Epidemiologic Modeling of HIV/AIDS: Use of Computational Models to Study the Population Dynamics of the Disease to Assess Effective Intervention Strategies for Decision-making.

Computational models and simulations are becoming central research tools in epidemiology, biology, and other fields. Epidemiologic research involves the study of a complex set of host, environment and causative agent factors as these interact to impact health and diseases in any population. The most advanced of these efforts have focused on micro (cellular) or macro (human) population levels. The dynamic interplay of HIV with a focus in its hosts at the cellular level provides the micro-epidemiologic basis, while the dynamic interplay of multifactorial determinants: biomedical, behavioral, and socioeconomic factors provide the macro-epidemiologic basis at the human population level. We have developed the computational tools and mathematical approaches to study the population-level effects of various drugs on HIV to integrate models from micro to macro- levels in a seamless fashion. The critical variables that facilitate transmission of HIV and intracellular interactions and molecular kinetics were considered. Such multilevel models are essential if we are to develop quantitative, predictive models of complex biological systems such as HIV/AIDS.