{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T21:24:09Z","timestamp":1779917049257,"version":"3.53.1"},"reference-count":86,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T00:00:00Z","timestamp":1768262400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:p>Compartmental models are essential for studying host-pathogen dynamics, evaluating intervention effectiveness, and predicting infection trends. However, the utility of these models for testing competing hypotheses is often overlooked. To address this, we propose a new model-based hypothesis testing (MBHT) approach, which uses compartmental models to evaluate the hypotheses in epidemiology. In our case, using the COVID-19 pandemic as a case study, we formulate hypotheses of SARS-CoV-2 mutation and construct a transmission model to test them. In addition to analyzing steady-state stability, deriving the basic reproduction number, and identifying a backward bifurcation, the model is fitted to seven peaks of U.S. COVID-19 data, each corresponding to periods of viral mutation and morbidity peaks. The estimated posterior probabilities reveal that Short-term within host selection primarily shaped mutations during the early pandemic stages, followed by immune selection driven by natural and vaccine-induced immunity. In later stages, mutations aligned with vaccination-induced virulence and transmission-virulence correlation, while the declining virulence and immune selection partially explained the final stages of SARS-CoV-2 mutation. In conclusion, model-based hypothesis testing offers a powerful yet underutilized approach to uncovering drivers of viral mutation and gaining deeper insights into pathogen evolution during outbreaks.<\/jats:p>","DOI":"10.3389\/fpubh.2025.1702428","type":"journal-article","created":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T13:59:03Z","timestamp":1768312743000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Utility of compartmental models to test the competing hypotheses of pathogen evolution and human intervention"],"prefix":"10.3389","volume":"13","author":[{"given":"Barsha","family":"Saha","sequence":"first","affiliation":[{"name":"Division of Computing, Analytics & Mathematics, School of Science and Engineering, University of Missouri-Kansas City","place":["Kansas City, MO, United 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