The sheer number of orphans being created is unusual in human history, as is the fact that many are dual orphans, children who have lost both parents and must be cared for by someone else. Compounding the problem for the elderly is the fact that their own numbers and the proportion of the population they constitute are also being affected by the epidemic, and all of the changes wrought by an HIV epidemic evolve as the epidemic grows and stabilizes. Accordingly, to adequately understand the total impact of the epidemic on the number and proportion of children who are orphans and on the number of grandparents and other family members who will be alive to care for them, one must employ a “whole population” model. Such a model takes into account all of the major avenues through which HIV impacts a population and how these interact with one another. Gregson, Garnett, and Anderson (1994) constructed one such model in the mid-1990s and used it to predict the major increase in the number and proportion of children who are orphaned as a result of HIV. Many of their theoretical findings are being validated now, as the epidemic unfolds and large numbers of orphans begin to appear in the worst affected African countries (Joint United Nations Programme on HIV/AIDS, UNICEF, and U.S. Agency for International Development, 2002).

Gregson and colleagues (1994) also examined more general demographic impacts of an HIV epidemic and demonstrate significant changes in the age-specific sex ratio, population age structure, and overall growth rates—all of which affect the elderly as the underlying structure and size of the population changes. Results presented here largely corroborate their findings while adding some additional nuances.

The work presented here employs a different modeling strategy from that used by Gregson and colleagues (1994) to explore many of the same questions. The individual-level microsimulator used here is capable of modeling marriage, sex, and the biological and behavioral impacts of HIV. The individual-level nature of the model allows it to track the links between parents and children and grandparents and grandchildren. In comparison to the deterministic, compartmental model used by Gregson and colleagues, this model provides a direct means through which to measure the number of orphans and the number of grandparents who could be living with orphaned grandchildren. In addition, it is able to realistically model two different types of intervention: a preventive, largely behaviorally mediated intervention and an antiretroviral treatment program, which reduces viral load and increases the time between infection and death without having other specific preventive effects. Treatment programs of these two types are simulated in the late phase of an HIV epidemic to ascertain their overall effects and how these affect the situation of the elderly. It is important to keep in mind that the microsimulator used here is a heuristic tool that allows us to explore the intricate, interrelated processes operating to create

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