TY - JOUR
T1 - The Estimation and Projection Package Age-Sex Model and the r-hybrid model
T2 - New tools for estimating HIV incidence trends in sub-Saharan Africa
AU - Eaton, Jeffrey W.
AU - Brown, Tim
AU - Puckett, Robert
AU - Glaubius, Robert
AU - Mutai, Kennedy
AU - Bao, Le
AU - Salomon, Joshua A.
AU - Stover, John
AU - Mahy, Mary
AU - Hallett, Timothy B.
N1 - Funding Information:
Funding: This research was supported by UNAIDS, NIH R01-AI136664, and the Bill and Melinda Gates Foundation. We acknowledge joint MRC Centre funding from the UK Medical Research Council and Department for International Development via MRC MR/R015600/1.
Publisher Copyright:
© 2019 The Author(s). Published by Wolters Kluwer Health, Inc.
PY - 2019/12/15
Y1 - 2019/12/15
N2 - Objectives:Improve models for estimating HIV epidemic trends in sub-Saharan Africa (SSA).Design:Mathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data.Methods: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.Results: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.Conclusion: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.
AB - Objectives:Improve models for estimating HIV epidemic trends in sub-Saharan Africa (SSA).Design:Mathematical epidemic model fit to national HIV survey and ANC sentinel surveillance (ANC-SS) data.Methods: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.Results: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.Conclusion: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.
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U2 - 10.1097/QAD.0000000000002437
DO - 10.1097/QAD.0000000000002437
M3 - Article
C2 - 31800403
AN - SCOPUS:85076038956
SN - 0269-9370
VL - 33
SP - S235-S244
JO - AIDS
JF - AIDS
ER -