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Global, Regional, and National Incidence, Prevalence, and Mortality of Hiv, 1980-2017, and Forecasts to 2030, for 195 Countries and Territories: A Systematic Analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017 Publisher Pubmed



Frank TD1 ; Carter A1 ; Jahagirdar D1 ; Biehl MH1 ; Douwesschultz D1 ; Larson SL1 ; Arora M1 ; Dwyerlindgren L1, 2 ; Steuben KM1 ; Abbastabar H19 ; Aburaddad LJ24 ; Abyu DM25 ; Adabi M29 ; Adebayo OM32 Show All Authors
Authors
  1. Frank TD1
  2. Carter A1
  3. Jahagirdar D1
  4. Biehl MH1
  5. Douwesschultz D1
  6. Larson SL1
  7. Arora M1
  8. Dwyerlindgren L1, 2
  9. Steuben KM1
  10. Abbastabar H19
  11. Aburaddad LJ24
  12. Abyu DM25
  13. Adabi M29
  14. Adebayo OM32
  15. Adekanmbi V33
  16. Adetokunboh OO34, 37
  17. Ahmadi A40
  18. Ahmadi K43
  19. Ahmadian E45, 47
  20. Ahmadpour E44
  21. Ahmed MB48
  22. Akal CG52
  23. Alahdab F56
  24. Alam N57
  25. Albertson SB1
  26. Alemnew BTT58, 64
  27. Alene KA75, 77
  28. Alipour V80
  29. Alvisguzman N84, 85
  30. Amini S88
  31. Anbari Z86
  32. Anber NH90
  33. Anjomshoa M92
  34. Antonio CAT93, 95
  35. Arabloo J80
  36. Aremu O96
  37. Areri HA69
  38. Asfaw ET104
  39. Ashagre AF72
  40. Asmelash D72
  41. Asrat AA51
  42. Avokpaho EFGA109, 110
  43. Awasthi A111, 113
  44. Awoke N116
  45. Ayanore MA119
  46. Azari S80
  47. Badawi A120, 121
  48. Bagherzadeh M123
  49. Banach M124, 125
  50. Barac A126, 127
  51. Barnighausen TW129, 132
  52. Basu S134
  53. Bedi N135, 136
  54. Behzadifar M137
  55. Bekele BB75, 140
  56. Belay SA30
  57. Belay YB105, 141
  58. Belayneh YMM142
  59. Berhane A70
  60. Bhat AG143
  61. Bhattacharyya K144, 145
  62. Biadgo B72
  63. Bijani A147
  64. Shahdaat Bin Sayeed M76, 148
  65. Bitew H107
  66. Blinov A150, 151
  67. Bogale KA54
  68. Bojia HA153
  69. Burugina Nagaraja SBN156
  70. Butt ZA157, 158
  71. Cahuanahurtado L159
  72. Campuzano Rincon JC160, 161
  73. Carvalho F162, 165
  74. Chattu VK122, 167
  75. Christopher DJ168
  76. Chu DT169
  77. Crider R170
  78. Dahiru T171
  79. Dandona L1, 113
  80. Dandona R1, 113
  81. Daryani A178
  82. Das Neves J163, 164
  83. De Neve JW129
  84. Degenhardt L1, 180
  85. Demeke FM55
  86. Demis ABB49, 60
  87. Demissie DB182, 185
  88. Demoz GT71, 188
  89. Deribe K70, 189
  90. Des Jarlais D190
  91. Dhungana GP191
  92. Diaz D192, 193
  93. Djalalinia S194
  94. Do HP195
  95. Doan LP196
  96. Duber H1, 2
  97. Dubey M197
  98. Dubljanin E127
  99. Duken EE50, 198
  100. Duko Adema B202
  101. Effiong A203
  102. Eftekhari A45, 204
  103. El Sayed Zaki M89
  104. Eljaafary SI206
  105. Elkhatib Z209
  106. Elsharkawy A207
  107. Endries AY210
  108. Eskandarieh S21
  109. Eyawo O211, 212
  110. Farzadfar F22
  111. Fatima B213
  112. Fentahun N53
  113. Fernandes E166
  114. Filip I214, 217
  115. Fischer F219
  116. Folayan MO220
  117. Foroutan M221
  118. Fukumoto T222, 223
  119. Fullman N1
  120. Garciabasteiro AL224, 225
  121. Gayesa RT199
  122. Gebremedhin KB65
  123. Gebremeskel GG102, 187
  124. Gebreyohannes KK226
  125. Gedefaw GA55, 155
  126. Gelaw BK184
  127. Gesesew HA48, 227
  128. Geta B142
  129. Gezae KE99
  130. Ghadiri K42
  131. Ghashghaee A79
  132. Ginindza TTG229
  133. Gugnani HC232, 233
  134. Guimaraes RA234
  135. Haile MT181
  136. Hailu GB97
  137. Hajmirzaian A13, 237
  138. Hajmirzaian A13, 237
  139. Hamidi S241
  140. Handanagic S242, 243
  141. Handiso DW244
  142. Hanfore LK117
  143. Hasanzadeh A12, 205
  144. Hassankhani H46
  145. Hassen HY140, 246
  146. Hay SI1, 2
  147. Henok A138
  148. Hoang CL195
  149. Hosgood HD247
  150. Hosseinzadeh M80, 248
  151. Hsairi M250
  152. Ibitoye SE252
  153. Idrisov B253
  154. Ikuta KS1, 5
  155. Ilesanmi OS251
  156. Irvani SSN22, 238
  157. Iwu CJ35, 36
  158. Jacobsen KH254
  159. James SL1
  160. Jenabi E218
  161. Jha RP255
  162. Jonas JB128, 256
  163. Jorjoran Shushtari Z257
  164. Kabir A82
  165. Kabir Z259
  166. Kadel R260
  167. Kasaeian A16, 17
  168. Kassa B67
  169. Kassa GM261
  170. Kassa TD98
  171. Kayode GA264, 265
  172. Kebede MM74, 266
  173. Kefale AT139
  174. Kengne AP267, 268
  175. Khader YS271
  176. Khafaie MA273
  177. Khalid N275
  178. Khan EA276
  179. Khan G277
  180. Khan J278
  181. Khang YH279, 280
  182. Khatab K281, 282
  183. Khazaei S285
  184. Khoja AT239, 288
  185. Kiadaliri AA289
  186. Kim YJ290
  187. Kisa A291, 292
  188. Kisa S293
  189. Kochhar S3, 294
  190. Komaki H287, 295
  191. Koul PA296
  192. Koyanagi A297, 298
  193. Kuate Defo B299, 300
  194. Kumar GA113
  195. Kumar M301, 303
  196. Kuupiel D229, 304
  197. Lal DK113
  198. Lee JJH6
  199. Lenjebo TL118
  200. Leshargie CT263
  201. Macarayan ERK94, 131
  202. Maddison ER1
  203. Magdy Abd El Razek H305
  204. Magisrodriguez C306
  205. Mahasha PW37
  206. Majdan M308
  207. Majeed A133
  208. Malekzadeh R14, 309
  209. Manafi N310, 311
  210. Mapoma CC312
  211. Martinsmelo FR313
  212. Masaka A314
  213. Mayenga ENL316
  214. Mehta V317
  215. Meles GG26
  216. Meles HG108
  217. Melese A52
  218. Melku M75
  219. Memiah PTN318
  220. Memish ZA320, 321
  221. Mena AT28
  222. Mendoza W322
  223. Mengistu DT106
  224. Mengistu G142, 154
  225. Meretoja TJ323, 324
  226. Mestrovic T325, 326
  227. Miller TR327, 328
  228. Moazen B130, 329
  229. Mohajer B21, 22
  230. Mohamadibolbanabad A331
  231. Mohammad KA333, 334
  232. Mohammad Y335
  233. Mohammad Darwesh A249
  234. Mohammad Gholi Mezerji N284
  235. Mohammadi M174
  236. Mohammadibakhsh R286
  237. Mohammadookhorasani M336
  238. Mohammed JA337
  239. Mohammed S130, 172
  240. Mohebi F18, 22
  241. Mokdad AH1, 2
  242. Moodley Y229
  243. Moossavi M338
  244. Moradi G330, 331
  245. Moradilakeh M83
  246. Moschos MM339, 340
  247. Mossie TB108
  248. Mousavi SM11
  249. Muchie KF75
  250. Muluneh AG73
  251. Muriithi MK302
  252. Mustafa G341, 342
  253. Muthupandian S100
  254. Nagarajan AJ343, 344
  255. Naik G345
  256. Najafi F41
  257. Nazari J87, 347
  258. Ndwandwe DE37
  259. Nguyen CT348
  260. Nguyen HLT348
  261. Nguyen SH195
  262. Nguyen TH195
  263. Ningrum DNA349, 350
  264. Nixon MR1
  265. Nnaji CA37, 270
  266. Noroozi M258
  267. Noubiap JJ268
  268. Nourollahpour Shiadeh M179
  269. Obsa MS216
  270. Odame EA319
  271. Oforiasenso R351, 352
  272. Ogbo FA353
  273. Okoro A354
  274. Oladimeji O355, 356
  275. Olagunju AT358, 359
  276. Olagunju TO357
  277. Olum S360, 361
  278. Oppong Asante K230, 362
  279. Oren E7, 363
  280. Otstavnov SS149, 364
  281. Mahesh PA365
  282. Padubidri JR366
  283. Pakhale S367
  284. Pakpour AH368, 369
  285. Patel SK370, 371
  286. Paulos K115
  287. Pepito VCF372
  288. Peprah EK373
  289. Piroozi B332
  290. Pourshams A14
  291. Qorbani M374
  292. Rabiee M375
  293. Rabiee N123
  294. Radfar A215, 376
  295. Rafay A377
  296. Rafiei A173, 176
  297. Rahim F15, 274
  298. Rahimimovaghar A20
  299. Rahimimovaghar V23
  300. Rahman SU378, 379
  301. Ranabhat CL381, 384
  302. Rawaf S133, 385
  303. Reis C386
  304. Renjith V387
  305. Reta MA59, 388
  306. Rezai MS177
  307. Rios Gonzalez CM307, 389
  308. Merdassa Roro EEM68, 200
  309. Rostami A146
  310. Rubino S390
  311. Saeedi Moghaddam S22
  312. Safari S236
  313. Sagar R391
  314. Sahraian MA21
  315. Salem MRR208
  316. Salimi Y41
  317. Salomon JA392
  318. Sambala EZ37
  319. Samy AM393
  320. Sartorius B2, 394
  321. Satpathy M395, 396
  322. Sawhney M397
  323. Sayyah M272
  324. Schutte AE38, 380
  325. Sepanlou SG14, 309
  326. Seyedmousavi S10, 175
  327. Shabaninejad H78
  328. Shaheen AA398
  329. Shaikh MA399
  330. Shallo SA183
  331. Shamsizadeh M283
  332. Sharifi H400
  333. Shibuya K401
  334. Shin JI382, 402
  335. Shirkoohi R8, 9
  336. Silva DAS403
  337. Silveira DGA404, 405
  338. Singh JA345, 346
  339. Sisay MMM73, 406
  340. Sisay M154
  341. Sisay S407
  342. Smith AE1
  343. Sokhan A408
  344. Somayaji R4, 409
  345. Soshnikov S410
  346. Stein DJ39, 269
  347. Sufiyan MB171
  348. Sunguya BF412
  349. Sykes BL414
  350. Tadesse BT201
  351. Tadesse DB27
  352. Tamirat KS73
  353. Taveira N415, 416
  354. Tekelemedhin SW108
  355. Temesgen HD262
  356. Tesfay FH108, 228
  357. Teshale MY25
  358. Thapa S417
  359. Tlaye KG61
  360. Topp SM418, 419
  361. Tovanipalone MR420
  362. Tran BX315
  363. Tran KB421, 422
  364. Ullah I423, 424
  365. Unnikrishnan B425, 426
  366. Uthman OA427
  367. Veisani Y428
  368. Vladimirov SK411, 429
  369. Wada FW62, 114
  370. Waheed Y430
  371. Weldegwergs KG98
  372. Weldesamuel GTT186
  373. Westerman R431
  374. Wijeratne T432, 433
  375. Wolde HF73
  376. Wondafrash DZ66, 103
  377. Wonde TE263
  378. Wondmagegn BY152
  379. Yeshanew AG63
  380. Yilma MT200
  381. Yimer EM107
  382. Yonemoto N434
  383. Yotebieng M435, 436
  384. Youm Y383
  385. Yu C437, 438
  386. Zaidi Z439
  387. Zarghi A235
  388. Zenebe ZM101
  389. Zewale TA51
  390. Ziapour A81
  391. Zodpey S112
  392. Naghavi M1, 2
  393. Vollset SE1, 2
  394. Wang H1, 2
  395. Lim SS1, 2
  396. Kyu HH1, 2
  397. Murray CJL1, 2

Source: The Lancet HIV Published:2019


Abstract

Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980-2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package - a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce agesex- specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87-2·04) and has since decreased to 0·95 million deaths (0·91-1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79-3·67) and since then have gradually decreased to 1·94 million (1·63-2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8-39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact. © 2019 The Author(s).
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