Demographic Change in Sub-Saharan Africa (1993) / Chapter Skim
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9 Models of the Demographic Effect of AIDS
9 Models of the Demographic Effect of AIDS
Pages 350-379
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, especially African countries. These modeling efforts have the potential to help health policymakers understand the dynamics of the epidemic, to forecast the burden of illness in the future, and to evaluate potential intervent~ons.
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This chapter describes the currently available models of the HIV/AIDS epidemic and summarizes what these models say about the potential future demographic effects of AIDS in Africa. It is not a comprehensive review of the epidemiology of HIV/AIDS or of all modeling efforts.
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HIV causes severe damage to the immune system, and the course of HIV disease usually spans several years. Some individuals develop an acute illness resembling mononucleosis several weeks or months after infection, but most infected persons have no other clinical signs or symptoms for years.
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Such models explore, for instance, the relative effect of changing sexual behaviors such as number and choice of partners, the use of condoms, and the screening of blood. A third group of models aims at understanding the epidemic's dynamics for the purposes of interpreting epidemiological data, understanding biological aspects of HIV disease and transmission, and making policy recommendations for disease control.
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Epidemic models, on the other hand, specify biologically and behaviorally realistic dynamics and, therefore, must employ a relatively large number of state variables to reflect differences in behavior and disease status in the population. The dynamics of these models reflect the epidemic process; for instance, the number of new HIV infections in a given period is commonly a function of both the number of infectious individuals (based on past infections, the natural history of HIV disease, and other biological and
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The model dynamics consist of equations that describe how the number of individuals in each category changes over time, given the model parameters. The state variables in stochastic or microsimulation models describe the demographic characteristics, risk-related behavioral characteristics, and infection/disease status of each of a finite number of discrete individuals.
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and others have shown that the number of new HIV infections in the United States peaked in the mid-1980s, but that the number of AIDS cases will not peak until the mid-199Os. Another analysis using this model has looked at the possible effect that AZT has had on AIDS mortality (Gail et al., 1990~.
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The state variable lets is the number of new HIV infections in the population at time t. In stable population theory, this is analogous to the population born in year t.
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Demographic/Behavioral Models The distinguishing characteristic of demographic/behavioral models is their explicit representation of the behavioral assumptions underlying the generation of new cases as well as a representation of the epidemic as in the previous category. Within this major category, three subcategories can be distinguished: demographic models, sexual behavior simulation models, and analytic models.
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1,' _ Demographic Models Most of the models of the AIDS epidemic are essentially extensions of the models commonly used in demographic projections. These include the models developed by Bulatao (1991)
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HIV-related mortality rates and rates of transition between stages of HIV infection are determined by epidemiological studies. The existing models differ most markedly in the assumptions they make about the distribution of time from infection to the appearance of symptoms of AIDS.
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Sexual Behavior Simulation Models Two of the existing models focus on detailed descriptions of sexual behavior. One of these models uses a microsimulation approach; the other uses macrosimulation.
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that assumes homogeneous mixing patterns for sexual contacts between susceptible and infectious groups. More complex versions include heterogeneity in sexual behavior via a probability distribution for preferred number of partners.
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, three demographic models (Bulatao, IWG, Palloni) , and two sexual behavior simulation models (Auvert, Dietz)
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The hypothetical population was assumed to be 25 percent urban. The age-specific HIV prevalence rates for urban and rural population were based on HIV serological surveys conducted in several African countries, as estimated by Chin and Lwanga (19911.
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, there was only modest agreement among the models: HIV prevalence ranges from 30.3 to 57.5 percent; life expectancy at birth ranges from 16 to 45 years. In four of the six models, the intrinsic growth rate is negative after 25 years.
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366 ¢ a' o _1 Cal no Cal au o Cal o au Cal a' V: o Ct 4 as o o ,= — o 3 By ._ _ o ~ ~ no V ~ A .o~ ~ lo, 1 0 C't)
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5 4 3 2 1 o Percent of population Auvert Dietz Brouard Bulatao IWG Palioni FIGURE 9-2 Prevalence of AIDS in a hypothetical population after 25 years as projected by six models.
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368 250 200 150 100 50 DEMOGRAPHIC CHANGE IN SUB-SAHARAN AFRICA Thousands : : 1 _ ~,~ Auvert Dietz Brouard Bulatao IWG Palioni FIGURE 9-3 Cumulative cases of AIDS in a hypothetical population after 25 years as projected by six models. 250 200 150 100 50 o Thousands Auvert Dietz Brouard Bulatao iWG Palloni FIGURE 9-4 Cumulative deaths from AIDS in a hypothetical population after 25 years as projected by four models.
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MODELS OF THE DEMOGRAPHIC EFFECT OF AIDS 60 50 40 30 20 10 n Years t~ , 369 Auvert Dietz Brouard Bulatao IWG Palloni FIGURE 9-S Life expectancy at birth in a hypothetical population after 25 years as projected by five models. 3 2.5 2 1.5 0.5 Percent , .~ ~ Auvert Dietz Brouard Bulatao IWG Palloni FIGURE 9-6 Rate of natural increase in a hypothetical population after 25 years as projected by six models.
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Among the demographic models, the Bulatao model predicts substantially higher HIV and AIDS prevalence rates in the final period than all of the other models, and the IWG model predicts substantially higher cumulative AIDS cases and deaths. The intermediate scenario seems to be the most realistic of the three UN/GPA workshop scenarios, but the numerical results are widely divergent.
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The IWG model predicts one important "noneffect," and this result is supported by other models of various types: The AIDS/HIV epidemic has very little effect on the population age distribution or on dependency ratios. Because AIDS affects childhood as well as adult mortality (and across a relatively wide age range)
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. The IWG model itself continues to be further developed and used, but no complete description of its modeling assumptions or results had been published as of August 1993.
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Whether the mean or the functional form of the incubation period depends on cofactors is not known. There is evidence that antiviral drugs such as AZT can lengthen the incubation period as well as the symptomatic period, but this increase is unlikely to be relevant for African countries in the near future.
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The added refinements of age-dependent changes in sexual behavior, men having sexual contact with women younger than themselves and not infrequent male contact with a small proportion of women with high rates of sexual-partner change, all serve to accentuate the predicted demographic impact, with the only significant uncertainty being whether AIDS induced mortality will decrease population size over a few or many decades. Note that this statement in a scientific journal is less extreme than the news reports mentioned earlier.
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The largest effect would be on mortality rates for children age 0 to 5 years and for young adults, and the changes could reverse mortality gains of the last few decades. Changes of this magnitude would substantially decrease population growth rates, but it is not clear whether negative growth rates would obtain, at least in the next few decades.
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In contrast to these qualitative results, much remains to be learned before HIV/AIDS models can provide reliable numerical estimates of demographic effects. There is little hard information on many of the critical biological parameters that describe the infectious process and the natural history of HIV disease.
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The spread of HIV-1 in Africa: Sexual contact patterns and the predicted demographic impact of AIDS. Nature 352:581-589.
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Bos 1988 Implications of control measures for the spread of HIV infection. Paper presented at the annual meeting of the Population Association of America, New Orleans, April.
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Curry 1991 The United States Interagency Working Group approach: The IWG model for the heterosexual spread of HIV and the demographic impact of the AIDS epidemic.
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