Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco.
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.
Smith
Robert J
RJ
Center for Biomedical Modeling, Semel Institute of Neuroscience & Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90024, USA.
Okano
Justin T
JT
Kahn
James S
JS
Bodine
Erin N
EN
Blower
Sally
S
D019380:Anti-HIV Agents / Q000494:pharmacology* / Q000627:therapeutic use; D023241:Antiretroviral Therapy, Highly Active; D003198:Computer Simulation; D004196:Disease Outbreaks; D024921:Drug Resistance, Multiple, Viral; D024882:Drug Resistance, Viral; D004359:Drug Therapy, Combination; D019143:Evolution, Molecular; D005544:Forecasting; D006678:HIV / Q000187:drug effects* / Q000235:genetics; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology / Q000635:transmission* / Q000821:virology*; D017320:HIV Protease Inhibitors / Q000494:pharmacology / Q000627:therapeutic use; D018451:Homosexuality, Male; D006801:Humans; D008297:Male; D015233:Models, Statistical; D009010:Monte Carlo Method; D011336:Probability; D018894:Reverse Transcriptase Inhibitors / Q000494:pharmacology / Q000627:therapeutic use; D012495:San Francisco / Q000453:epidemiology
D019380:Anti-HIV Agents; D017320:HIV Protease Inhibitors; D018894:Reverse Transcriptase Inhibitors