Journal
SCIENCE
Volume 327, Issue 5966, Pages 697-701Publisher
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.1180556
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Funding
- National Institute of Allergy and Infectious Diseases (NIAID) [RO1 AI041935, P30-AI27763]
- Natural Sciences and Engineering Research Council of Canada
- Mathematics of Information Technology and Complex Systems
- John Simon Guggenheim Foundation
- National Academies Keck Foundation
- Semel Institute for Neuroscience Human Behavior
- NCRR [K24RR024369]
- AHRQ [R18-HS017784]
- AHRQ [541399, 5R18HS017784-02] Funding Source: Federal RePORTER
- Div Of Biological Infrastructure
- Direct For Biological Sciences [0832858] Funding Source: National Science Foundation
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Over the past two decades, HIV resistance to antiretroviral drugs (ARVs) has risen to high levels in the wealthier countries of the world, which are able to afford widespread treatment. We have gained insights into the evolution and transmission dynamics of ARV resistance by designing a biologically complex multistrain network model. With this model, we traced the evolutionary history of ARV resistance in San Francisco and predict its future dynamics. By using classification and regression trees, we identified the key immunologic, virologic, and treatment factors that increase ARV resistance. Our modeling shows that 60% of the currently circulating ARV-resistant strains in San Francisco are capable of causing self-sustaining epidemics, because each individual infected with one of these strains can cause, on average, more than one new resistant infection. It is possible that a new wave of ARV-resistant strains that pose a substantial threat to global public health is emerging.
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