Using the Kalman filter and dynamic models to assess the changing HIV/AIDS epidemic.
Many factors, including therapy and behavioral changes, have modified the course of the HIV/AIDS epidemic in recent years. To include these modifications in HIV/AIDS models, in the absence of appropriate external data sources, changes over time in the parameters can be incorporated by a recursive estimation technique such as the Kalman filter. The Kalman filter accounts for stochastic fluctuations in both the model and the data and provides a means to assess any parameter modifications included in new observations. The Kalman filter approach was applied to a simple differential model to describe the observed HIV/AIDS epidemic in the homo/bisexual male community in Paris (France). This approach gave quantitative information on the time-evolution of some parameters of major epidemiological significance (average transmission rate, mean incubation rate, and basic reproduction rate), which appears quite consistent with the recent epidemiological literature.
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Centre de Bioinformatique, Université Paris, France.
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D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D008297:Male; D008433:Mathematics; D008954:Models, Biological; D010297:Paris / Q000453:epidemiology; D013269:Stochastic Processes