Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share By
Mapping Age- and Sex-Specific Hiv Prevalence in Adults in Sub-Saharan Africa, 2000–2018 Publisher Pubmed



Haeuser E1 ; Serfes AL1 ; Cork MA1 ; Yang M1 ; Abbastabar H2 ; Abhilash ES3 ; Adabi M4 ; Adebayo OM5 ; Adekanmbi V6 ; Adeyinka DA7, 8 ; Afzal S9, 10 ; Ahinkorah BO11 ; Ahmadi K12 ; Ahmed MB13, 14 Show All Authors
Authors
  1. Haeuser E1
  2. Serfes AL1
  3. Cork MA1
  4. Yang M1
  5. Abbastabar H2
  6. Abhilash ES3
  7. Adabi M4
  8. Adebayo OM5
  9. Adekanmbi V6
  10. Adeyinka DA7, 8
  11. Afzal S9, 10
  12. Ahinkorah BO11
  13. Ahmadi K12
  14. Ahmed MB13, 14
  15. Akalu Y15
  16. Akinyemi RO16, 17
  17. Akunna CJ18, 19
  18. Alahdab F20
  19. Alanezi FM21
  20. Alanzi TM22
  21. Alene KA23, 24
  22. Alhassan RK25
  23. Alipour V26, 27
  24. Almasihashiani A28
  25. Alvisguzman N29, 30
  26. Ameyaw EK11
  27. Amini S31
  28. Amugsi DA32
  29. Ancuceanu R33
  30. Anvari D34, 35
  31. Appiah SCY36, 37
  32. Arabloo J26
  33. Aremu O38
  34. Asemahagn MA39
  35. Jafarabadi MA40, 41
  36. Awedew AF42
  37. Quintanilla BPA43, 44
  38. Ayanore MA45, 46
  39. Aynalem YA47
  40. Azari S48
  41. Azene ZN49
  42. Darshan BB50
  43. Babalola TK51, 52
  44. Baig AA53
  45. Banach M54, 55
  46. Barnighausen TW56, 57
  47. Bell AW58, 59
  48. Bhagavathula AS60, 61
  49. Bhardwaj N62
  50. Bhardwaj P63, 64
  51. Bhattacharyya K65, 66
  52. Bijani A67
  53. Bitew ZW68
  54. Bohlouli S70
  55. Bolarinwa OA51
  56. Boloor A71
  57. Bozicevic I72, 73
  58. Butt ZA74, 75
  59. Cardenas R76
  60. Carvalho F77
  61. Charan J78
  62. Chattu VK79, 80
  63. Chowdhury MAK81, 82
  64. Chu DT83
  65. Cowden RG84
  66. Dahlawi SMA85
  67. Damiani G86, 87
  68. Darteh EKM88
  69. Darwesh AM89
  70. Das Neves J90, 91
  71. Weaver ND1
  72. De Leo D92
  73. De Neve JW56
  74. Deribe K93, 94
  75. Deuba K95, 96
  76. Dharmaratne S1, 97, 98
  77. Dianatinasab M99, 100
  78. Diaz D101, 102
  79. Didarloo A103
  80. Djalalinia S104
  81. Dorostkar F105
  82. Dubljanin E106
  83. Duko B107, 108
  84. El Tantawi M109
  85. Eljaafary SI110
  86. Eshrati B111
  87. Eskandarieh S112
  88. Eyawo O113
  89. Ezeonwumelu IJ114, 115
  90. Ezzikouri S116
  91. Farzadfar F117
  92. Fattahi N118
  93. Fauk NK119, 120
  94. Fernandes E121
  95. Filip I122, 123
  96. Fischer F124
  97. Foigt NA125
  98. Foroutan M126, 127
  99. Fukumoto T128
  100. Gad MM129, 130
  101. Gaidhane AM131
  102. Gebregiorgis BG47
  103. Gebremedhin KB132
  104. Getacher L133
  105. Ghadiri K134, 135
  106. Ghashghaee A136
  107. Golechha M137
  108. Gubari MIM138
  109. Gugnani HC139, 140
  110. Guimaraes RA141
  111. Haider MR142
  112. Hajmirzaian A143, 144
  113. Hamidi S145
  114. Hashi A146
  115. Hassanipour S147, 148
  116. Hassankhani H149, 150
  117. Hayat K151, 152
  118. Herteliu C153, 154
  119. Ho HC155
  120. Holla R50
  121. Hosseini M156, 157
  122. Hosseinzadeh M158, 159
  123. Hwang BF160
  124. Ibitoye SE161
  125. Ilesanmi OS162, 163
  126. Ilic IM164
  127. Ilic MD165
  128. Islam RM166
  129. Iwu CCD167
  130. Jakovljevic M168, 169
  131. Jha RP170, 171
  132. Ji JS172
  133. Johnson KB1
  134. Joseph N173
  135. Joshua V174
  136. Joukar F147, 148
  137. Jozwiak JJ175
  138. Kalankesh LR176
  139. Kalhor R177, 178
  140. Kamyari N179
  141. Kanchan T180
  142. Matin BK118
  143. Karimi SE181
  144. Kayode GA182, 183
  145. Karyani AK118
  146. Keramati M184
  147. Khan EA185
  148. Khan G186
  149. Khan MN187
  150. Khatab K188, 189
  151. Khubchandani J190
  152. Kim YJ191
  153. Kisa A192, 193
  154. Kisa S194
  155. Kopec JA195, 196
  156. Kosen S197
  157. Laxminarayana SLK198
  158. Koyanagi A199, 200
  159. Krishan K201
  160. Defo BK202, 203
  161. Kugbey N204
  162. Kulkarni V173
  163. Kumar M205, 206
  164. Kumar N173
  165. Kusuma D207, 208
  166. La Vecchia C209
  167. Lal DK210
  168. Landires I211, 212
  169. Larson HJ1, 213
  170. Lasrado S214
  171. Lee PH215
  172. Li S216
  173. Liu X217, 218
  174. Maleki A219, 220
  175. Malik P221, 222
  176. Mansournia MA156
  177. Martinsmelo FR223
  178. Mendoza W224
  179. Menezes RG225
  180. Mengesha EW226
  181. Meretoja TJ227, 228
  182. Mestrovic T229, 230
  183. Mirica A153
  184. Moazen B56, 231
  185. Mohamad O232
  186. Mohammad Y233
  187. Mohammadianhafshejani A234
  188. Mohammadpourhodki R235
  189. Mohammed S236, 237
  190. Mohammed S236, 237
  191. Mokdad AH1, 98
  192. Moradi M118
  193. Moraga P240
  194. Mubarik S241
  195. Mulu GBB242
  196. Mwanri L243
  197. Nagarajan AJ244, 245
  198. Naimzada MD246, 247
  199. Naveed M248
  200. Nazari J249
  201. Ndejjo R250
  202. Negoi I251, 252
  203. Ngalesoni FN253
  204. Nguefacktsague G254
  205. Ngunjiri JW255
  206. Nguyen CT256
  207. Nguyen HLT256
  208. Nnaji CA257, 258
  209. Noubiap JJ259
  210. Nunezsamudio V260, 261
  211. Nwatah VE262, 263
  212. Oancea B264
  213. Odukoya OO265, 266
  214. Olagunju AT267, 268
  215. Olakunde BO269
  216. Olusanya BO270
  217. Olusanya JO270
  218. Bali AO271
  219. Onwujekwe OE272
  220. Orisakwe OE273
  221. Otstavnov N246
  222. Otstavnov SS246, 274
  223. Owolabi MO275, 276
  224. Mahesh PA277
  225. Padubidri JR278
  226. Pana A153, 279
  227. Pandey A280, 281
  228. Pandiperumal SR282
  229. Kan FP283
  230. Patton GC284, 285
  231. Pawar S286
  232. Peprah EK287
  233. Postma MJ288, 289
  234. Preotescu L290, 291
  235. Syed ZQ131
  236. Rabiee N292, 293
  237. Radfar A294
  238. Rafiei A295, 296
  239. Rahim F297
  240. Rahimimovaghar V298
  241. Rahmani AM299
  242. Ramezanzadeh K143
  243. Rana J300, 301
  244. Ranabhat CL302, 303
  245. Rao SJ304
  246. Rawaf DL305, 306
  247. Rawaf S307, 308
  248. Rawassizadeh R309
  249. Regassa LD310
  250. Rezaei N311, 312
  251. Rezapour A26
  252. Riaz MA313
  253. Ribeiro AI314
  254. Ross JM1, 315, 316
  255. Rubagotti E317, 318
  256. Rumisha SF319, 320
  257. Rwegerera GM321
  258. Moghaddam SS117
  259. Sagar R322
  260. Sahiledengle B323
  261. Sahu M1
  262. Salem MR324
  263. Kafil HS325
  264. Samy AM326
  265. Sartorius B98, 327, 328
  266. Sathian B329, 330
  267. Seidu AA88, 331
  268. Shaheen AA332
  269. Shaikh MA333
  270. Shamsizadeh M334
  271. Shiferaw WS47
  272. Shin JI335
  273. Shrestha R336
  274. Singh JA337, 338
  275. Skryabin VY339
  276. Skryabina AA340
  277. Soltani S118
  278. Sufiyan MB341
  279. Tabuchi T342
  280. Tadesse EG343
  281. Taveira N344, 345
  282. Tesfay FH346, 347
  283. Thapar R173
  284. Tovanipalone MR348, 349
  285. Tsegaye GW350
  286. Umeokonkwo CD351
  287. Unnikrishnan B352
  288. Villafane JH353
  289. Violante FS354, 355
  290. Vo B356
  291. Vu GT357
  292. Wado YD358
  293. Waheed Y359
  294. Wamai RG360, 361
  295. Wang Y362
  296. Ward P363
  297. Wickramasinghe ND364
  298. Wilson K365
  299. Yaya S366, 367
  300. Yip P368, 369
  301. Yonemoto N370, 371
  302. Yu C241
  303. Zastrozhin MS372, 373
  304. Zhang Y374, 375
  305. Zhang ZJ376
  306. Hay SI1, 98
  307. Dwyerlindgren L1, 98

Source: BMC Medicine Published:2022


Abstract

Background: Human immunodeficiency virus and acquired immune deficiency syndrome (HIV/AIDS) is still among the leading causes of disease burden and mortality in sub-Saharan Africa (SSA), and the world is not on track to meet targets set for ending the epidemic by the Joint United Nations Programme on HIV/AIDS (UNAIDS) and the United Nations Sustainable Development Goals (SDGs). Precise HIV burden information is critical for effective geographic and epidemiological targeting of prevention and treatment interventions. Age- and sex-specific HIV prevalence estimates are widely available at the national level, and region-wide local estimates were recently published for adults overall. We add further dimensionality to previous analyses by estimating HIV prevalence at local scales, stratified into sex-specific 5-year age groups for adults ages 15–59 years across SSA. Methods: We analyzed data from 91 seroprevalence surveys and sentinel surveillance among antenatal care clinic (ANC) attendees using model-based geostatistical methods to produce estimates of HIV prevalence across 43 countries in SSA, from years 2000 to 2018, at a 5 × 5-km resolution and presented among second administrative level (typically districts or counties) units. Results: We found substantial variation in HIV prevalence across localities, ages, and sexes that have been masked in earlier analyses. Within-country variation in prevalence in 2018 was a median 3.5 times greater across ages and sexes, compared to for all adults combined. We note large within-district prevalence differences between age groups: for men, 50% of districts displayed at least a 14-fold difference between age groups with the highest and lowest prevalence, and at least a 9-fold difference for women. Prevalence trends also varied over time; between 2000 and 2018, 70% of all districts saw a reduction in prevalence greater than five percentage points in at least one sex and age group. Meanwhile, over 30% of all districts saw at least a five percentage point prevalence increase in one or more sex and age group. Conclusions: As the HIV epidemic persists and evolves in SSA, geographic and demographic shifts in prevention and treatment efforts are necessary. These estimates offer epidemiologically informative detail to better guide more targeted interventions, vital for combating HIV in SSA. © 2022, The Author(s).
Other Related Docs