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Browsing by Author "Knight, Megan (57218877591)"

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    Publication
    Assessing performance of the Healthcare Access and Quality Index, overall and by select age groups, for 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019
    (2022)
    Haakenstad, Annie (56079498000)
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    Yearwood, Jamal Akeem (57202282849)
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    Fullman, Nancy (57211064970)
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    Bintz, Corinne (57215013911)
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    Bienhoff, Kelly (57201959866)
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    Weaver, Marcia R (7201548872)
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    Nandakumar, Vishnu (57204605749)
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    Joffe, Jonah N (57224994124)
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    LeGrand, Kate E (57216789066)
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    Knight, Megan (57218877591)
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    Abbafati, Cristiana (54917122400)
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    Abbasi-Kangevari, Mohsen (57193543882)
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    Abdoli, Amir (59421084100)
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    Zuñiga, Roberto Ariel Abeldaño (57737618600)
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    Adedeji, Isaac Akinkunmi (57208456508)
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    Adekanmbi, Victor (53463192900)
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    Adetokunboh, Olatunji O (56598104300)
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    Afzal, Muhammad Sohail (56009310800)
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    Afzal, Saira (7004381116)
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    Agudelo-Botero, Marcela (58888387100)
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    Ahinkorah, Bright Opoku (57194684030)
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    Ahmad, Sajjad (57218961022)
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    Ahmadi, Ali (57193998515)
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    Ahmadi, Sepideh (58189812000)
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    Ahmed, Ali (57201189007)
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    Rashid, Tarik Ahmed (57023479100)
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    Aji, Budi (55911737200)
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    Akande-Sholabi, Wuraola (57204532006)
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    Alam, Khurshid (57203681299)
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    Hamad, Hanadi Al (57779217200)
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    Alhassan, Robert Kaba (55829647800)
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    Ali, Liaqat (55646005400)
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    Alipour, Vahid (56436629300)
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    Aljunid, Syed Mohamed (6504304159)
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    Ameyaw, Edward Kwabena (57194076624)
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    Amin, Tarek Tawfik (23007746000)
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    Amu, Hubert (57190183918)
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    Amugsi, Dickson A (24461463800)
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    Ancuceanu, Robert (35728302200)
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    Andrade, Pedro Prata (58155276500)
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    Anjum, Afifa (57212707890)
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    Arabloo, Jalal (57208760927)
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    Arab-Zozani, Morteza (57210284593)
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    Ariffin, Hany (7004238528)
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    Arulappan, Judie (57224210161)
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    Aryan, Zahra (55479968600)
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    Ashraf, Tahira (56366752600)
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    Atnafu, Desta Debalkie (57203502301)
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    Atreya, Alok (55856196800)
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    Ausloos, Marcel (7101798907)
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    Avila-Burgos, Leticia (8530790100)
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    Ayano, Getinet (57189617474)
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    Ayanore, Martin Amogre (57070358300)
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    Azari, Samad (56396696500)
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    Badiye, Ashish D (56340201200)
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    Baig, Atif Amin (49460999600)
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    Bairwa, Mohan (50461080100)
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    Bakkannavar, Shankar M (34970692400)
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    Baliga, Shrikala (7004412881)
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    Banik, Palash Chandra (57193523050)
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    Bärnighausen, Till Winfried (23011726900)
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    Barra, Fabio (57201953956)
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    Barrow, Amadou (57217061576)
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    Basu, Sanjay (9335409500)
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    Bayati, Mohsen (56906776500)
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    Belete, Rebuma (57217182390)
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    Bell, Arielle Wilder (57362817700)
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    Bhagat, Devidas S (57327243700)
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    Bhagavathula, Akshaya Srikanth (56398498300)
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    Bhardwaj, Pankaj (57226841442)
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    Bhardwaj, Nikha (57221591832)
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    Bhaskar, Sonu (57192268582)
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    Bhattacharyya, Krittika (57204647266)
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    Bhutta, Zulfiqar A (57415572700)
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    Bibi, Sadia (57524553300)
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    Bijani, Ali (23134684900)
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    Bikbov, Boris (57219957158)
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    Biondi, Antonio (57226837403)
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    Bolarinwa, Obasanjo Afolabi (57218336464)
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    Bonny, Aime (57190091246)
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    Brenner, Hermann (57216427807)
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    Buonsenso, Danilo (36607486700)
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    Burkart, Katrin (29067507300)
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    Busse, Reinhard (35589070800)
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    Butt, Zahid A (57202522739)
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    Butt, Nadeem Shafique (7003613681)
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    Dos Santos, Florentino Luciano Caetano (56373058500)
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    Cahuana-Hurtado, Lucero (57207890731)
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    Cámera, Luis Alberto (7003354253)
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    Cárdenas, Rosario (57216482927)
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    Carneiro, Vera L A (57213266524)
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    Catalá-López, Ferrán (57202553733)
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    Chandan, Joht Singh (57221106138)
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    Charan, Jaykaran (9251091600)
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    Chavan, Prachi P (57192304065)
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    Chen, Simiao (57203514169)
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    Chen, Shu (57192606069)
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    Choudhari, Sonali Gajanan (55760057300)
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    Chowdhury, Enayet Karim (35278162800)
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    Chowdhury, Mohiuddin Ahsanul Kabir (57199184042)
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    Cirillo, Massimo (35247478400)
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    Corso, Barbara (54402100400)
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    Dadras, Omid (57205721978)
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    Dahlawi, Saad M A (57189234459)
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    Dai, Xiaochen (57221591169)
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    Dandona, Lalit (7007017243)
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    Dandona, Rakhi (57203043697)
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    Dangel, William James (57219386065)
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    Dávila-Cervantes, Claudio Alberto (45561136400)
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    Davletov, Kairat (6602803024)
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    Deuba, Keshab (55619379400)
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    Dhimal, Meghnath (54941157300)
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    Dhimal, Mandira Lamichhane (57201374139)
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    Djalalinia, Shirin (37113718000)
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    Do, Huyen Phuc (57200737094)
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    Doshmangir, Leila (44261140600)
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    Duncan, Bruce B (35476478500)
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    Effiong, Andem (57213158150)
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    Ehsani-Chimeh, Elham (36107566300)
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    Elgendy, Islam Y (56022050500)
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    Elhadi, Muhammed (57212082248)
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    El Sayed, Iman (7004479194)
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    El Tantawi, Maha (57214851491)
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    Erku, Daniel Asfaw (57190738018)
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    Eskandarieh, Sharareh (57211720158)
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    Fares, Jawad (55606854400)
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    Farzadfar, Farshad (57195049611)
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    Ferrero, Simone (57190137236)
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    Desideri, Lorenzo Ferro (57201549628)
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    Fischer, Florian (55508208800)
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    Foigt, Nataliya A (57216998893)
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    Foroutan, Masoud (58948371300)
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    Fukumoto, Takeshi (26531100300)
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    Gaal, Peter Andras (55966171600)
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    Gaihre, Santosh (36503840700)
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    Gardner, William M (57204566870)
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    Garg, Tushar (57681919400)
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    Obsa, Abera Getachew (57221609252)
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    Ghafourifard, Mansour (57193420915)
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    Ghashghaee, Ahmad (57194174020)
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    Ghith, Nermin (55249750100)
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    Gilani, Syed Amir (37008269900)
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    Gill, Paramjit Singh (7202766660)
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    Goharinezhad, Salime (56731088600)
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    Golechha, Mahaveer (36006347600)
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    Guadamuz, Jenny S (57191321779)
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    Guo, Yuming (55712472800)
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    Gupta, Rajat Das (57215122060)
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    Gupta, Rajeev (55705295300)
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    Gupta, Vivek Kumar (35073936800)
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    Gupta, Veer Bala (57194978364)
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    Hamiduzzaman, Mohammad (57201153688)
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    Hanif, Asif (55360052800)
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    Haro, Josep Maria (57215877903)
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    Hasaballah, Ahmed I (56002305300)
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    Hasan, Md Mehedi (57213529757)
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    Hasan, M Tasdik (57798246500)
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    Hashi, Abdiwahab (57193562090)
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    Hay, Simon I (7101875313)
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    Hayat, Khezar (57219918947)
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    Heidari, Mohammad (56494430400)
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    Heidari, Golnaz (57218883864)
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    Henry, Nathaniel J (57196076616)
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    Herteliu, Claudiu (26035943100)
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    Holla, Ramesh (55270371800)
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    Hossain, Sahadat (57188667199)
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    Hossain, Sheikh Jamal (57212734709)
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    Hossain, Mohammad Bellal Hossain (36028425500)
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    Hosseinzadeh, Mehdi (57201880569)
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    Hostiuc, Sorin (24829099800)
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    Hoveidamanesh, Soodabeh (57201943166)
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    Hsieh, Vivian Chia-Rong (55368127500)
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    Hu, Guoqing (57218106596)
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    Huang, Junjie (57199198962)
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    Huda, M Mamun (36501626400)
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    Ifeagwu, Susan C (58406883300)
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    Ikuta, Kevin S (57211541916)
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    Ilesanmi, Olayinka Stephen (54782692800)
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    Irvani, Seyed Sina Naghibi (57202975543)
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    Islam, Rakibul M (57205202128)
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    Islam, Sheikh Mohammed Shariful (56400111100)
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    Ismail, Nahlah Elkudssiah (57885381900)
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    Iso, Hiroyasu (35227393400)
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    Isola, Gaetano (25825125500)
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    Itumalla, Ramaiah (57212472658)
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    Iwagami, Masao (54381883100)
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    Jahani, Mohammad Ali (56091589300)
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    Jahanmehr, Nader (57203122718)
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    Jain, Rajesh (57216728875)
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    Jakovljevic, Mihajlo (14318929700)
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    Janodia, Manthan Dilipkumar (12791073000)
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    Jayapal, Sathish Kumar (57202019648)
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    Jayaram, Shubha (57221589240)
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    Jha, Ravi Prakash (58586863400)
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    Jonas, Jost B (7202492953)
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    Joo, Tamas (57214777013)
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    Joseph, Nitin (35292547200)
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    Jürisson, Mikk (55547524800)
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    Kabir, Ali (23050698400)
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    Kalankesh, Leila R (12796418600)
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    Kalhor, Rohollah (55670548600)
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    Kamath, Aruna M (57204215390)
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    Kamenov, Kaloyan (56242269700)
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    Kandel, Himal (57226834655)
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    Kantar, Rami S (56719718400)
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    Kapoor, Neeti (56340726700)
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    Karanikolos, Marina (45961091300)
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    Katikireddi, Srinivasa Vittal (6508254091)
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    Kavetskyy, Taras (57220358576)
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    Kawakami, Norito (35377339000)
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    Kayode, Gbenga A (53463867400)
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    Keikavoosi-Arani, Leila (58630116900)
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    Keykhaei, Mohammad (57208162861)
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    Khader, Yousef Saleh (55654192600)
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    Khajuria, Himanshu (56639982500)
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    Khalilov, Rovshan (57193308858)
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    Khammarnia, Mohammad (55804349000)
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    Khan, Md Nuruzzaman (57209404949)
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    Khan, Moien A B (57209800900)
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    Khan, Maseer (57215721758)
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    Khezeli, Mehdi (57192816879)
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    Kim, Min Seo (57203591936)
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    Kim, Yun Jin (57211086375)
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    Kisa, Sezer (14030019900)
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    Kisa, Adnan (6603346067)
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    Klymchuk, Vitalii (57221758551)
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    Koly, Kamrun Nahar (57217036585)
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    Korzh, Oleksii (7004882843)
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    Kosen, Soewarta (57211346192)
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    Koul, Parvaiz A (14022262900)
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    Defo, Barthelemy Kuate (6602271655)
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    Kumar, G Anil (57139550500)
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    Kusuma, Dian (57190047530)
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    Kyu, Hmwe Hmwe (57217040073)
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    Larsson, Anders O (56381985300)
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    Lasrado, Savita (36632480900)
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    Lee, Wei-Chen (57394248700)
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    Lee, Yo Han (57193632340)
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    Lee, Chiachi Bonnie (56101115800)
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    Li, Shanshan (57216631901)
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    Lucchetti, Giancarlo (35790096500)
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    Mahajan, Preetam Bhalchandra (57168727200)
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    Majeed, Azeem (57217722657)
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    Makki, Alaa (57224607101)
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    Malekzadeh, Reza (7005197760)
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    Malik, Ahmad Azam (57198682313)
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    Malta, Deborah Carvalho (15835283500)
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    Mansournia, Mohammad Ali (34570618600)
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    Mantovani, Lorenzo Giovanni (7006357517)
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    Martinez-Valle, Adolfo (7006099775)
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    Martins-Melo, Francisco Rogerlândio (57204796807)
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    Masoumi, Seyedeh Zahra (55769011500)
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    Mathur, Manu Raj (55270329300)
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    Maude, Richard James (25625222500)
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    Maulik, Pallab K (7005919685)
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    McKee, Martin (7202304775)
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    Mendoza, Walter (57216905642)
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    Menezes, Ritesh G (55517099900)
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    Mensah, George A (57196028147)
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    Meretoja, Atte (12775885500)
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    Meretoja, Tuomo J (57219008708)
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    Mestrovic, Tomislav (6507240107)
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    Michalek, Irmina Maria (56982945900)
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    Mirrakhimov, Erkin M (57508336100)
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    Misganaw, Awoke (57202808713)
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    Misra, Sanjeev (35501005200)
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    Moazen, Babak (57204324006)
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    Mohammadi, Mokhtar (57188972365)
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    Mohammed, Shafiu (57838689000)
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    Moitra, Modhurima (57191962343)
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    Mokdad, Ali H (7004813962)
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    Molokhia, Mariam (7004121920)
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    Monasta, Lorenzo (7801520497)
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    Moni, Mohammad Ali (35119094400)
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    Moradi, Ghobad (48161434000)
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    Moreira, Rafael Silveira (57819635000)
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    Mosser, Jonathan F (56111776300)
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    Mostafavi, Ebrahim (57440829200)
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    Mouodi, Simin (55372646500)
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    Nagarajan, Ahamarshan Jayaraman (57204562074)
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    Nagata, Chie (50061824800)
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    Naghavi, Mohsen (57207906323)
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    Nangia, Vinay (57201490837)
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    Swamy, Sreenivas Narasimha (57222706843)
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    Narayana, Aparna Ichalangod (26530691100)
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    Nascimento, Bruno Ramos (14424406800)
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    Nassereldine, Hasan (57226192220)
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    Nayak, Biswa Prakash (56639942500)
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    Nazari, Javad (57207759174)
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    Negoi, Ionut (57200640014)
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    Nepal, Samata (56549676600)
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    Kandel, Sandhya Neupane (57222966618)
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    Ngunjiri, Josephine W (57195296110)
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    Nguyen, Huong Lan Thi (57226837406)
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    Nguyen, Cuong Tat (56531347200)
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    Ningrum, Dina Nur Anggraini (57195329470)
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    Noubiap, Jean Jacques (55490374000)
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    Oancea, Bogdan (26658614800)
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    Oghenetega, Onome Bright (57216588908)
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    Oh, In-Hwan (57204090669)
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    Olagunju, Andrew T (26029995700)
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    Olakunde, Babayemi Oluwaseun (55251697700)
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    Bali, Ahmed Omar (57201273344)
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    Omer, Emad (57227106800)
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    Onwujekwe, Obinna E (7003992855)
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    Otoiu, Adrian (56375694100)
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    Padubidri, Jagadish Rao (58295062300)
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    Palladino, Raffaele (57215205417)
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    Pana, Adrian (57191837583)
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    Panda-Jonas, Songhomitra (6603112353)
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    Pandi-Perumal, Seithikurippu R (7801638271)
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    Pardhan, Shahina (7003706887)
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    Pasupula, Deepak Kumar (57196471042)
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    Pathak, Praveen Kumar (27267907300)
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    Patton, George C (7102184358)
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    Pawar, Shrikant (58594958600)
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    Pereira, Jeevan (57218878130)
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    Pilania, Manju (55372464500)
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    Podder, Vivek (57201487580)
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    Pokhrel, Khem Narayan (57189445377)
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    Postma, Maarten J (7006296502)
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    Prada, Sergio I (55259772200)
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    Syed, Zahiruddin Quazi (36337182700)
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    Rabiee, Navid (57201008317)
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    Radhakrishnan, Raghu Anekal (7103113006)
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    Rahman, Md. Mosfequr (57706424400)
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    Rahman, Mosiur (55457953000)
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    Rahman, Mahfuzar (35571661300)
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    Ur Rahman, Mohammad Hifz (57208867497)
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    Rahmani, Amir Masoud (57204588830)
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    Ranabhat, Chhabi Lal (56719695500)
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    Rao, Chythra R (35771430100)
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    Rao, Sowmya J (57195423591)
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    Rasella, Davide (36184697300)
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    Rawaf, Salman (6602475959)
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    Rawaf, David Laith (57209228052)
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    Rawal, Lal (37262106500)
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    Renzaho, Andre M N (6505786588)
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    Reshmi, Bhageerathy (58925604800)
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    Resnikoff, Serge (7006012071)
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    Rezapour, Aziz (55548281300)
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    Riahi, Seyed Mohammad (57193205976)
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    Ripon, Rezaul Karim (57219948722)
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    Sacco, Simona (55751819500)
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    Sadeghi, Masoumeh (35516248000)
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    Saeed, Umar (36612315100)
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    Sahebkar, Amirhossein (26639699900)
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    Sahiledengle, Biniyam (57204583027)
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    Sahoo, Harihar (44462008100)
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    Sahu, Maitreyi (57216341277)
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    Salama, Joseph S (57202975625)
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    Salamati, Payman (14045860600)
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    Samy, Abdallah M (36973661300)
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    Sanabria, Juan (57226829732)
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    Santric-Milicevic, Milena M (57211144346)
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    Sathian, Brijesh (27467953500)
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    Sawhney, Monika (57217153893)
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    Schmidt, Maria Inês (7404398885)
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    Seidu, Abdul-Aziz (57200383297)
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    Sepanlou, Sadaf G (36248136000)
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    Seylani, Allen (57222325334)
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    Shaikh, Masood Ali (57203122601)
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    Sheikh, Aziz (7202522962)
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    Shetty, Adithi (57315189400)
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    Shigematsu, Mika (23968093000)
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    Shiri, Rahman (57200737050)
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    Shivakumar, K.M. (57221603938)
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    Shokri, Azad (57192161989)
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    Singh, Jasvinder A (7404421736)
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    Sinha, Dhirendra Narain (7201637609)
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    Skryabin, Valentin Yurievich (57226830981)
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    Skryabina, Anna Aleksandrovna (57218875198)
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    Sofi-Mahmudi, Ahmad (57216854132)
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    Sousa, Raúl A R C (57218215064)
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    Stephens, Jacqueline H (57222523979)
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    Sun, Jing (55547135859)
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    Szócska, Miklós (13410278600)
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    Tabarés-Seisdedos, Rafael (6602981102)
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    Tadbiri, Hooman (57138410000)
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    Tamiru, Animut Tagele (57218877788)
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    Thankappan, Kavumpurathu Raman (57202955435)
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    Topor-Madry, Roman (57211182892)
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    Tovani-Palone, Marcos Roberto (56644977900)
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    Tran, Mai Thi Ngoc (57225047867)
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    Tran, Bach Xuan (57209107515)
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    Tripathi, Niharika (55816015000)
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    Tripathy, Jaya Prasad (55290251600)
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    Troeger, Christopher E (57195223624)
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    Uezono, Deinzel Robles (57211025059)
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    Ullah, Saif (57219395828)
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    Unnikrishnan, Bhaskaran (12790012100)
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    Vacante, Marco (23037085900)
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    Tahbaz, Sahel Valadan (57216154072)
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    Valdez, Pascual R (57202115577)
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    Violante, Francesco S (7003555890)
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    Vladimirov, Sergey Konstantinovitch (57195959162)
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    Waheed, Yasir (35303643700)
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    Wamai, Richard G (23969762700)
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    Wang, Yuan-Pang (8576812100)
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    Wang, Yanzhong (59417336500)
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    Ward, Paul (7402101951)
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    Wiangkham, Taweewat (56829456300)
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    Yadav, Lalit (57211483937)
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    Jabbari, Seyed Hossein Yahyazadeh (57207954055)
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    Yamagishi, Kazumasa (35231751500)
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    Yaya, Sanni (55191139800)
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    Yazdi-Feyzabadi, Vahid (56017415700)
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    Yi, Siyan (16837551600)
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    Yiǧit, Vahit (57222328239)
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    Yonemoto, Naohiro (57204947657)
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    Younis, Mustafa Z (8549393000)
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    Yu, Chuanhua (57208140344)
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    Yunusa, Ismaeel (57202137670)
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    Zaman, Sojib Bin (57193070058)
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    Zastrozhin, Mikhail Sergeevich (56728932200)
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    Zhang, Zhi-Jiang (56068578400)
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    Zhong, Chenwen (59289905900)
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    Zuniga, Yves Miel H (57194979049)
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    Lim, Stephen S (57201800433)
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    Murray, Christopher J L (57224556036)
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    Lozano, Rafael (57570224000)
    Background: Health-care needs change throughout the life course. It is thus crucial to assess whether health systems provide access to quality health care for all ages. Drawing from the Global Burden of Diseases, Injuries, and Risk Factors Study 2019 (GBD 2019), we measured the Healthcare Access and Quality (HAQ) Index overall and for select age groups in 204 locations from 1990 to 2019. Methods: We distinguished the overall HAQ Index (ages 0–74 years) from scores for select age groups: the young (ages 0–14 years), working (ages 15–64 years), and post-working (ages 65–74 years) groups. For GBD 2019, HAQ Index construction methods were updated to use the arithmetic mean of scaled mortality-to-incidence ratios (MIRs) and risk-standardised death rates (RSDRs) for 32 causes of death that should not occur in the presence of timely, quality health care. Across locations and years, MIRs and RSDRs were scaled from 0 (worst) to 100 (best) separately, putting the HAQ Index on a different relative scale for each age group. We estimated absolute convergence for each group on the basis of whether the HAQ Index grew faster in absolute terms between 1990 and 2019 in countries with lower 1990 HAQ Index scores than countries with higher 1990 HAQ Index scores and by Socio-demographic Index (SDI) quintile. SDI is a summary metric of overall development. Findings: Between 1990 and 2019, the HAQ Index increased overall (by 19·6 points, 95% uncertainty interval 17·9–21·3), as well as among the young (22·5, 19·9–24·7), working (17·2, 15·2–19·1), and post-working (15·1, 13·2–17·0) age groups. Large differences in HAQ Index scores were present across SDI levels in 2019, with the overall index ranging from 30·7 (28·6–33·0) on average in low-SDI countries to 83·4 (82·4–84·3) on average in high-SDI countries. Similarly large ranges between low-SDI and high-SDI countries, respectively, were estimated in the HAQ Index for the young (40·4–89·0), working (33·8–82·8), and post-working (30·4–79·1) groups. Absolute convergence in HAQ Index was estimated in the young group only. In contrast, divergence was estimated among the working and post-working groups, driven by slow progress in low-SDI countries. Interpretation: Although major gaps remain across levels of social and economic development, convergence in the young group is an encouraging sign of reduced disparities in health-care access and quality. However, divergence in the working and post-working groups indicates that health-care access and quality is lagging at lower levels of social and economic development. To meet the needs of ageing populations, health systems need to improve health-care access and quality for working-age adults and older populations while continuing to realise gains among the young. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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    Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
    (2020)
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    Mihretie, Kebadnew Mulatu (57214781514)
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    Miller, Ted R. (7403948600)
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    Milne, George J. (9434770500)
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    Mini, G.K. (12800865800)
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    Mirica, Andreea (57188983765)
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    Mirrakhimov, Erkin M. (57508336100)
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    Mirzaei, Hamed (37034594600)
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    Mirzaei, Maryam (56902299800)
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    Mirzaei, Roya (55745833800)
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    Mirzaei-Alavijeh, Mehdi (57201700997)
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    Misganaw, Awoke Temesgen (57202808713)
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    Mitchell, Philip B. (35354747000)
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    Mithra, Prasanna (36018632500)
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    Moazen, Babak (57204324006)
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    Moghadaszadeh, Masoud (57200791890)
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    Mohajer, Bahram (57039225300)
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    Mohamad, Osama (36342663600)
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    Mohamadi, Efat (57202198397)
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    Mohammad, Dara K. (43161421200)
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    Mohammad, Yousef (6603403710)
    Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and development investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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    Measuring the availability of human resources for health and its relationship to universal health coverage for 204 countries and territories from 1990 to 2019: a systematic analysis for the Global Burden of Disease Study 2019
    (2022)
    Haakenstad, Annie (56079498000)
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    Irvine, Caleb Mackay Salpeter (57203666733)
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    Knight, Megan (57218877591)
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    Bintz, Corinne (57215013911)
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    Aravkin, Aleksandr Y. (35386103000)
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    Zheng, Peng (57213707656)
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    Gupta, Vin (57209148425)
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    Abrigo, Michael R.M. (56018773400)
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    Abushouk, Abdelrahman I. (57191479876)
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    Adebayo, Oladimeji M. (57194329853)
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    Al-Aly, Ziyad (9738161500)
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    Alanzi, Turki M. (55978240000)
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    Alcalde-Rabanal, Jacqueline Elizabeth (35749450200)
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    Zhang, Zhi-Jiang (56068578400)
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    Zodpey, Sanjay (7003415080)
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    Lim, Stephen S. (57201800433)
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    Murray, Christopher J.L. (57224556036)
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    Lozano, Rafael (7102198442)
    Background: Human resources for health (HRH) include a range of occupations that aim to promote or improve human health. The UN Sustainable Development Goals (SDGs) and the WHO Health Workforce 2030 strategy have drawn attention to the importance of HRH for achieving policy priorities such as universal health coverage (UHC). Although previous research has found substantial global disparities in HRH, the absence of comparable cross-national estimates of existing workforces has hindered efforts to quantify workforce requirements to meet health system goals. We aimed to use comparable and standardised data sources to estimate HRH densities globally, and to examine the relationship between a subset of HRH cadres and UHC effective coverage performance. Methods: Through the International Labour Organization and Global Health Data Exchange databases, we identified 1404 country-years of data from labour force surveys and 69 country-years of census data, with detailed microdata on health-related employment. From the WHO National Health Workforce Accounts, we identified 2950 country-years of data. We mapped data from all occupational coding systems to the International Standard Classification of Occupations 1988 (ISCO-88), allowing for standardised estimation of densities for 16 categories of health workers across the full time series. Using data from 1990 to 2019 for 196 of 204 countries and territories, covering seven Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) super-regions and 21 regions, we applied spatiotemporal Gaussian process regression (ST-GPR) to model HRH densities from 1990 to 2019 for all countries and territories. We used stochastic frontier meta-regression to model the relationship between the UHC effective coverage index and densities for the four categories of health workers enumerated in SDG indicator 3.c.1 pertaining to HRH: physicians, nurses and midwives, dentistry personnel, and pharmaceutical personnel. We identified minimum workforce density thresholds required to meet a specified target of 80 out of 100 on the UHC effective coverage index, and quantified national shortages with respect to those minimum thresholds. Findings: We estimated that, in 2019, the world had 104·0 million (95% uncertainty interval 83·5–128·0) health workers, including 12·8 million (9·7–16·6) physicians, 29·8 million (23·3–37·7) nurses and midwives, 4·6 million (3·6–6·0) dentistry personnel, and 5·2 million (4·0–6·7) pharmaceutical personnel. We calculated a global physician density of 16·7 (12·6–21·6) per 10 000 population, and a nurse and midwife density of 38·6 (30·1–48·8) per 10 000 population. We found the GBD super-regions of sub-Saharan Africa, south Asia, and north Africa and the Middle East had the lowest HRH densities. To reach 80 out of 100 on the UHC effective coverage index, we estimated that, per 10 000 population, at least 20·7 physicians, 70·6 nurses and midwives, 8·2 dentistry personnel, and 9·4 pharmaceutical personnel would be needed. In total, the 2019 national health workforces fell short of these minimum thresholds by 6·4 million physicians, 30·6 million nurses and midwives, 3·3 million dentistry personnel, and 2·9 million pharmaceutical personnel. Interpretation: Considerable expansion of the world's health workforce is needed to achieve high levels of UHC effective coverage. The largest shortages are in low-income settings, highlighting the need for increased financing and coordination to train, employ, and retain human resources in the health sector. Actual HRH shortages might be larger than estimated because minimum thresholds for each cadre of health workers are benchmarked on health systems that most efficiently translate human resources into UHC attainment. Funding: Bill & Melinda Gates Foundation. © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
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    Measuring universal health coverage based on an index of effective coverage of health services in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019
    (2020)
    Lozano, Rafael (7102198442)
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    Fullman, Nancy (57211064970)
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    Background: Achieving universal health coverage (UHC) involves all people receiving the health services they need, of high quality, without experiencing financial hardship. Making progress towards UHC is a policy priority for both countries and global institutions, as highlighted by the agenda of the UN Sustainable Development Goals (SDGs) and WHO's Thirteenth General Programme of Work (GPW13). Measuring effective coverage at the health-system level is important for understanding whether health services are aligned with countries' health profiles and are of sufficient quality to produce health gains for populations of all ages. Methods: Based on the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we assessed UHC effective coverage for 204 countries and territories from 1990 to 2019. Drawing from a measurement framework developed through WHO's GPW13 consultation, we mapped 23 effective coverage indicators to a matrix representing health service types (eg, promotion, prevention, and treatment) and five population-age groups spanning from reproductive and newborn to older adults (≥65 years). Effective coverage indicators were based on intervention coverage or outcome-based measures such as mortality-to-incidence ratios to approximate access to quality care; outcome-based measures were transformed to values on a scale of 0–100 based on the 2·5th and 97·5th percentile of location-year values. We constructed the UHC effective coverage index by weighting each effective coverage indicator relative to its associated potential health gains, as measured by disability-adjusted life-years for each location-year and population-age group. For three tests of validity (content, known-groups, and convergent), UHC effective coverage index performance was generally better than that of other UHC service coverage indices from WHO (ie, the current metric for SDG indicator 3.8.1 on UHC service coverage), the World Bank, and GBD 2017. We quantified frontiers of UHC effective coverage performance on the basis of pooled health spending per capita, representing UHC effective coverage index levels achieved in 2019 relative to country-level government health spending, prepaid private expenditures, and development assistance for health. To assess current trajectories towards the GPW13 UHC billion target—1 billion more people benefiting from UHC by 2023—we estimated additional population equivalents with UHC effective coverage from 2018 to 2023. Findings: Globally, performance on the UHC effective coverage index improved from 45·8 (95% uncertainty interval 44·2–47·5) in 1990 to 60·3 (58·7–61·9) in 2019, yet country-level UHC effective coverage in 2019 still spanned from 95 or higher in Japan and Iceland to lower than 25 in Somalia and the Central African Republic. Since 2010, sub-Saharan Africa showed accelerated gains on the UHC effective coverage index (at an average increase of 2·6% [1·9–3·3] per year up to 2019); by contrast, most other GBD super-regions had slowed rates of progress in 2010–2019 relative to 1990–2010. Many countries showed lagging performance on effective coverage indicators for non-communicable diseases relative to those for communicable diseases and maternal and child health, despite non-communicable diseases accounting for a greater proportion of potential health gains in 2019, suggesting that many health systems are not keeping pace with the rising non-communicable disease burden and associated population health needs. In 2019, the UHC effective coverage index was associated with pooled health spending per capita (r=0·79), although countries across the development spectrum had much lower UHC effective coverage than is potentially achievable relative to their health spending. Under maximum efficiency of translating health spending into UHC effective coverage performance, countries would need to reach $1398 pooled health spending per capita (US$ adjusted for purchasing power parity) in order to achieve 80 on the UHC effective coverage index. From 2018 to 2023, an estimated 388·9 million (358·6–421·3) more population equivalents would have UHC effective coverage, falling well short of the GPW13 target of 1 billion more people benefiting from UHC during this time. Current projections point to an estimated 3·1 billion (3·0–3·2) population equivalents still lacking UHC effective coverage in 2023, with nearly a third (968·1 million [903·5–1040·3]) residing in south Asia. Interpretation: The present study demonstrates the utility of measuring effective coverage and its role in supporting improved health outcomes for all people—the ultimate goal of UHC and its achievement. Global ambitions to accelerate progress on UHC service coverage are increasingly unlikely unless concerted action on non-communicable diseases occurs and countries can better translate health spending into improved performance. Focusing on effective coverage and accounting for the world's evolving health needs lays the groundwork for better understanding how close—or how far—all populations are in benefiting from UHC. Funding: Bill & Melinda Gates Foundation. © 2020 Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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