdedos, R, Topor-Madry, R, Tovani-Palone, MR, Tran, BX, Travillian, R, Undurraga, EA, Valdez, PR, van Boven, JFM, Vasankari, TJ, Violante, FS, Vlassov, V, Vos, T, Wolfe, CDA, Wu, J, Yaya, S, Yazdi-Feyzabadi, V, Yip, P, Yonemoto, N, Younis, MZ, Yu, C, Zaidi, Z, Bin Zaman, S, Zastrozhin, MS, Zhang, Z-J, Zhao, Y, Murray, CJL, Dieleman, JL, Micah, AE, Su, Y, Bachmeier, SD, Chapin, A, Cogswell, IE, Crosby, SW, Cunningham, B, Harle, AC, Maddison, ER, Moitra, M, Sahu, M, Schneider, MT, Simpson, KE, Stutzman, HN, Tsakalos, G, Zende, RR, Zlavog, BS, Abbafati, C, Abebo, ZH, Abolhassani, H, Abrigo, MRM, Ahmed, MB, Akinyemi, RO, Alam, K, Ali, S, Alinia, C, Alipour, V, Aljunid, SM, Almasi, A, Alvis-Guzman, N, Ancuceanu, R, Andrei, T, Andrei, CL, Anjomshoa, M, Antonio, CAT, Arabloo, J, Arab-Zozani, M, Aremu, O, Atnafu, DD, Ausloos, M, Avila-Burgos, L, Ayanore, MA, Azari, S, Babalola, TK, Bagherzadeh, M, Baig, AA, Bakhtiari, A, Banach, M, Banerjee, SK, Barnighausen, TW, Basu, S, Baune, BT, Bayati, M, Berman, AE, Bhageerathy, R, Bhardwaj, P, Bohluli, M, Busse, R, Cahuana-Hurtado, L, Camera, LLAA, 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Shibuya, K, Shrime, MG, Simonetti, B, Singh, JA, Singh, P, Skryabin, VY, Soheili, A, Soltani, S, Stefan, SC, Tabares-Seisdedos, R, Topor-Madry, R, Tovani-Palone, MR, Tran, BX, Travillian, R, Undurraga, EA, Valdez, PR, van Boven, JFM, Vasankari, TJ, Violante, FS, Vlassov, V, Vos, T, Wolfe, CDA, Wu, J, Yaya, S, Yazdi-Feyzabadi, V, Yip, P, Yonemoto, N, Younis, MZ, Yu, C, Zaidi, Z, Bin Zaman, S, Zastrozhin, MS, Zhang, Z-J, Zhao, Y, Murray, CJL, and Dieleman, JL
Abstract: BACKGROUND: Sustainable Development Goal (SDG) 3 aims to "ensure healthy lives and promote well-being for all at all ages". While a substantial effort has been made to quantify progress towards SDG3, less research has focused on tracking spending towards this goal. We used spending estimates to measure progress in financing the priority areas of SDG3, examine the association between outcomes and financing, and identify where resource gains are most needed to achieve the SDG3 indicators for which data are available. METHODS: We estimated domestic health spending, disaggregated by source (government, out-of-pocket, and prepaid private) from 1995 to 2017 for 195 countries and territories. For disease-specific health spending, we estimated spending for HIV/AIDS and tuberculosis for 135 low-income and middle-income countries, and malaria in 106 malaria-endemic countries, from 2000 to 2017. We also estimated development assistance for health (DAH) from 1990 to 2019, by source, disbursing development agency, recipient, and health focus area, including DAH for pandemic preparedness. Finally, we estimated future health spending for 195 countries and territories from 2018 until 2030. We report all spending estimates in inflation-adjusted 2019 US$, unless otherwise stated. FINDINGS: Since the development and implementation of the SDGs in 2015, global health spending has increased, reaching $7·9 trillion (95% uncertainty interval 7·8-8·0) in 2017 and is expected to increase to $11·0 trillion (10·7-11·2) by 2030. In 2017, in low-income and middle-income countries spending on HIV/AIDS was $20·2 billion (17·0-25·0) and on tuberculosis it was $10·9 billion (10·3-11·8), and in malaria-endemic countries spending on malaria was $5·1 billion (4·9-5·4). Development assistance for health was $40·6 billion in 2019 and HIV/AIDS has been the health focus area to receive the highest contribution since 2004. In 2019, $374 million of DAH was provided for pandemic preparedness, less than 1% of
Published: 2020

13. Direct cost of lupus care in the developing world: the case of Colombia

Author: Prada, SI, primary, Perez, AM, additional, Nieto-Aristizábal, I, additional, and Tobón, GJ, additional
Published: 2019
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14. Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Author: Abbafati, C., Machado, D.B., Cislaghi, B., Salman, O.M., Karanikolos, M., McKee, M., Abbas, K.M., Brady, O.J., Larson, H.J., Trias-Llimós, S., Cummins, S., Langan, S.M., Sartorius, B., Hafiz, A., Jenabi, E., Mohammad Gholi Mezerji, N., Borzouei, S., Azarian, G., Khazaei, S., Abbasi, M., Asghari, B., Masoumi, S., Komaki, H., Taherkhani, A., Adabi, M., Abbasifard, M., Bazmandegan, G., Kamiab, Z., Vakilian, A., Anjomshoa, M., Mokari, A., Sabour, S., Shahbaz, M., Saeedi, R., Ahmadieh, H., Yousefinezhadi, T., Haj-Mirzaian, A., Nikbakhsh, R., Safi, S., Asgari, S., Irvani, S.N., Jahanmehr, N., Ramezanzadeh, K., Abbasi-Kangevari, M., Khayamzadeh, M., Abbastabar, H., Shirkoohi, R., Fazlzadeh, M., Janjani, H., Hosseini, M., Mansournia, M., Tohidinik, H., Bakhtiari, A., Fazaeli, A., Mousavi, S., Hasanzadeh, A., Nabavizadeh, B., Malekzadeh, R., Hashemian, M., Pourshams, A., Salimzadeh, H., Sepanlou, S.G., Afarideh, M., Esteghamati, A., Esteghamati, S., Ghajar, A., Heidari, B., Rezaei, N., Mohamadi, E., Rahimi-Movaghar, A., Rahim, F., Eskandarieh, S., Sahraian, M., Mohebi, F., Aminorroaya, A., Ebrahimi, H., Farzadfar, F., Mohajer, B., Pishgar, F., Saeedi Moghaddam, S., Shabani, M., Zarafshan, H., Abolhassani, H., Hafezi-Nejad, N., Heidari-Soureshjani, R., Abdollahi, M., Farahmand, M., Salamati, P., Mehrabi Nasab, E., Tajdini, M., Aghamir, S., Mirzaei, R., Dibaji Forooshani, Z., Khater, M.M., Abd-Allah, F., Abdelalim, A., Abualhasan, A., El-Jaafary, S.I., Hassan, A., Elsharkawy, A., Khater, A.M., Elhabashy, H.R., Salem, M.R.R., Salem, H., Sadeghi, M., Jafarinia, M., Amini-Rarani, M., Mohammadifard, N., Sarrafzadegan, N., Abdollahpour, I., Sarveazad, A., Tehrani-Banihashemi, A., Yoosefi Lebni, J., Manafi, N., Pazoki Toroudi, H., Dorostkar, F., Alipour, V., Sheikhtaheri, A., Arabloo, J., Azari, S., Ghashghaee, A., Rezapour, A., Naserbakht, M., Kabir, A., Mehri, F., Yousefifard, M., Asadi-Aliabadi, M., Babaee, E., Eshrati, B., Goharinezhad, S., Moradi-Lakeh, M., Abedi, P., 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Mokari, Amin, Mokdad, Ali H, Momen, Natalie C, Monasta, Lorenzo, Mooney, Meghan D, Moradi, Ghobad, Moradi, Masoud, Moradi-Joo, Mohammad, Moradi-Lakeh, Maziar, Moradzadeh, Rahmatollah, Moraga, Paula, Moreno Velásquez, Ilai, Morgado-da-Costa, Joana, Morrison, Shane Dougla, Mosser, Jonathan F, Mouodi, Simin, Mousavi, Seyyed Meysam, Mousavi Khaneghah, Amin, Mueller, Ulrich Otto, Musa, Kamarul Imran, Muthupandian, Saravanan, Nabavizadeh, Behnam, Naderi, Mehdi, Nagarajan, Ahamarshan Jayaraman, Naghavi, Mohsen, Naghshtabrizi, Behshad, Naik, Gurudatta, Najafi, Farid, Nangia, Vinay, Nansseu, Jobert Richie, Ndwandwe, Duduzile Edith, Negoi, Ionut, Negoi, Ruxandra Irina, Ngunjiri, Josephine W, Nguyen, Huong Lan Thi, Nguyen, Trang Huyen, Nigatu, Yeshambel T, Nikbakhsh, Rajan, Nikpoor, Amin Reza, Nixon, Molly R, Nnaji, Chukwudi A, Nomura, Shuhei, Noubiap, Jean Jacque, Nouraei Motlagh, Soraya, Nowak, Christoph, Oţoiu, Adrian, Odell, Christopher M, Oh, In-Hwan, Oladnabi, Morteza, Olagunju, Andrew T, Olusanya, Bolajoko Olubukunola, Olusanya, Jacob Olusegun, Omar Bali, Ahmed, Ong, Kanyin L, Onwujekwe, Obinna E, Ortiz, Alberto, Otstavnov, Nikita, Otstavnov, Stanislav S, Øverland, Simon, Owolabi, Mayowa O, P A, Mahesh, Padubidri, Jagadish Rao, Pakshir, Keyvan, Palladino, Raffaele, Pana, Adrian, Panda-Jonas, Songhomitra, Park, Jame, Pasupula, Deepak Kumar, Patel, Jenil R, Patel, Sangram Kishor, Patton, George C, Paulson, Katherine R, Pazoki Toroudi, Hamidreza, Pease, Spencer A, Peden, Amy E, Pepito, Veincent Christian Filipino, Peprah, Emmanuel K, Pereira, Alexandre, Pereira, David M, Perico, Norberto, Pigott, David M, Pilgrim, Thoma, Pilz, Tessa M, Piradov, Michael A, Pirsaheb, Meghdad, Pokhrel, Khem Narayan, Postma, Maarten J, Pourjafar, Hadi, Pourmalek, Farshad, Pourshams, Akram, Poznańska, Anna, Prada, Sergio I, Prakash, Sanjay, Preotescu, Liliana, Quazi Syed, Zahiruddin, Rabiee, Mohammad, Rabiee, Navid, Radfar, Amir, Rafiei, Alireza, Raggi, Alberto, Rahman, Muhammad Aziz, Rajabpour-Sanati, Ali, Ram, Pradhum, Ranabhat, Chhabi Lal, Rao, Sowmya J, Rasella, Davide, Rashedi, Vahid, Rastogi, Prateek, Rathi, Priya, Rawal, Lal, Remuzzi, Giuseppe, Renjith, Vishnu, Renzaho, Andre M N, Resnikoff, Serge, Rezaei, Nima, Rezai, Mohammad sadegh, Rezapour, Aziz, Rickard, Jennifer, Roever, Leonardo, Ronfani, Luca, Roshandel, Gholamreza, Rostamian, Morteza, Rubagotti, Enrico, Rwegerera, Godfrey M, Sabour, Siamak, Saddik, Basema, Sadeghi, Ehsan, Sadeghi, Masoumeh, Saeedi Moghaddam, Sahar, Safari, Yahya, Safi, Sare, Safiri, Saeid, Sagar, Rajesh, Sahebkar, Amirhossein, Sahraian, Mohammad Ali, Sajadi, S Mohammad, Salahshoor, Mohammad Reza, Salama, Joseph S, Salamati, Payman, Salem, Marwa R Rashad, Salimi, Yahya, Salomon, Joshua A, Salz, Inbal, Samad, Zainab, Samy, Abdallah M, Sanabria, Juan, Santric-Milicevic, Milena M, Saraswathy, Sivan Yegnanarayana Iyer, Sartorius, Benn, Sarveazad, Arash, Sathian, Brijesh, Sathish, Thirunavukkarasu, Sattin, Davide, Saylan, Mete, Schaeffer, Lauren E, Schiavolin, Silvia, Schwebel, David C, Schwendicke, Falk, Sekerija, Mario, Senbeta, Anbissa Muleta, Senthilkumaran, Subramanian, Sepanlou, Sadaf G, Serván-Mori, Edson, Shabani, Mahsima, Shahabi, Saeed, Shahbaz, Mohammad, Shaheen, Amira A, Shaikh, Masood Ali, Shalash, Ali S, Shams-Beyranvand, Mehran, Shamsi, Mohammadbagher, Shamsizadeh, Morteza, Shannawaz, Mohammed, Sharafi, Kiomar, Sharafi, Zeinab, Sharara, Fablina, Sharma, Rajesh, Shaw, David H, Sheikh, Aziz, Shin, Jae Il, Shiri, Rahman, Shrime, Mark G, Shuval, Kerem, Siabani, Soraya, Sigfusdottir, Inga Dora, Sigurvinsdottir, Rannveig, Silva, Diego Augusto Santo, Simonetti, Biagio, Simpson, Kyle E, Singh, Jasvinder A, Skiadaresi, Eirini, Skryabin, Valentin Yurievich, Soheili, Amin, Sokhan, Anton, Sorensen, Reed J D, Soriano, Joan B, Sorrie, Muluken Bekele, Soyiri, Ireneous N, Spurlock, Emma Elizabeth, Sreeramareddy, Chandrashekhar T, Stockfelt, Leo, Stokes, Mark A, Stubbs, Jacob L, Sudaryanto, Agu, Sufiyan, Mu'awiyyah Babale, Suliankatchi Abdulkader, Rizwan, Sykes, Bryan L, Tabarés-Seisdedos, Rafael, Tabb, Karen M, Tadakamadla, Santosh Kumar, Taherkhani, Amir, Tang, Muming, Taveira, Nuno, Taylor, Heather Jean, Teagle, Whitney L, Tehrani-Banihashemi, Arash, Teklehaimanot, Berhane Fseha, Tessema, Zemenu Tadesse, Thankappan, Kavumpurathu Raman, Thomas, Nihal, Thrift, Amanda G, Titova, Mariya Vladimirovna, Tohidinik, Hamid Reza, Tonelli, Marcello, Topor-Madry, Roman, Topouzis, Foti, Tovani-Palone, Marcos Roberto Roberto, Traini, Eugenio, Tran, Bach Xuan, Travillian, Ravensara, Trias-Llimós, Sergi, Truelsen, Thomas Clement, Tudor Car, Lorainne, Unnikrishnan, Bhaskaran, Upadhyay, Era, Vacante, Marco, Vakilian, Alireza, Valdez, Pascual R, Valli, Alessandro, Vardavas, Constantine, Vasankari, Tommi Juhani, Vasconcelos, Ana Maria Nogale, Vasseghian, Yasser, Veisani, Yousef, Venketasubramanian, Narayanaswamy, Vidale, Simone, Violante, Francesco S, Vlassov, Vasily, Vollset, Stein Emil, Vos, Theo, Vujcic, Isidora S, Vukovic, Ana, Vukovic, Rade, Waheed, Yasir, Wallin, Mitchell Taylor, Walters, Magdalene K, Wang, Hongbo, Wang, Yuan-Pang, Watson, Stefanie, Wei, Jingkai, Weiss, Jordan, Weldesamuel, Girmay Teklay, Werdecker, Andrea, Westerman, Ronny, Whiteford, Harvey A, Wiangkham, Taweewat, Wiens, Kirsten E, Wijeratne, Tissa, Wiysonge, Charles Shey, Wojtyniak, Bogdan, Wolfe, Charles D A, Wondmieneh, Adam Belay, Wool, Eve E, Wu, Ai-Min, Wu, Junjie, Xu, Gelin, Yamada, Tomohide, Yamagishi, Kazumasa, Yano, Yuichiro, Yaya, Sanni, Yazdi-Feyzabadi, Vahid, Yearwood, Jamal A, Yeheyis, Tomas Y, Yilgwan, Christopher Sabo, Yip, Paul, Yonemoto, Naohiro, Yoon, Seok-Jun, Yoosefi Lebni, Javad, York, Hunter W, Younis, Mustafa Z, Younker, Theodore Patrick, Yousefi, Zabihollah, Yousefinezhadi, Taraneh, Yousuf, Abdilahi Yousuf, Yusefzadeh, Hasan, Zahirian Moghadam, Telma, Zakzuk, Josefina, Zaman, Sojib Bin, Zamani, Mohammad, Zamanian, Maryam, Zandian, Hamed, Zhang, Zhi-Jiang, Zheng, Peng, Zhou, Maigeng, Ziapour, Arash, Murray, Christopher J L, Collaborators, GBD 2019 Demographics, GBD 2019 Demographics Collaborator, Violante FS, Value, Affordability and Sustainability (VALUE), Real World Studies in PharmacoEpidemiology, -Genetics, -Economics and -Therapy (PEGET), Microbes in Health and Disease (MHD), Department of Earth Systems Analysis, Biomechanical Engineering, TechMed Centre, Biomolecular Nanotechnology, Research Methodology, Measurement and Data Analysis, Materials Science and Technology of Polymers, Inorganic Materials Science, MESA+ Institute, Biomedical and Environmental Sensorsystems, Mesoscale Chemical Systems, Faculty of Engineering Technology, Nonlinear Solid Mechanics, Digital Society Institute, Pervasive Systems, Nanobiophysics, Faculty of Geo-Information Science and Earth Observation, Multi Scale Mechanics, Engineering Fluid Dynamics, Physics of Complex Fluids, Developmental BioEngineering, Physics of Fluids, Elastomer Technology and Engineering, Medical Cell Biophysics, European Membrane Institute, Department of Earth Observation Science, Biomaterials Science and Technology, Sustainable Process Technology, Department of Urban and Regional Planning and Geo-Information Management, Department of Natural Resources, XUV Optics, Databases (Former), Department of Water Resources, Psychology, Health & Technology, Membrane Science & Technology, Department of Public Health, Clinicum, HUS Neurocenter, HUS Comprehensive Cancer Center, and Environmental Sciences
Subjects: Male, very elderly, Demographic transition, HALE, 030204 cardiovascular system & hematology, preschool child, Global Burden of Disease, Carga Global de Enfermedades, 0302 clinical medicine, newborn, Risk Factors, Surveys and Questionnaires, and Risk Factors Study, 80 and over, 030212 general & internal medicine, Birth Rate, Child, Migration, 11 Medical and Health Sciences, Aged, 80 and over, education.field_of_study, Injuries, Geography, Mortality rate, 1. No poverty, DEATH, Censuses, General Medicine, SDG 10 - Reduced Inequalities, Middle Aged, Demographic analysis, 3142 Public health care science, environmental and occupational health, 3. Good health, demographic analysis, Estilo de Vida Saludable, risk factor, Child, Preschool, Demography/statistics & numerical data, Global Burden of Diseases, Injuries, Risk Factors, Fertility, Mortality, Migration, Population, epidemiology, Female, A990 Medicine and Dentistry not elsewhere classified, CHILD-MORTALITY, Live Birth, Global Health Metrics, TRANSITION, demographics, GBD, fertility, mortality, hale, Adult, Adolescent, Total fertility rate, Population, Global Burden of Diseases, Injuries, and Risk Factors Study, Birth rate, 03 medical and health sciences, Young Adult, Life Expectancy, SDG 3 - Good Health and Well-being, General & Internal Medicine, SYSTEMATIC ANALYSIS, Demografía, Humans, Global Burden of Disease Study, human, Mortality, education, Preschool, Aged, Demography, Spatial Analysis, questionnaire, Infant, Newborn, Klinisk medicin, HIV, Infant, Global Burden of Diseases, sex-specific fertility, Live Birth/epidemiology, purl.org/pe-repo/ocde/ford#3.02.00 [https], MODEL, Fertilidad, Fertility, Demographic change, Life expectancy, NA, global disease burden, Clinical Medicine, population research
Abstract: Background Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10-14 and 50-54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings The global TFR decreased from 2.72 (95% uncertainty interval [UI] 2.66-2.79) in 2000 to 2.31 (2.17-2.46) in 2019. Global annual livebirths increased from 134.5 million (131.5-137.8) in 2000 to a peak of 139.6 million (133.0-146.9) in 2016. Global livebirths then declined to 135.3 million (127.2-144.1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2.1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27.1% (95% UI 26.4-27.8) of global livebirths. Global life expectancy at birth increased from 67.2 years (95% UI 66.8-67.6) in 2000 to 73.5 years (72.8-74.3) in 2019. The total number of deaths increased from 50.7 million (49.5-51.9) in 2000 to 56.5 million (53.7-59.2) in 2019. Under-5 deaths declined from 9.6 million (9.1-10.3) in 2000 to 5.0 million (4.3-6.0) in 2019. Global population increased by 25.7%, from 6.2 billion (6.0-6.3) in 2000 to 7.7 billion (7.5-8.0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58.6 years (56.1-60.8) in 2000 to 63.5 years (60.8-66.1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Copyright (C) 2020 The Author(s). Published by Elsevier Ltd.
Published: 2020

15. Effects of a hospital-based food security programme for children with complex diseases in an upper-middle-income country: a before-and-after study.

Author: Gómez-Casas ÁM, Gempeler A, Montoya D, González LF, Prada SI, Escobar LA, Madriñán JM, and Granados M
Subjects: Humans, Male, Female, Child, Child, Preschool, Food Insecurity, Infant, Program Evaluation, Adolescent, Food Supply statistics & numerical data, Nutritional Status, Food Security
Abstract: Background: To reduce health inequities in paediatric patients with complex diseases, our hospital developed a food security programme in 2022. The programme aims to mitigate food insecurity (FI) in paediatric patients with oncological, transplantation and congenital cardiovascular diagnoses, by providing a monthly nutritious food supply that covers up to 50% of the patient's family food intake, accompanied by social and nutritional follow-up. In this study, we aimed to assess the effect of the programme on FI and nutritional status and describe its implementation., Method: We conducted a before-and-after study of patients who entered the programme in a 14-month period. We used the Escala Latinoamericana y Caribeña de Seguridad Alimentaria (ELCSA) scale score, FI level and nutritional status measures to assess the effect of the programme. We used the Wilcoxon and McNemar tests to assess changes in scores and proportions of patients with moderate and severe FI, respectively, 31.5%-14.4% (p=0.0008) and of moderate FI from 68.5% to 36.9%., Results: 111 patients were included. They had a baseline median (IQR) ELCSA score=8 (7-11) that changed to 6 (4-9) (p<0.0001). Severe FI according to ELCSA changed from 31.5% to 14.4% (p<0.001) and moderate from 68.5% to 36.9% (p<0.001). We found no differences in nutritional status regarding height for age (49.5% vs 51.3%, p=0.76), weight for height (42.5% vs 59.1%, p=0.75) or body mass index for age (38% vs 46%, p=0.42) CONCLUSION: The programme reduced FI in families by improving its level to mild or moderate. Children who entered the programme maintained an appropriate nutritional status despite the considerable risk of malnutrition described for oncological paediatric patients and paediatric solid organ transplantation receptors., Competing Interests: Competing interests: Hospital Universitario Fundación Valle del Lili is a non-profit university hospital in Cali, Colombia. Among the authors are researchers and institutional directors involved in the development of the program and the conduction of the research project. The study does not promote or recommend any medication, medical devices or services. The authors declare to have no conflict of interest regarding the conduction of this project., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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16. Impact of a teaching hospital-based multidisciplinary telemedicine programme in Southwestern Colombia: a cross-sectional resource analysis.

Author: Prada SI, Toro JJ, Peña-Zárate EE, Libreros-Peña L, Alarcón J, and Escobar MF
Subjects: Humans, Colombia, Cross-Sectional Studies, Female, Male, Middle Aged, Adult, Aged, Cost Savings, Health Services Accessibility economics, Adolescent, Young Adult, Travel economics, Telemedicine economics, Telemedicine methods, Hospitals, Teaching
Abstract: Background: Telemedicine, a method of healthcare service delivery bridging geographic distances between patients and providers, has gained prominence. This modality is particularly advantageous for outpatient consultations, addressing inherent barriers of travel time and cost., Objective: We aim to describe economical outcomes towards the implementation of a multidisciplinary telemedicine service in a high-complexity hospital in Latin America, from the perspective of patients., Design: A cross-sectional study was conducted, analysing the institutional data obtained over a period of 9 months, between April 2020 and December 2020., Setting: A high-complexity teaching hospital located in Cali, Colombia., Participants: Individuals who received care via telemedicine. The population was categorised into three groups based on their place of residence: Cali, Valle del Cauca excluding Cali and Outside of Valle del Cauca., Outcome Measures: Travel distance, time, fuel and public round-trip cost savings, and potential loss of productivity were estimated from the patient's perspective., Results: A total of 62 258 teleconsultations were analysed. Telemedicine led to a total distance savings of 4 514 903 km, and 132 886 hours. The estimated cost savings were US$680 822 for private transportation and US$1 087 821 for public transportation. Patients in the Outside of Valle del Cauca group experienced an estimated average time savings of 21.2 hours, translating to an average fuel savings of US$149.02 or an average savings of US$156.62 in public transportation costs. Areas with exclusive air access achieved a mean cost savings of US$362.9 per teleconsultation, specifically related to transportation costs., Conclusion: Telemedicine emerges as a powerful tool for achieving substantial travel savings for patients, especially in regions confronting geographical and socioeconomic obstacles. These findings underscore the potential of telemedicine to bridge healthcare accessibility gaps in low-income and middle-income countries, calling for further investment and expansion of telemedicine services in such areas., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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17. Unveiling the truth: is COVID-19 reimbursement in Colombia a flawed design? A cost-of-illness analysis for moderate, severe and critical infections.

Author: Fernandez-Trujillo L, Sangiovanni S, Castrillon AI, Hincapie-Zapata L, Góez-Mogollón LM, Brun Vergara M, and Prada SI
Subjects: Humans, Colombia epidemiology, Pandemics, Hospitalization, Intensive Care Units, COVID-19
Abstract: Purpose: This study examines the financial impact of the COVID-19 pandemic on the Colombian Health System, focusing on the adequacy of reimbursement rates for inpatient stays. The study, based on a cost of illness analysis, aims to evaluate the effectiveness of the reimbursement scheme and identify potential economic losses within the health system., Patients and Methods: The study protocol outlines the inclusion criteria for patients >18 years with confirmed COVID-19 infection and moderate to critical disease. Patients hospitalised between June 2020 and June 2021 for at least 24 hours were included. Exclusion criteria involved pregnant patients and those initially hospitalised for non-COVID-19., Results: The study included 781 patients contributing to 790 hospitalisations. Demographic and clinical characteristics were analysed, with critical illness being the most prevalent category (61%). The overall mortality rate was 20.3%, primarily observed in critically ill patients. In the general ward for moderate cases, the reimbursement rate saw a substantial increase from US$3237 in 2020 to US$6760 in 2021, surpassing median resource utilisation. However, for severe cases in the intermediate care unit, reimbursement rates decreased, indicating potential insufficiency in covering costs. In the intensive care unit for critical cases, despite improved reimbursement rates, median resource utilisation still exceeds the 2021 rate, suggesting financial insufficiency in reimbursement rates., Conclusion: Our study underscores the inadequacies of the previous reimbursement system in addressing the varying resource utilisation and costs associated with COVID-19 inpatient care. Our analysis reveals substantial discrepancies between estimated costs and actual resource utilisation, particularly for severe and critical cases. We advocate for government flexibility in revising reimbursement baskets, supported by pilot studies to assess effectiveness. The use of real-world evidence forms a crucial basis for informed adjustments to reimbursement levels in preparation for future pandemics. This proactive approach ensures alignment between reimbursement policies and the actual costs associated., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2024
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18. Managed competition in Colombia: convergence of public and private insurance and delivery.

Author: Castano R, Prada SI, Maldonado N, and Soto V
Abstract: The Colombian health system has made a deep transition into managed competition since a major reform in 1993. A market for insurers was created, the consumer has free choice of insurer and a national-level equalisation fund distributes revenues via a per-capita payment. Fully subsidised insurance for the poor and informal, and a comprehensive standardised benefit package for subsidised and contributory schemes (both schemes covering 98 per cent of the population), has led to a low level of out-of-pocket expenses and high financial protection, as well as to reduced gaps in equity in access. The preconditions for managed competition are largely met, but improving health care providers' organisation towards integrated care, to enable them to deliver more value, is a necessary step to achieve the expected results of managed competition in terms of efficiency and quality. Although the current system is likely to be reformed in the coming months, the nature and extent of those reforms are not defined yet, so our analysis is based on the current system.
Published: 2024
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19. Scarcity in abundance? Spatial inequalities in Rheumatoid Arthritis in a health system with financial equity.

Author: Maldonado N, Camacho S, Prada SI, Hormaza-Jaramillo A, Soto V, García W, Paredes N, and Cardona F
Abstract: Background: This paper estimates spatial inequalities of Rheumatoid Arthritis (RA) in Colombia and explores correlates of those disparities from a health system perspective., Methods: We apply descriptive epidemiology to healthcare administrative records for estimation of crude and age-standardized prevalences, and health systems thinking for identification of barriers to effective access in RA diagnosis., Results: The crude and age-standardized RA prevalence for Colombia in 2018 is estimated at 0.43% and 0.36%, respectively. In the contributory regime, the binding constraint is effective access to rheumatologists in rural and sparsely populated areas; this constraint in workforce affects service delivery, and ultimately comes from the lack of a differentiated model for effective provision of healthcare in those areas (governance)., Conclusions: There are opportunities for implementation of public health policies and health system interventions that would lead to a better identification of RA patients and the subsequent more precise estimation of RA prevalence, and most importantly, to reduce exposition to risk factors and accurate diagnosis and treatment of RA patients., (© 2023. The Author(s).)
Published: 2023
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20. Automated extraction of information from free text of Spanish oncology pathology reports.

Author: Mendoza-Urbano DM, Garcia JF, Moreno JS, Bravo-Ocaña JC, Riascos AJ, Zambrano Harvey A, and Prada SI
Subjects: Humans, Registries, Algorithms
Abstract: Background: Pathology reports are stored as unstructured, ungrammatical, fragmented, and abbreviated free text with linguistic variability among pathologists. For this reason, tumor information extraction requires a significant human effort. Recording data in an efficient and high-quality format is essential in implementing and establishing a hospital-based-cancer registry., Objective: This study aimed to describe implementing a natural language processing algorithm for oncology pathology reports., Methods: An algorithm was developed to process oncology pathology reports in Spanish to extract 20 medical descriptors. The approach is based on the successive coincidence of regular expressions., Results: The validation was performed with 140 pathological reports. The topography identification was performed manually by humans and the algorithm in all reports. The human identified morphology in 138 reports and by the algorithm in 137. The average fuzzy matching score was 68.3 for Topography and 89.5 for Morphology., Conclusions: A preliminary algorithm validation against human extraction was performed over a small set of reports with satisfactory results. This shows that a regular-expression approach can accurately and precisely extract multiple specimen attributes from free-text Spanish pathology reports. Additionally, we developed a website to facilitate collaborative validation at a larger scale which may be helpful for future research on the subject., Competing Interests: Conflict of interests: authors declare no conflict of interest., (Copyright © 2023 Colombia Medica.)
Published: 2023
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21. A comparison of resource use of insured and uninsured venezuelan migrants: evidence from the hospital setting.

Author: Prada SI, Pulgarín-Rodríguez E, Hincapié-Zapata L, and Pizarro AB
Subjects: Humans, Insurance, Health, Health Services, Hospitals, Medically Uninsured, Transients and Migrants
Abstract: Background: There is no characterization of resource use in the hospital setting for immigrants in Colombia, we aimed to describe the resource use by Venezuelan immigrants, comparing those enrolled in the national health insurance system with those with and without the ability to pay., Methods: Retrospective review in the billing data system of our Hospital from 2011 to 2020. We collected information for 6,837 hospital episodes associated with 1,022 Venezuelan patients, hospital's billing information for all services rendered was extracted., Results: The mean cost per patient event were 4,595 USD for those without the ability to pay, costing 2.37 times more than a legal resident insured. Care in the ICU, inpatient days, surgery, and OB-GYN department consume most resources provided to vulnerable migrants., Discussion: Enrolment in the national health insurance may allow better access to health services by vulnerable Venezuelan migrants and thus reduce resource use for the health system., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)
Published: 2023
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22. Priorities in Biobanking Research: A Report on the 2021 ISBER Round Table.

Author: Byrne JA, Banaszak AT, Carpenter JE, Carroll SL, Castelhano MG, Espinal PS, Henderson MK, Hettiaratchi A, Maseme M, Ng W, Patel K, Popescu I, Prada SI, Schleif WS, Smith M, Wee S, Weil CJ, and Woods K
Subjects: Biological Specimen Banks, Biomedical Research
Published: 2023
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23. Hospital-based COVID-19 registry: Design and implementation. Colombian experience.

Author: Rodriguez S, Guzmán TM, Tafurt E, Beltrán E, Castro A, Rosso F, Prada SI, and Zarama V
Abstract: Registries are essential to providing valuable clinical and epidemiological decisions. Designing a registry is challenging because it is time-consuming and resource-intensive, particularly in low- and middle-income countries. Here, we described our experience with the rationale, design, and implementation of a hospital-based COVID-19 registry in Cali, Colombia. We designed and implemented a hospital-based registry over a dynamic web-based structure to record all sociodemographic, clinical, and laboratory tests, imaging, treatment, and outcomes of SARS-CoV-2. We included 4458 confirmed COVID-19 cases of 18 years and older from March 2020 to March 2021. The median age was 48 years. The most frequent comorbidities were hypertension, obesity, and diabetes. The ICU admission rate was 19%, and the in-hospital mortality rate was 20%. The implemented strategies provided rapid and reliable information collection for the registry of emerging studies from the different clinical areas. Regular data quality and feedback are essential to ensure the reliability of the information. The integration of automatic data extraction reduces time consumption in information gathering and resources., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)
Published: 2023
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24. Decreases in resource use after implementing an interdisciplinary management program for patients with placenta accreta spectrum.

Author: Prada SI, Nieto-Calvache AJ, López-Girón MC, Pulgarín-Rodriguez EE, and Hincapié-Zapata LC
Subjects: Female, Health Resources, Humans, Morbidity, Pregnancy, Retrospective Studies, Placenta Accreta surgery
Abstract: Objective: Placenta accreta spectrum (PAS) often causes severe morbidity and demands the availability of abundant health resources. Research has shown that the participation of experienced interdisciplinary groups in specialized centers improves clinical outcomes. Our objective is to measure resource use variation after implementing an interdisciplinary management program for this condition., Methods: Using detailed billing information, hospital care resource use was measured at constant prices for women with PAS who were treated between 2011 and 2019. Cases were classified before (Group 1) and after (Group 2) the implementation of the program. A third group included women with intraoperative MAP findings (Group 3). Comparisons were made using descriptive statistics., Results: The mean reduction in resource use after the program was 16.5% per patient. The program also reduced variability in resource use as measured by the standard deviation and the coefficient of variation, which decreased by 55.2% and 46.3%, respectively., Conclusion: The interdisciplinary management of patients affected by PAS in experienced hospitals is associated with a reduction in resource use and variability.
Published: 2022
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25. Safe and effective re-use policy for high-efficiency filtering facepiece respirators (FFRS): Experience of one hospital during the Covid-19 pandemic in 2020.

Author: Prada SI, Vivas Á, Garcia-Garcia MP, Rosero E, Orrego M, Candelo JS, España J, Soto G, Martínez D, and García L
Abstract: The high transmissibility rate of the Severe Acute Respiratory Syndrome Coronavirus 2 facilitated an exponential growth in the number of infections, posing a tremendous threat to healthcare systems across the world. The use of Non-oil 95% efficiency (N95) respirators demonstrated to reduce the risk of virus transmission. The escalated demand in N95 respirators during 2020 generated a massive shortage worldwide which resulted in serious implications, one being an increase in healthcare providers' costs. In response, various optimization strategies were implemented. This study aimed to assess the implementation of a safe and effective re-use policy for high-efficiency filtering facepiece respirators (FFRs) in a high-complexity university hospital in 2020. Associated costs were estimated through a descriptive accounting analysis of resources saved. Acceptability, appropriateness, and feasibility rates were 80.5%, 78.8%, and 83.6%, respectively. With an implementation cost of approximately 10,000 USD, there was a 56.1% reduction in FFRs consumption, compared with a non-policy scenario, with savings exceeding 500,000 USD in 2020. In a pandemic scenario where it is vital to spare resources, a FFRs rational use policy demonstrated to be a highly cost-efficient alternative in order to save resources without increasing contagion risk among healthcare workers., Competing Interests: None declared., (© 2022 The Author(s).)
Published: 2022
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26. COVID-19 response in Colombia: Hits and misses.

Author: Prada SI, Garcia-Garcia MP, and Guzman J
Abstract: Introduction: Colombia has been hit particularly hard by the COVID-19 pandemic, being ranked 22nd among 187 countries in deaths per 100,000 people by February 2022. The country has also experienced the worst economic recession in its history, with real GDP contracting 7% in 2020. This paper describes Colombia's pre-pandemic context and the overall effect of the pandemic on health and economic indicators and examines the government's response to COVID-19., Methods: Descriptive chronologic policy analysis on the COVID-19 pandemic in Colombia and the measures and interventions implemented, using publicly available secondary data from Colombia's official agencies and international sources published from March 2020 to February 2022., Results: The Colombian healthcare system increased its capacity in terms of infrastructure and human resources (from 8.6 ICU beds per 100,000 pre-pandemic to 21.9 in 2020, from 1.7 to 1.3 per 1000 doctors and nurses, respectively in 2019 to 1.8 and 1.5 per 1000 in 2020). The government commenced the National Vaccination Strategy on February 17, 2021, despite a slow start it managed to fully vaccinate 65.1% of its population, including Venezuelan immigrants, by February 2022., Conclusions: Colombia's response to the pandemic combines hits and misses. The country organized an early and robust response; increased its healthcare system capacity; designed a risk-based, equitable, and inclusive national vaccination strategy; and introduced a flexible and responsive vaccine rollout. However, the government chose the wrong timing for reform, implemented a long and unpredictable lockdown, was late to procure COVID-19 vaccines and has not appropriately tackled vaccine hesitancy., Public Interest Summary: Colombia has been hit particularly hard by the COVID-19 pandemic, with over 138,000 COVID-19 deaths and over 6 million cases by the end of February 2022. According to number of deaths per 100,000 people, Colombia ranks 22nd in the world, among 187 countries. The country has also experienced the worst economic recession in its history. The Colombian healthcare system has been able to cope with a high number of COVID-19 cases without collapsing, but some public health indicators deteriorated. Colombia's response to the pandemic combines hits and misses. The country organized an early and robust response; increased its healthcare system capacity; designed a risk-based, equitable, and inclusive national vaccination strategy; and introduced a flexible and responsive vaccine rollout. As of February 2022, Colombia has fully vaccinated 65.1% of its population. However, the government chose the wrong timing for a tax reform, implemented a long and unpredictable lockdown, was late to procure COVID-19 vaccines and has not appropriately tackled vaccine hesitancy, which certainly contributed to its undesirable position in the mortality world raking., Competing Interests: None declared., (© 2022 Fellowship of Postgraduate Medicine. Published by Elsevier Ltd. All rights reserved.)
Published: 2022
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27. Increase in direct costs for health systems due to lupus nephritis: the case of Colombia.

Author: Prada SI, Pérez AM, Nieto-Aristizábal I, and Tobón GJ
Subjects: Colombia epidemiology, Costs and Cost Analysis, Humans, Lupus Erythematosus, Systemic complications, Lupus Nephritis complications
Abstract: Objective: Lupus nephritis is one of the most severe complications of systemic lupus erythematosus and it has been estimated that can occur in up to 60% of patients. Direct costs of lupus nephritis have not been studied in developing countries. This study aimed to describe lupus nephritis direct costs in Colombia., Methods: Administrative data from two Colombian health maintenance organizations for 2014 and 2015 was obtained. An algorithm based on the International Statistical Classification of Diseases and Related Health Problems 10th revision codes was developed to identify patients with lupus nephritis and lupus nephritis under study., Results: The average annual per-patient, all-claims, all-cause direct cost for lupus nephritis was US$ 12,624, 7.5 times higher than the average lupus patient without lupus nephritis. For lupus nephritis cases under study, estimated direct cost was US$ 3,664, 2 times higher than average lupus patient in Colombia. Difference in lupus nephritis patients is mainly accounted for the cost and frequency of procedures, exceeding by a factor of 5 the cost for durable medical equipment and the cost for drugs, respectively., Conclusion: Lupus patients who progress to lupus nephritis stage increased seven-fold the average annual per-patient, all-claims, and all-cause direct cost for the Colombian health system.
Published: 2022
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28. Direct cost of Parkinson's disease in a health system with high judicialization: evidence from Colombia.

Author: Prada SI, Pérez AM, Valderrama-Chaparro J, Molina-Echeverry MI, Orozco JL, and Takeuchi Y
Subjects: Adult, Aged, Aged, 80 and over, Colombia, Female, Health Expenditures statistics & numerical data, Health Maintenance Organizations statistics & numerical data, Humans, Insurance, Health economics, Insurance, Health standards, Male, Middle Aged, Parkinson Disease therapy, Health Care Costs statistics & numerical data, Health Maintenance Organizations economics, Parkinson Disease economics
Abstract: Objective : To estimate all-claims-all-conditions expenditures paid for by health plans for patients suffering from Parkinson´s disease (PD). Methods : Using administrative claims data from two health maintenance organizations for 2014 and 2015 in Colombia, we identified 2,917 patients with PD by applying an algorithm that uses International Statistical Classification of Diseases and Related Health Problems and Anatomical Therapeutic Chemical Classification System codes. Descriptive statistics were applied to compute unadjusted all-cause median costs. A generalized linear model was used to estimate adjusted and attributable direct costs of advanced PD. Results : Approximately 30% of the all-cause direct costs were associated with technologies not included in universal health coverage benefit packages. In 2015, the annual median interquartile range per patient all-cause direct costs to insurers was USD1,576 (605-3,617). About 16% of patients had advanced PD. Regression analysis estimated that additional costs attributable to advanced PD was USD3,416 (p = 0.000). Multimorbidity was highly prevalent, and 96% of PD patients had at least one other chronic condition. Conclusions : In the context of high judicialization, patients suffering from PD must increasingly use the judicial system to access treatment. To promote more equitable and efficient access benefit packages, developing countries must consider more thoroughly the needs of these patients.
Published: 2020
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29. Parkinson's disease prevalence, age distribution and staging in Colombia.

Author: Orozco JL, Valderrama-Chaparro JA, Pinilla-Monsalve GD, Molina-Echeverry MI, Pérez Castaño AM, Ariza-Araújo Y, Prada SI, and Takeuchi Y
Abstract: Parkinson's disease (PD) has the second highest prevalence among neurodege - nerative diseases. In Colombia, PD population dynamics are currently unknown. Health records offer a unique resource to study frequency and multi-morbidity of chronic diseases. The aim of this research is to estimate prevalence and staging using administrative data (AD) provided by Health Maintenance Organizations (HMOs). A cross-sectional study was conducted using 2015 AD from two Colombian HMOs (4.312.928 beneficiaries, 9.01% of the affiliated Colombian population). PD prevalence and severity was estimated by age and sex. Prevalence was adjusted to WHO demographics. Age-adjusted PD prevalence was 205.89 per 100.000 inhabitants. Prevalence increment of 62.13% was found between those aged ≥40 years and those aged ≥50 years. Similarly, each extra decade (50-80+) represented an increment of 83.65%, 80.95%, and 35.10%. Between 40 and 89 years, males exhibited a significantly higher PD prevalence compared to females. Advanced PD was more frequent as age increased from 3.77% in the group between 40 to 49 years to 25.86% in those older than 89 years. More common related comorbidities were arterial hypertension, diabetes, and psychiatric disorders; the first two increased their frequency with age, and the last one maintained its prevalence across all age groups. AD sets are useful to estimate the prevalence and staging of PD. Prevalence of PD in Colombia is higher in men and increases with age, as well as disease severity., Competing Interests: Conflict of interest: The authors declare no conflicts of interest., (©Copyright: the Author(s).)
Published: 2020
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30. Cost-effectiveness analysis of VECTOS software for the control of diseases transmitted by Aedes aegypti in two Colombian municipalities

Author: Salinas MA, Soto VE, and Prada SI
Subjects: Animals, Colombia epidemiology, Cost-Benefit Analysis, Costs and Cost Analysis, Decision Support Techniques, Decision Trees, Dengue economics, Dengue epidemiology, Dengue transmission, Humans, Incidence, Mosquito Control methods, Mosquito Control organization & administration, Workforce economics, Workforce statistics & numerical data, Aedes virology, Dengue prevention & control, Mosquito Control economics, Mosquito Vectors virology, Urban Health
Abstract: Introduction: Diseases transmitted by Aedes aegypti are considered a public health problem. VECTOS is a novel software for the integration of vector control strategies. Objective: To assess the cost-effectiveness of the use of VECTOS in the routine control programs of diseases transmitted by A. aegypti in the municipality of San Juan de Girón (Santander). Materials and methods: We conducted a cost-effectiveness analysis using a decision analysis model from the perspective of the local health authorities. We considered the use of the VECTOS software in the routine control activities in the municipality of San Juan de Girón during 2016 as the treatment group while the routine control in the municipality of Floridablanca, where VECTOS is not implemented, was considered as the comparator. We calculated the incremental cost-effectiveness ratio (ICER) taking as effectiveness measure the disability-adjusted life years (DALY). Results: VECTOS was cost-effective at a rate of USD$ 660,4 savings per each DALY avoided compared to the routine control in Floridablanca. The probabilistic model showed that the system was cost-effective in 70% of the 10.000 iterations for a threshold between 1 to 3 GDP per capita. Conclusions: VECTOS software as implemented in the municipality of San Juan de Girón is highly cost-effective and could be used in other municipalities in the country where diseases transmitted by A. aegypti are endemic.
Published: 2020
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31. Analyzing Factors Associated with Trash Pickers' Health Status: Census Data in a Major City in Colombia.

Author: Martínez L, Zuluaga B, and Prada SI
Subjects: Colombia, Female, Humans, Male, Mental Disorders prevention & control, Risk Factors, Health Status, Occupational Health, Refuse Disposal
Abstract: This study aims to identify factors associated with the probability of trash pickers feeling physically or mentally ill and assesses differences by gender. To achieve these, we estimated multivariate regression models by using data from a census' update of 3109 trash pickers in Cali-Colombia in 2015. Outcomes are defined by two binary variables for whether the trash picker reports 14 or more days during the last month with physical and mental illness. Factors included demographic, family, psychological, socioeconomic and job characteristics. We found gender differences in several risk factors. Also a strong link between physical and mental health was found. Trash picker women are more vulnerable than men, public policy interventions aimed at prevention and treatment of mental health problems will have a positive side effect on their physical and mental health.
Published: 2020
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32. Mental health, interpersonal trust and subjective well-being in a high violence context.

Author: Martínez LM, Estrada D, and Prada SI
Abstract: This paper assesses whether two factors of wellbeing, social capital (interpersonal trust and social networks) and subjective well-being are associated with frequent mental distress and if there are any mediating effects by gender in a city of high urban violence. This paper relies on data that comes from a sample of over 1300 people representative by gender, race/ethnicity, and socioeconomic breakdown of the city of Cali in Colombia, which was collected in 2017 through face-to-face surveys. Our study uses logistic regression with fixed-effects at the district level to control for unobserved time-invariant factors. At the individual level, our analyses account for social and demographic context variables. The dependent variable is mental distress, defined as having 14 or more days feeling mentally ill in the previous 30-day period. Independent variables of interest are "interpersonal trust in unknown people" measured in a scale 0-10 and, social networks measured using the number of family members and close friends and subjective well-being through a question about life satisfaction in a scale 0-10. We find risk factors for mental health distress were low trust in unknown people, low life satisfaction, high levels of depression, living in cohabitation, being female, not having children, and living in middle socio-economic status. The odds of feeling mentally ill decreased as trust in unknown people increased by each unit in the trust scale (OR: 0.92). There were gender differences, with women's mental health being less likely to be affected by lack of interpersonal trust (OR: 0.94) than men (OR: 0.76). Our study suggests that actions aimed at fostering interpersonal trust in unknown people could positively affect mental health distress for both males and females. In the context of high urban violence, our study shows that men are more likely to benefit from such actions.
Published: 2019
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33. Comparing the Medicaid Prospective Drug Utilization Review Program Cost-Savings Methods Used by State Agencies in 2015 and 2016.

Author: Prada SI and Loaiza JS
Abstract: Background: The Medicaid Drug Utilization Review (DUR) program is a 2-phase process conducted by Medicaid state agencies. The first phase is a prospective DUR process and involves electronically monitoring prescription drug claims to identify prescription-related problems, such as therapeutic duplication, contraindications, incorrect dosage, or duration of treatment. The second phase is a retrospective DUR involving ongoing, periodic examinations of claims data to identify patterns of fraud, abuse, underutilization, drug-drug interaction, and medically unnecessary care, and implement corrective actions when needed. The Centers for Medicare & Medicaid Services requires each state to measure the prescription drug cost-savings generated from its DUR programs annually, but it provides no methodology for doing so. An earlier article compared the methodologies used by states to measure cost-savings in their retrospective DUR program in fiscal years 2014 and 2015., Objective: To describe and synthesize the methodologies used by states to measure cost-savings using their Medicaid prospective DUR program in federal fiscal years 2015 and 2016., Methods: For each state, we downloaded from Medicaid's website the cost-savings methodologies included in the Medicaid DUR 2015 and 2016 reports. We then reviewed and synthesized the reports. Methods described by the states were classified into a unique group based on the methodology used, except for Arkansas and Connecticut, which were classified in more than 1 category for the same period., Results: Currently, 3 different methodologies are being used by states. In 2015 and 2016, the most common methodology used (by 18 states) was the calculation of total claim rejections and subtracting claim resubmissions at the amount actually paid. The comparisons of DUR program cost-savings among states are unreliable, because the states lack a common methodology in the way they measure their performance., Conclusions: Considering the lack of methodologic consistency among states in measuring the savings in the Medicaid DUR program shown in this analysis, the federal government must lead an effort to define a unique methodology to measure cost-savings in its entire DUR program. This will help to improve the measure of savings among states and understand how this program is performing in that matter.
Published: 2019

34. Higher pharmaceutical public expenditure after direct price control: improved access or induced demand? The Colombian case.

Author: Prada SI, Soto VE, Andia TS, Vaca CP, Morales ÁA, Márquez SR, and Gaviria A
Abstract: Background: High pharmaceutical expenditure is one of the main concerns for policymakers worldwide. In Colombia, a middle-income country, outpatient prescription represents over 10% of total health expenditure in the mandatory benefits package (POS), and close to 90% in the complementary government fund (No POS). In order to control expenditure, since 2011, the Ministry of Health introduced price caps on inpatient drugs reimbursements by active ingredient. By 2013, more than 400 different products, covering 80% of public pharmaceutical expenditure were controlled. This paper investigates the effects of the Colombian policy efforts to control expenditure by controlling prices., Methods: Using SISMED data, the official database for prices and quantities sold in the domestic market, we estimate a Laspeyres price index for 90 relevant markets in the period 2011-2015, and, then, we estimate real pharmaceutical expenditure., Results: Results show that, after direct price controls were enacted, price inflation decreased almost - 43%, but real pharmaceutical expenditure almost doubled due mainly to an increase in units sold. Such disproportionate increase in units sold maybe attributable to better access to drugs due to lower prices, and/or to an increase in marketing efforts by the pharmaceutical industry to maintain profits., Conclusions: We conclude that pricing interventions should be implemented along with a strong market monitoring to prevent market distortions such as inappropriate and unnecessary drug use.
Published: 2018
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35. Comparing the Medicaid Retrospective Drug Utilization Review Program Cost-Savings Methods Used by State Agencies.

Author: Prada SI
Abstract: Background: The Medicaid Drug Utilization Review (DUR) program is a 2-phase process conducted by Medicaid state agencies. The first phase is a prospective DUR and involves electronically monitoring prescription drug claims to identify prescription-related problems, such as therapeutic duplication, contraindications, incorrect dosage, or duration of treatment. The second phase is a retrospective DUR and involves ongoing and periodic examinations of claims data to identify patterns of fraud, abuse, underutilization, drug-drug interaction, or medically unnecessary care, implementing corrective actions when needed. The Centers for Medicare & Medicaid Services requires each state to measure prescription drug cost-savings generated from its DUR programs on an annual basis, but it provides no guidance or unified methodology for doing so., Objectives: To describe and synthesize the methodologies used by states to measure cost-savings using their Medicaid retrospective DUR program in federal fiscal years 2014 and 2015., Method: For each state, the cost-savings methodologies included in the Medicaid DUR 2014 and 2015 reports were downloaded from Medicaid's website. The reports were then reviewed and synthesized. Methods described by the states were classified according to research designs often described in evaluation textbooks., Discussion: In 2014, the most often used prescription drugs cost-savings estimation methodology for the Medicaid retrospective DUR program was a simple pre-post intervention method, without a comparison group (ie, 12 states). In 2015, the most common methodology used was a pre-post intervention method, with a comparison group (ie, 14 states). Comparisons of savings attributed to the program among states are still unreliable, because of a lack of a common methodology available for measuring cost-savings., Conclusion: There is great variation among states in the methods used to measure prescription drug utilization cost-savings. This analysis suggests that there is still room for improvement in terms of methodology transparency, which is important, because lack of transparency hinders states from learning from each other. Ultimately, the federal government needs to evaluate and improve its DUR program.
Published: 2017

36. Actual expense associated with patients with Alzheimer's disease in Colombia.

Author: Prada SI, Takeuchi Y, Merchán-Galvis AM, and Ariza-Araújo Y
Subjects: Aged, Aged, 80 and over, Alzheimer Disease drug therapy, Colombia, Comorbidity, Cost of Illness, Female, Humans, Male, Middle Aged, Neuroprotective Agents therapeutic use, Regression Analysis, Severity of Illness Index, Alzheimer Disease economics, Drug Costs statistics & numerical data, Health Care Costs statistics & numerical data
Abstract: Background: There is paucity in the level of knowledge on the actual insurer expenses associated with patients suffering with dementia in the developing world. Less is known about direct costs by severity and how costs vary because of the presence of other comorbidities., Methods: Using claims data from an insurer for three years, we identified patients with AD with an algorithm that takes advantage of information on age, primary diagnosis, and services and drugs provided., Results: Distribution by dementia stage was as follows: mild 21%, moderate 53%, severe 17%, and undetermined 9%. Expenses paid for all causes by the insurer were at least double than estimated in the literature and were increasing annually at rates higher than 30%. Also, 92% of patients have at least another chronic condition., Conclusions: Worldwide costs of dementia estimates maybe underestimating the actual costs to health systems in the developing world.
Published: 2017
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37. [Chronic diseases and insured spending in Colombia].

Author: Prada SI and Pérez Castaño AM
Subjects: Colombia, Humans, Chronic Disease economics, Health Expenditures, Insurance, Health
Published: 2017
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38. Barrier to Access or Cost Share? Coinsurance and Dental-Care Utilization in Colombia.

Author: Higuera L and Prada SI
Subjects: Adult, Colombia, Cost Sharing economics, Cost Sharing statistics & numerical data, Dental Care statistics & numerical data, Female, Health Services Accessibility statistics & numerical data, Humans, Male, Cost Sharing methods, Deductibles and Coinsurance economics, Dental Care economics, Health Services Accessibility economics, Insurance, Dental economics
Abstract: Background: Copayments, deductibles, and coinsurance, are elements of health-care systems to make prices salient for the insured. Individuals may respond differently to cost sharing, according to the type of care they seek; dental care, as a combination of both acute and elective care, is an ideal setting to study the effects of cost-sharing mechanisms on utilization., Objective: To test how coinsurance affects dental-care utilization in a middle-income country context., Methods: This study uses policy variations in the Colombian health-care system to analyze changes in dental-care utilization due to different levels of coinsurance. We used matching procedures to balance observed differences in pre-treatment variables between those who face coinsurance (non-policy holders, or beneficiaries) and those who don't (policyholders). We use zero-inflated negative binomial models for the count of visits and two-part models for total expenditures, and test for unobservable confounders with random-effect models and instrumental variables., Results: Individuals who face coinsurance are less likely to have any dental-care utilization, at a relatively small scale. Facing coinsurance does not correlate with changes in total expenditures. Falsification tests with dental-care visits exempt from coinsurance show no statistically distinguishable changes in utilization. Random-effect models and instrumental variable models show results similar to the main specification., Conclusions: Cost-sharing policies in Colombia seem to be well designed because they don't represent an important barrier to dental-care access.
Published: 2016
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39. Alcohol use disorders and psychiatric diseases in Colombia.

Author: Rincon-Hoyos HG, Castillo A, and Prada SI
Subjects: Adult, Aged, Colombia epidemiology, Comorbidity, Female, Humans, Male, Middle Aged, Prevalence, Regression Analysis, Sex Factors, Socioeconomic Factors, Substance-Related Disorders epidemiology, Alcohol-Related Disorders epidemiology, Mental Disorders epidemiology
Abstract: Background: An accurate understanding of co-occurrence and comorbidity of alcohol use disorders (AUD) in Colombia is crucial for public health., Objective: A secondary analysis was conducted, using a 2003/2004 government´s population database to determine the lifetime associations between AUD and other mental and addictive disorders in people of Colombia aged 18-65 years., Methods: Several statistical analysis were performed: testing prevalence difference in mental disorders by whether the individual had an AUD; a stratified analysis by gender and logistic regression analyses accounting for differences in demographic, socio-economic, behavioral and self-reported health status variables., Results: People with AUD comprised 9% of the population, of which 88% were males and on average 37 years old. They were more likely to be males, be working, and be current smokers; and less likely to be at home or retired. The population with AUD had greater chance to comply with criteria for all disorders but minor depressive disorder, post-traumatic stress disorder, nicotine dependence, and oppositional defiant disorder., Conclusion: This study demonstrates a high prevalence of mental disorders in the adult population with AUD in Colombia. The findings highlight the importance of comorbidity as a sign of disease severity and impact on public health and supports the need for training of more professionals and developing appropriate interventions and services.
Published: 2016

40. What are some of the features of worksite wellness interventions in the United States?

Author: Martinez L and Prada SI
Subjects: Humans, United States, Workplace, Health Promotion organization & administration, Occupational Health, Occupational Health Services organization & administration
Abstract: The Occupational Medicine Forum is prepared by the ACOEM Occupational and Environmental Medical Practice Committee and does not necessarily represent an official ACOEM position. The Forum is intended for health professionals and is not intended to provide medical or legal advice, including illness prevention, diagnosis or treatment, or regulatory compliance. Such advice should be obtained directly from a physician and/or attorney.
Published: 2015
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41. Level-I trauma centre treatment effects on return to work in teaching hospitals.

Author: Prada SI, Salkever D, and MacKenzie EJ
Subjects: Adolescent, Adult, Air Ambulances economics, Female, Humans, Injury Severity Score, Length of Stay economics, Male, Middle Aged, Return to Work, Surveys and Questionnaires, Treatment Outcome, Work Capacity Evaluation, Wounds and Injuries economics, Wounds and Injuries physiopathology, Wounds and Injuries psychology, Air Ambulances statistics & numerical data, Hospitals, Teaching, Length of Stay statistics & numerical data, Trauma Centers economics, Wounds and Injuries rehabilitation
Abstract: Background: Previous research found a positive effect of Level-I trauma centres on return to work outcomes for patients 18-64 years old who were mainly working before injury. Trauma centres were compared to hospitals that differed on average in characteristics such as size and staffing, among others. Thus, a portion of the effect found could be due to general differences in hospital variables rather than the special characteristics of Level I trauma centres. Comparing Level I trauma centres to other Teaching hospitals provides a more refined test of the effect of these centres on return-to-work outcomes., Methods: The National Study on the Costs and Outcomes of Trauma (NSCOT) is the main source of data for our empirical investigation. We used non-linear instrumental variables methods to control for unobserved characteristics and restrict the sample to teaching hospitals. The first method is the two-stage residual inclusion model in which we identify the effect using the proportion of resident population served by Helicopter Ambulance Services (at the state level) as an instrumental variable. The second method is a recursive bivariate probit model., Results: We found that treatment at Level-I trauma centres has a positive effect on return to work outcomes three months after injury. The estimated effect is statistically significant and positive, but lower than the estimate that did not focus on teaching hospitals., Conclusions: A previous study found positive effects of treatment at a Level-I trauma centre on return-to-work outcomes, however, a portion of the effect found was due to general differences in hospital variables., (Copyright © 2014 Elsevier Ltd. All rights reserved.)
Published: 2014
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42. Population-level effects of depression diagnosis on Medicare payments and use.

Author: Prada SI
Subjects: Aged, Aged, 80 and over, Depression diagnosis, Female, Hospitalization economics, Humans, Male, Medicare economics, Sex Factors, Skilled Nursing Facilities economics, United States epidemiology, Depression economics, Depression epidemiology, Hospitalization statistics & numerical data, Medicare statistics & numerical data, Skilled Nursing Facilities statistics & numerical data
Published: 2014
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43. Quantifying the effect of a cancer diagnosis on Medicare payments and use according to new Public Use Files.

Author: Prada SI
Subjects: Aged, Aged, 80 and over, Female, Health Expenditures, Humans, Male, Medicare statistics & numerical data, Middle Aged, Neoplasms diagnosis, United States epidemiology, Medicare economics, Neoplasms economics, Neoplasms epidemiology
Published: 2014
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44. Medicare Public Use Files and Alzheimer's disease factors in 2008 and 2010.

Author: Prada SI
Subjects: Aged, Aged, 80 and over, Alzheimer Disease economics, Chronic Disease, Comorbidity, Fee-for-Service Plans statistics & numerical data, Female, Humans, Insurance, Health, Reimbursement statistics & numerical data, Internet, Male, Medicare economics, Middle Aged, Office Visits statistics & numerical data, Patient Admission statistics & numerical data, United States, User-Computer Interface, Access to Information, Alzheimer Disease epidemiology, Databases, Factual, Medicare statistics & numerical data
Published: 2013
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45. Medicare payments: how much do chronic conditions matter?

Author: Erdem E, Prada SI, and Haffer SC
Subjects: Age Factors, Aged, Chronic Disease epidemiology, Fee-for-Service Plans economics, Fee-for-Service Plans statistics & numerical data, Female, Health Care Costs statistics & numerical data, Humans, Ischemic Attack, Transient economics, Ischemic Attack, Transient epidemiology, Male, Medicare statistics & numerical data, Medicare Part A economics, Medicare Part A statistics & numerical data, Medicare Part B economics, Medicare Part B statistics & numerical data, Middle Aged, Neoplasms economics, Neoplasms epidemiology, Prevalence, Renal Insufficiency, Chronic economics, Renal Insufficiency, Chronic epidemiology, Sex Factors, Stroke economics, Stroke epidemiology, United States epidemiology, Chronic Disease economics, Medicare economics
Abstract: Objective: Analyze differences in Medicare Fee-for-Service utilization (i.e., program payments) by beneficiary characteristics, such as gender, age, and prevalence of chronic conditions., Methods: Using the 2008 and 2010 Chronic Conditions Public Use Files, we conduct a descriptive analysis of enrollment and program payments by gender, age categories, and eleven chronic conditions., Results: We find that the effect of chronic conditions on Medicare payments is dramatic. Average Medicare payments increase significantly with the number of chronic conditions. Finally, we quantify the effect of individual conditions and find that "Stroke / Transient Ischemic Attack" and "Chronic Kidney Disease" are the costliest chronic conditions for Part A, and "Cancer" and "Chronic Kidney Disease" are the costliest for Part B.
Published: 2013
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46. Level-I trauma center effects on return-to-work outcomes.

Author: Prada SI, Salkever D, and Mackenzie EJ
Subjects: Adolescent, Adult, Colombia, Female, Humans, Injury Severity Score, Male, Middle Aged, Multivariate Analysis, Occupational Health economics, Propensity Score, Prospective Studies, Risk, Surveys and Questionnaires, Trauma Centers statistics & numerical data, Work Capacity Evaluation, Wounds and Injuries economics, Young Adult, Occupational Health statistics & numerical data, Trauma Centers economics, Treatment Outcome, Wounds and Injuries rehabilitation
Abstract: Background: Injury is the leading cause of death for persons aged 1-44 years in the United States. Injuries have a substantial economic cost. For that reason, regional systems of trauma care in which the more acutely injured patients are transported to Level-I (L-I) trauma centers (TCs) has been widely advocated. However, the cost of TC care is high, raising questions about the value of such an approach., Objectives: To study L-I TC effectiveness and study return-to-work (RTW) outcomes., Research Design: Using data from National Study on the Costs and Outcomes of Trauma, the authors address the issue of selection bias by comparing naive estimates to matching techniques, as well as to nonlinear instrumental variable models (2SRI) and bivariate probit estimators., Subjects: Individuals ages 18-64 who were mainly working before traumatic injury. Patients selected for the study were treated at 69 hospitals located in 12 states in the United States. N = 1790., Measures: Treatment is binary indicator on whether treated at L-I TC. Outcome is binary indicator on whether returned to work within 3 months after injury. Covariates include: demographics, pre-injury characteristics (job, health and insurance status), injury descriptors, other income sources, etc., Results: Across all models that control for unobserved factors, the authors find that L-I TC treatment is positively associated with RTW within 3 months after injury. The estimated average marginal effect of treatment on the probability of RTW ranges from 23 to 38 percentage points., Conclusions: Benefits of L-I TC care extend beyond mortality and morbidity.
Published: 2012
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