ArticleSexually transmitted infections2012
National HIV prevalence estimates for sub-Saharan Africa: controlling selection bias with Heckman-type selection models.
Article in Sexually transmitted infections, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Socio-demographic characteristics and risk factors for HIV transmission in female bar workers in sub-Saharan Africa: a systematic literature review.BMC public health · 2020Pooled it
- Frequency of HIV-testing and factors associated with multiple lifetime HIV-testing among a rural population of Zambian men.BMC public health · 2015Trial
- Correcting for selection bias in HIV prevalence estimates: an application of sample selection models using data from population-based HIV surveys in seven sub-Saharan African countries.Journal of the International AIDS Society · 2022Article
- Community-based progress indicators for prevention of mother-to-child transmission and mortality rates in HIV-exposed children in rural Mozambique.BMC public health · 2021Article
- Quantifying the gender gap in the HIV care cascade in southern Mozambique: We are missing the men.PloS one · 2021Article
- Impact of Home-Based HIV Testing Services on Progress Toward the UNAIDS 90-90-90 Targets in a Hyperendemic Area of South Africa.Journal of acquired immune deficiency syndromes (1999) · 2019Article
- Major depressive disorder prevalence and risk factors among Syrian asylum seekers in Greece.BMC public health · 2018Article
- Role of survey response rates on valid inference: an application to HIV prevalence estimates.Emerging themes in epidemiology · 2018Article
- Community-based strategies to strengthen men's engagement in the HIV care cascade in sub-Saharan Africa.PLoS medicine · 2017Article
- Are all biases missing data problems?Current epidemiology reports · 2015Article
- On the assumption of bivariate normality in selection models: a Copula approach applied to estimating HIV prevalence.Epidemiology (Cambridge, Mass.) · 2015Article
- Using interviewer random effects to remove selection bias from HIV prevalence estimates.BMC medical research methodology · 2015Article
- Socioeconomic gradients in internalized stigma among 4,314 persons with HIV in sub-Saharan Africa.AIDS and behavior · 2015Article
- A cautionary note about estimating effects of secondary exposures in cohort studies.American journal of epidemiology · 2015Article
- Trends in socioeconomic inequalities in HIV prevalence among young people in seven countries in eastern and southern Africa.PloS one · 2015Article
- Adjusting HIV prevalence estimates for non-participation: an application to demographic surveillance.Journal of the International AIDS Society · 2015Article
- Assessing and adjusting for differences between HIV prevalence estimates derived from national population-based surveys and antenatal care surveillance, with applications for Spectrum 2013.AIDS (London, England) · 2014Article
- Refusal bias in the estimation of HIV prevalence.Demography · 2014Article
- Validation, replication, and sensitivity testing of Heckman-type selection models to adjust estimates of HIV prevalence.PloS one · 2014Article
- Sexual behaviour in a rural high HIV prevalence South African community: time trends in the antiretroviral treatment era.AIDS (London, England) · 2013Article
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6 authors.
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Abstract
objectivesPopulation-based HIV testing surveys have become central to deriving estimates of national HIV prevalence in sub-Saharan Africa. However, limited participation in these surveys can lead to selection bias. We control for selection bias in national HIV prevalence estimates using a novel approach, which unlike conventional imputation can account for selection on unobserved factors.
methodsFor 12 Demographic and Health Surveys conducted from 2001 to 2009 (N=138 300), we predict HIV status among those missing a valid HIV test with Heckman-type selection models, which allow for correlation between infection status and participation in survey HIV testing. We compare these estimates with conventional ones and introduce a simulation procedure that incorporates regression model parameter uncertainty into confidence intervals.
resultsSelection model point estimates of national HIV prevalence were greater than unadjusted estimates for 10 of 12 surveys for men and 11 of 12 surveys for women, and were also greater than the majority of estimates obtained from conventional imputation, with significantly higher HIV prevalence estimates for men in Cote d'Ivoire 2005, Mali 2006 and Zambia 2007. Accounting for selective non-participation yielded 95% confidence intervals around HIV prevalence estimates that are wider than those obtained with conventional imputation by an average factor of 4.5.
conclusionsOur analysis indicates that national HIV prevalence estimates for many countries in sub-Saharan African are more uncertain than previously thought, and may be underestimated in several cases, underscoring the need for increasing participation in HIV surveys. Heckman-type selection models should be included in the set of tools used for routine estimation of HIV prevalence.
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