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Cross-sectional HIV incidence estimation leverages recency test results todetermine the HIV incidence of a population of interest, where recency testuses biomarker profiles to infer whether an HIV-positive individual was"recently" infected. This approach possesses an obvious advantage over theconventional cohort follow-up method since it avoids longitudinal follow-up andrepeated HIV testing. In this manuscript, we consider the extension ofcross-sectional incidence estimation to estimate the incidence of a differenttarget population addressing potential population heterogeneity. We propose ageneral framework that incorporates two settings: one with the targetpopulation that is a subset of the population with cross-sectional recencytesting data, e.g., leveraging recency testing data from screening inactive-arm trial design, and the other with an external target population. Wealso propose a method to incorporate HIV subtype, a special covariate thatmodifies the properties of recency test, into our framework. Through extensivesimulation studies and a data application, we demonstrate the excellentperformance of the proposed methods. We conclude with a discussion ofsensitivity analysis and future work to improve our framework.

Addressing Population Heterogeneity for HIV Incidence Estimation Based on Recency Test