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Using Population-Size Estimation and Cross-sectional Survey Methods to Evaluate HIV Service Coverage Among Key Populations in Burkina Faso and Togo.

Identifieur interne : 000A72 ( Ncbi/Merge ); précédent : 000A71; suivant : 000A73

Using Population-Size Estimation and Cross-sectional Survey Methods to Evaluate HIV Service Coverage Among Key Populations in Burkina Faso and Togo.

Auteurs : Claire E. Holland [États-Unis] ; Seni Kouanda ; Marcel Lougué ; Vincent Palokinam Pitche ; Sheree Schwartz [États-Unis] ; Simplice Anato ; Henri Gautier Ouedraogo ; Jules Tchalla ; Clarence S. Yah [États-Unis] ; Laurent Kapesa ; Sosthenes Ketende [États-Unis] ; Chris Beyrer [États-Unis] ; Stefan Baral [États-Unis]

Source :

RBID : pubmed:28123223

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English descriptors

Abstract

The objective of our study was to measure progress toward the UNAIDS 90-90-90 HIV care targets among key populations in urban areas of 2 countries in West Africa: Burkina Faso and Togo.

DOI: 10.1177/0033354916677237
PubMed: 28123223

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pubmed:28123223

Le document en format XML

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<term>Adolescent</term>
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<term>Cross-Sectional Studies</term>
<term>Female</term>
<term>HIV Infections (epidemiology)</term>
<term>Health Services Accessibility (statistics & numerical data)</term>
<term>Homosexuality, Male</term>
<term>Humans</term>
<term>Male</term>
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<term>Accessibilité des services de santé ()</term>
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<term>Burkina (épidémiologie)</term>
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<term>Homosexualité masculine</term>
<term>Humains</term>
<term>Infections à VIH (épidémiologie)</term>
<term>Jeune adulte</term>
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<term>Adult</term>
<term>Cross-Sectional Studies</term>
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<term>Accessibilité des services de santé</term>
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<term>Adulte</term>
<term>Adulte d'âge moyen</term>
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<term>Homosexualité masculine</term>
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<front>
<div type="abstract" xml:lang="en">The objective of our study was to measure progress toward the UNAIDS 90-90-90 HIV care targets among key populations in urban areas of 2 countries in West Africa: Burkina Faso and Togo.</div>
</front>
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<Month>01</Month>
<Day>26</Day>
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<DateCompleted>
<Year>2017</Year>
<Month>06</Month>
<Day>26</Day>
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<Year>2017</Year>
<Month>06</Month>
<Day>26</Day>
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<ISSN IssnType="Electronic">1468-2877</ISSN>
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<Volume>131</Volume>
<Issue>6</Issue>
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<Year>2016</Year>
<Month>Nov</Month>
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<Title>Public health reports (Washington, D.C. : 1974)</Title>
<ISOAbbreviation>Public Health Rep</ISOAbbreviation>
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<ArticleTitle>Using Population-Size Estimation and Cross-sectional Survey Methods to Evaluate HIV Service Coverage Among Key Populations in Burkina Faso and Togo.</ArticleTitle>
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<AbstractText Label="OBJECTIVES" NlmCategory="OBJECTIVE">The objective of our study was to measure progress toward the UNAIDS 90-90-90 HIV care targets among key populations in urban areas of 2 countries in West Africa: Burkina Faso and Togo.</AbstractText>
<AbstractText Label="METHODS" NlmCategory="METHODS">We recruited female sex workers (FSWs) and men who have sex with men (MSM) through respondent-driven sampling. From January to July 2013, 2738 participants were enrolled, tested for HIV, and completed interviewer-administered surveys. We used population-size estimation methods to calculate the number of people who were engaged in the HIV continuum of care.</AbstractText>
<AbstractText Label="RESULTS" NlmCategory="RESULTS">HIV prevalence ranged from 0.6% (2 of 329) of MSM in Kara, Togo, to 32.9% (115 of 350) of FSWs in Bobo Dioulasso, Burkina Faso. Of those confirmed to be HIV infected, a range of 0.0% (0 of 2) of MSM in Kara to 55.7% (64 of 115) of FSWs in Bobo Dioulasso were using ART. Based on population estimates, the percentage gap between HIV-infected people who should be using ART (per the 90-90-90 targets) and those who reported using ART ranged from 31.5% among FSWs in Bobo Dioulasso to 100.0% among MSM in Kara.</AbstractText>
<AbstractText Label="CONCLUSIONS" NlmCategory="CONCLUSIONS">HIV service coverage among MSM and FSWs in Burkina Faso and Togo was low in 2013. Interventions for improving engagement of these at-risk populations in the HIV continuum of care should include frequent, routine HIV testing and linkage to evidence-based HIV treatment services. Population-size estimates can be used to inform governments, policy makers, and funding agencies about where elements of HIV service coverage are most needed.</AbstractText>
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<ForeName>Claire E</ForeName>
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</AffiliationInfo>
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<LastName>Kouanda</LastName>
<ForeName>Seni</ForeName>
<Initials>S</Initials>
<AffiliationInfo>
<Affiliation>Institut de Recherche en Sciences de la Santé, Ouagadougou, Burkina Faso, West Africa; Institut Africain de Santé Publique, Ouagadougou, Burkina Faso, West Africa.</Affiliation>
</AffiliationInfo>
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<ForeName>Marcel</ForeName>
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</AffiliationInfo>
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<Affiliation>National AIDS Council, Lomé, Togo, West Africa; University of Lomé, Lomé, Togo, West Africa.</Affiliation>
</AffiliationInfo>
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<Affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.</Affiliation>
</AffiliationInfo>
</Author>
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<ForeName>Simplice</ForeName>
<Initials>S</Initials>
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<Affiliation>Arc-en-Ciel, Lomé, Togo, West Africa.</Affiliation>
</AffiliationInfo>
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<Affiliation>Institut de Recherche en Sciences de la Santé, Ouagadougou, Burkina Faso, West Africa.</Affiliation>
</AffiliationInfo>
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<LastName>Yah</LastName>
<ForeName>Clarence S</ForeName>
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<Affiliation>Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.</Affiliation>
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<LastName>Ketende</LastName>
<ForeName>Sosthenes</ForeName>
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