Abstract
Improve models for estimating HIV epidemic trends in sub-Saharan Africa (SSA). Mathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data. We modified EPP to incorporate age and sex stratification (EPP-ASM) to more accurately capture the shifting demographics of maturing HIV epidemics. Secondly, we developed a new functional form for the HIV transmission rate, termed 'r-hybrid', which combines a four-parameter logistic function for the initial epidemic growth, peak, and decline followed by a first-order random walk for recent trends after epidemic stabilization. We fitted the r-hybrid model along with previously developed r-spline and r-trend models to HIV prevalence data from household surveys and ANC-SS in 177 regions in 34 SSA countries. We used leave-one-out cross validation with household survey HIV prevalence to compare model predictions. The r-hybrid and r-spline models typically provided similar HIV prevalence trends, but sometimes qualitatively different assessments of recent incidence trends because of different structural assumptions about the HIV transmission rate. The r-hybrid model had the lowest average continuous ranked probability score, indicating the best model predictions. Coverage of 95% posterior predictive intervals was 91.5% for the r-hybrid model, versus 87.2 and 85.5% for r-spline and r-trend, respectively. The EPP-ASM and r-hybrid models improve consistency of EPP and Spectrum, improve the epidemiological assumptions underpinning recent HIV incidence estimates, and improve estimates and short-term projections of HIV prevalence trends. Countries that use general population survey and ANC-SS data to estimate HIV epidemic trends should consider using these tools.
Highlights
In sub-Saharan Africa (SSA), key HIV epidemic indicators are estimated by fitting mathematical models to HIV prevalence data from sentinel surveillance among pregnant women attending antenatal care (ANC-SS) and nationally representative household surveys of the general adult population
Population surveys consistently find that viral suppression amongst persons on antiretroviral treatment (ART) is between 85 and 95% and studies conclusively demonstrate that persons who are virally suppressed do not transmit HIV [20], the lower value of v 1⁄4 0.7 reflects that the average population impact of an increase in ART coverage is somewhat less
In some cases, the models can produce qualitatively different trends for HIV incidence, which can be understood through assumptions about the transmission rate r(t)
Summary
In sub-Saharan Africa (SSA), key HIV epidemic indicators are estimated by fitting mathematical models to HIV prevalence data from sentinel surveillance among pregnant women attending antenatal care (ANC-SS) and nationally representative household surveys of the general adult population. Mathematical models combine epidemiologic information about natural history of HIV infection, population data, and the effects of antiretroviral treatment (ART) programmes to infer HIV incidence and AIDS mortality consistent with the observed HIV prevalence trends. The Estimation and Projection Package (EPP) is a basic HIV epidemic model implemented within the Spectrum software for this purpose. EPP was initially conceived as a simple four-parameter HIV epidemic model capturing the HIV epidemic growth rate, start time, epidemic peak, and stabilization following initial decline [1,2]. Parameter inference from ANC-SS HIV prevalence was initially via maximum likelihood [3] and subsequently probabilistic
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