ArticlePloS one2022
Sub optimal HIV status ascertainment at antenatal clinics and the impact on HIV prevalence estimates: A cross sectional study.
Article in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundWhile many countries including Kenya transitioned from sentinel surveillance to the use of routine antenatal care (ANC) data to estimate the burden of HIV, countries in Sub Saharan Africa reported several challenges of this transition, including low uptake of HIV testing and sub national / site-level differences in HIV prevalence estimates. In Kenya voluntary HIV testing is offered to all 1st ANC clients. However, some women may decline testing. We aim to predict the HIV positivity (as a proxy of prevalence) at ANC assuming 100% uptake of HIV testing and compare this to the observed positivity.
methodsUsing a cross sectional study design, we examine routine data on HIV testing among all women attending ANC in Kwale County, Kenya, for the period January 2015 to December 2019.We used a generalized estimating equation with binomial distribution to model the observed HIV prevalence as explained by HIV status ascertainment. We then used marginal standardization to predict the HIV prevalence at 100% HIV status ascertainment and make recommendations to improve the utility of ANC routine data for HIV surveillance.
resultsHIV testing at ANC was at 91.3%, slightly above the global target of 90%. If there was 100% HIV status ascertainment at ANC, the HIV prevalence would be 2.7% (95% CI 2.3-3.2). This was 0.3% lower than the observed prevalence. Across the yearly predictions, there was no difference between the observed and predicted values except for 2018 where the HIV prevalence was underestimated with an absolute bias of -0.2 percent. This implies missed opportunities for identifying new HIV infections in the year 2018.
conclusionsImperfect HIV status ascertainment at ANC overestimates HIV prevalence among women attending ANC in Kwale County. However, the use of ANC routine data may underestimate the true population prevalence. There is need to address both community level and health facility level barriers to the uptake of ANC services.
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