Time series: theory and methods
Time series: theory and methods
Effects of randomness of risk factors on the HIV epidemic in homosexual populations
SIAM Journal on Applied Mathematics
Bayesian forecasting and dynamic models (2nd ed.)
Bayesian forecasting and dynamic models (2nd ed.)
The chain multinomial models of the HIV epidemiology in homosexual populations
Mathematical and Computer Modelling: An International Journal
A stochastic model of the HIV epidemic involving both sexual contact and IV drug use
Mathematical and Computer Modelling: An International Journal
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A state-space approach is proposed for modelling the HIV epidemic. This model allows us to estimate and project the number of AIDS cases and the number of infective people at different stages using the Kalman recursion, in which we combine the information from the dynamic model and the observation of AIDS cases. The dynamic models (the state equations) are derived from the chain multinomial model proposed by Tan and his colleagues. The observation equations are the observed (reported) AIDS cases and the total system population which can be obtained by population survey. The methodology is illustrated by modelling the HIV epidemic in the homosexual population in the city of San Francisco. A brief discussion is given on the relationship between the backcalculation and our approach.