On the role of variable infectivity in the dynamics of the human immunodeficiency virus epidemic
Mathematical and statistical approaches to AIDS epidemiology
Mixing framework for social/sexual behavior
Mathematical and statistical approaches to AIDS epidemiology
Structured mixing: heterogeneous mixing by the definition of activity groups
Mathematical and statistical approaches to AIDS epidemiology
Mathematical and statistical approaches to AIDS epidemiology
Stochastic models of HIV epidemic in homosexual populations-the effects of mixing patterns
Mathematical and Computer Modelling: An International Journal
Some general stochastic models for the spread of AIDS and some simulation results
Mathematical and Computer Modelling: An International Journal
Modelling the HIV epidemic: A state-space approach
Mathematical and Computer Modelling: An International Journal
A methodological study on fitting a nonlinear stochastic model of the AIDS epidemic in Philadelphia
Mathematical and Computer Modelling: An International Journal
A stochastic model for the HIV epidemic in homosexual populations involving age and race
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
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In this paper, we propose a general class of stochastic models for the HIV epidemic in homosexual populations. This class of models are referred to as chain multinomial models. We illustrate this class of models by assuming some stochastic models of the HIV epidemic in homosexual populations in Sections 2-4 and derive the means, the variances and the covariances; we also derive results for the mean behaviors of these models. It is shown that under proportional mixing, the mean behaviors and the trend of these models are quite similar to one another; yet the variances and covariances of the infective people and AIDS cases of these models are very different over different models. These results suggest that the infection duration of infective people and sexual activity levels have significant impact on the projection of HIV epidemic.