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Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.<\/jats:p>","DOI":"10.1371\/journal.ppat.1012236","type":"journal-article","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T15:37:51Z","timestamp":1722267471000},"page":"e1012236","update-policy":"https:\/\/doi.org\/10.1371\/journal.ppat.corrections_policy","source":"Crossref","is-referenced-by-count":18,"title":["Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion"],"prefix":"10.1371","volume":"20","author":[{"given":"Tin","family":"Phan","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jessica 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