Science (New York, N.Y.) · 2010
Evolutionary dynamics of complex networks of HIV drug-resistant strains: the case of San Francisco.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАПоддержка службы здравоохранения СШАНазвание и аннотация: Перевод пока не подготовлен
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Smith Robert J, Okano Justin T, Kahn James S, Bodine Erin N, Blower Sally
Аннотация
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.
Предметные рубрики MeSH
Anti-HIV AgentsAntiretroviral Therapy, Highly ActiveComputer SimulationDisease OutbreaksDrug Resistance, Multiple, ViralDrug Resistance, ViralDrug Therapy, CombinationEvolution, MolecularForecastingHIVHIV InfectionsHIV Protease InhibitorsHomosexuality, MaleHumansMaleModels, StatisticalMonte Carlo MethodProbabilityReverse Transcriptase InhibitorsSan Francisco