Challenges in estimating HIV prevalence trends and geographical variation in HIV prevalence using antenatal data: Insights from mathematical modelling

PloS One
L F JohnsonJeffrey W Eaton

Abstract

HIV prevalence data among pregnant women have been critical to estimating HIV trends and geographical patterns of HIV in many African countries. Although antenatal HIV prevalence data are known to be biased representations of HIV prevalence in the general population, mathematical models have made various adjustments to control for known sources of bias, including the effect of HIV on fertility, the age profile of pregnant women and sexual experience. We assessed whether assumptions about antenatal bias affect conclusions about trends and geographical variation in HIV prevalence, using simulated datasets generated by an agent-based model of HIV and fertility in South Africa. Results suggest that even when controlling for age and other previously-considered sources of bias, antenatal bias in South Africa has not been constant over time, and trends in bias differ substantially by age. Differences in the average duration of infection explain much of this variation. We propose an HIV duration-adjusted measure of antenatal bias that is more stable, which yields higher estimates of HIV incidence in recent years and at older ages. Simpler measures of antenatal bias, which are not age-adjusted, yield estimates of HIV prevalence and inci...Continue Reading

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Citations

Sep 4, 2021·AIDS and Behavior·Joseph W HoganWendy W Davis

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Methods Mentioned

BETA
contraception
circumcision
ELISA

Software Mentioned

MicroCOSM ( Microsimulation for
MicroCOSM
Thembisa

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