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This approach possesses an obvious advantage over the conventional cohort follow\u2010up method since it avoids longitudinal follow\u2010up and repeated HIV testing. In this manuscript, we consider the extension of cross\u2010sectional incidence estimation to estimate the incidence of a different target population, addressing potential population heterogeneity. We propose a general framework that incorporates two scenarios: one when the target population is a subset of the population with cross\u2010sectional recency testing data and the other with an external target population. In addition, we propose estimators to incorporate HIV subtypes, a special type of covariate that modifies the properties of recency tests, into our framework. Through simulation studies and a data application, we demonstrate the performance of the proposed methods. We conclude with a discussion on sensitivity analysis and future work to improve our framework.<\/jats:p>","DOI":"10.1002\/sim.70216","type":"journal-article","created":{"date-parts":[[2025,8,8]],"date-time":"2025-08-08T15:54:07Z","timestamp":1754668447000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Addressing Population Heterogeneity for HIV Incidence Estimation Based on Recency Test"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9342-4053","authenticated-orcid":false,"given":"Qi","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Biostatistics and Bioinformatics Duke University  Durham North Carolina USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ann","family":"Duerr","sequence":"additional","affiliation":[{"name":"Vaccine and Infectious Disease Division Fred Hutchinson Cancer Research Center  Seattle Washington 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