A1197
Title: Addressing population heterogeneity for HIV incidence estimation based on recency test
Authors: Qi Wang - Duke University (United States)
Ann Duerr - Fred Hutchinson Cancer Center (United States)
Fei Gao - Fred Hutchinson Cancer Center (United States) [presenting]
Abstract: Cross-sectional HIV incidence estimation leverages recency test results to determine the HIV incidence of a population of interest, where a recency test uses biomarker profiles to infer whether an HIV-positive individual was recently infected. This approach possesses an obvious advantage over the conventional cohort follow-up method since it avoids longitudinal follow-up and repeated HIV testing. The extension of cross-sectional incidence estimation is considered to estimate the incidence of a different target population, addressing potential population heterogeneity. A general framework is proposed that incorporates two scenarios: one when the target population is a subset of the population with cross-sectional recency testing data and the other with an external target population. In addition, estimators are proposed to incorporate HIV subtypes, a special type of covariate that modifies the properties of the recency test, into the framework. Through simulation studies and a data application, the performance of the proposed methods is demonstrated. It is concluded with a discussion on sensitivity analysis and future work to improve the framework.
