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Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays
Published on: September 26, 2011
Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco
Robert J Smith1, Justin T Okano, James S Kahn
1Center for Biomedical Modeling, Semel Institute of Neuroscience & Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA.
Abstract:
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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