{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,7]],"date-time":"2026-10-07T20:40:35Z","timestamp":1791405635168,"version":"4.3.3"},"reference-count":120,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2012,10,4]],"date-time":"2012-10-04T00:00:00Z","timestamp":1349308800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Viruses"],"abstract":"<jats:p>The Human Immunodeficiency Virus (HIV) is one of the most threatening viral agents. This virus infects approximately 33 million people, many of whom are unaware of their status because, except for flu-like symptoms right at the beginning of the infection during the acute phase, the disease progresses more or less symptom-free for 5 to 10 years. During this asymptomatic phase, the virus slowly destroys the immune system until the onset of AIDS when opportunistic infections like pneumonia or Kaposi\u2019s sarcoma can overcome immune defenses. Mathematical models have played a decisive role in estimating important parameters (e.g., virion clearance rate or life-span of infected cells). However, most models only account for the acute and asymptomatic latency phase and cannot explain the progression to AIDS. Models that account for the whole course of the infection rely on different hypotheses to explain the progression to AIDS. The aim of this study is to review these models, present their technical approaches and discuss the robustness of their biological hypotheses. Among the few models capturing all three phases of an HIV infection, we can distinguish between those that mainly rely on population dynamics and those that involve virus evolution. Overall, the modeling quest to capture the dynamics of an HIV infection has improved our understanding of the progression to AIDS but, more generally, it has also led to the insight that population dynamics and evolutionary processes can be necessary to explain the course of an infection.<\/jats:p>","DOI":"10.3390\/v4101984","type":"journal-article","created":{"date-parts":[[2012,10,4]],"date-time":"2012-10-04T11:02:47Z","timestamp":1349348567000},"page":"1984-2013","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":57,"title":["Modelling the Course of an HIV Infection: Insights from Ecology and Evolution"],"prefix":"10.3390","volume":"4","author":[{"given":"Samuel","family":"Alizon","sequence":"first","affiliation":[{"name":"Laboratoire MIVEGEC (UMR CNRS 5290, IRD 224, UM1, UM2), 911 Avenue Agropolis, B.P. 64501, 34394 Montpellier Cedex 5, France"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carsten","family":"Magnus","sequence":"additional","affiliation":[{"name":"Department of Zoology, University of Oxford, South Parks Road, OX1 3PS, Oxford, UK"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2012,10,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1038\/280361a0","article-title":"Population biology of infectious diseases","volume":"280","author":"Anderson","year":"1979","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1016\/0893-9659(90)90051-C","article-title":"Adaptive dynamics and evolutionary stability","volume":"3","author":"Hofbauer","year":"1990","journal-title":"Appl. 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