Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data, 2010–23 (Q30228): Difference between revisions
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Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa | |||
Latest revision as of 23:55, 8 November 2024
No description defined
- Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data, 2010-23.
- Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data, 2010–23 |
No description defined |
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Statements
Key population HIV programmes in sub-Saharan Africa require epidemiological information to ensure equitable and universal access to effective services. (English)
BACKGROUND (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
We aimed to consolidate and harmonise survey data among female sex workers, men who have sex with men, people who inject drugs, and transgender people to estimate key population size, HIV prevalence, and antiretroviral therapy (ART) coverage for countries in mainland sub-Saharan Africa. (English)
BACKGROUND (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Key population size estimates, HIV prevalence, and ART coverage data from 39 sub-Saharan Africa countries between 2010 and 2023 were collated from existing databases and verified against source documents. (English)
METHODS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
We used Bayesian mixed-effects spatial regression to model urban key population size estimates as a proportion of the gender-matched, year-matched, and area-matched population aged 15-49 years. (English)
METHODS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
We modelled subnational key population HIV prevalence and ART coverage with age-matched, gender-matched, year-matched, and province-matched total population estimates as predictors. (English)
METHODS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
We extracted 2065 key population size data points, 1183 HIV prevalence data points, and 259 ART coverage data points. (English)
FINDINGS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Across national urban populations, a median of 1·65% (IQR 1·35-1·91) of adult cisgender women were female sex workers, 0·89% (0·77-0·95) were men who have sex with men, 0·32% (0·31-0·34) were men who injected drugs, and 0·10% (0·06-0·12) were women who were transgender. (English)
FINDINGS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
HIV prevalence among key populations was, on average, four to six times higher than matched total population prevalence, and ART coverage was correlated with, but lower than, the total population ART coverage with wide heterogeneity in relative ART coverage across studies. (English)
FINDINGS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Across sub-Saharan Africa, key populations were estimated as comprising 1·2% (95% credible interval 0·9-1·6) of the total population aged 15-49 years but 6·1% (4·5-8·2) of people living with HIV. (English)
FINDINGS (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Key populations in sub-Saharan Africa experience higher HIV prevalence and lower ART coverage, underscoring the need for focused prevention and treatment services. (English)
INTERPRETATION (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
In 2024, limited data availability and heterogeneity constrain precise estimates for programming and monitoring trends. (English)
INTERPRETATION (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Strengthening key population surveys and routine data within national HIV strategic information systems would support more precise estimates. (English)
INTERPRETATION (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
UNAIDS, Bill & Melinda Gates Foundation, and US National Institutes of Health. (English)
FUNDING (English)
Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved. (English)
2024
Oliver (English)
Stevens (English)
O
Keith (English)
Sabin (English)
K
Rebecca L (English)
Anderson (English)
RL
Sonia Arias (English)
Garcia (English)
SA
Kalai (English)
Willis (English)
K
Amrita (English)
Rao (English)
A
Anne F (English)
McIntyre (English)
AF
Elizabeth (English)
Fearon (English)
E
Emilie (English)
Grard (English)
E
Alice (English)
Stuart-Brown (English)
A
Frances (English)
Cowan (English)
F
Louisa (English)
Degenhardt (English)
L
James (English)
Stannah (English)
J
Jinkou (English)
Zhao (English)
J
Avi J (English)
Hakim (English)
AJ
Katherine (English)
Rucinski (English)
K
Isabel (English)
Sathane (English)
I
Makini (English)
Boothe (English)
M
Lydia (English)
Atuhaire (English)
L
Mathieu (English)
Maheu-Giroux (English)
M
Lucy (English)
Platt (English)
L
Brian (English)
Rice (English)
B
Wolfgang (English)
Hladik (English)
W
Stefan (English)
Baral (English)
S
Mary (English)
Mahy (English)
M
Jeffrey W (English)
Imai-Eaton (English)
JW
23 September 2024
16 August 2024
Declaration of interests SB has received funding from the US National Institutes of Health (NIH). (English)
FC has received funding from the Wellcome Trust, the Medical Research Council, NIH, Unitaid, and the Bill & Melinda Gates Foundation. (English)
LD has received untied educational grants for the study of new opioid medications in Australia from Indivior and Sequirus. (English)
EF has received funding from the UK Research and Innovation Medical Research Council, the Royal Society, and the Centre for Sexual Health and HIV/AIDS Research Zimbabwe. (English)
JWI-E acknowledges funding from UNAIDS, NIH, the Gates Foundation, UK Research and Innovation, and BAO Systems, and has received support to attend meetings from UNAIDS, the South African Centre for Epidemiological Modelling and Analysis, the International AIDS Society, and the Gates Foundation. (English)
KR and MM-G have received support to attend meetings from UNAIDS. (English)
All other authors declare no competing interests. (English)