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Bayesian Projection of Life Expectancy Accounting for the HIV/AIDS Epidemic

Jessica L Godwin and Adrian Elmes Raftery

August 2016 CSSS Working Paper #155



While probabilistic projection methods for projecting life expectancy exist, few account for covariates related to life expectancy. Generalized HIV/AIDS epidemics have a large, immediate negative impact on the life expectancy in a country, but this impact can be mitigated
by widespread use of antiretroviral therapy (ART). Thus projection methods for countries with generalized HIV/AIDS epidemics could be improved by accounting for HIV prevalence, the future course of the epidemic and coverage of ART. We propose a method for making
probabilistic projections of life expectancy to 2100 for all countries in the world accounting for HIV prevalence, the future course of the epidemic and its uncertainty, and adult ART coverage. We extend the current Bayesian probabilistic life expectancy projection methods
of Raftery et al. (2013) to account for HIV prevalence and adult ART coverage. We evaluate our method using out-of-sample validation. We fi nd that the proposed method performs better than the method that does not account for HIV prevalence or ART coverage for projections of life expectancy in countries with a generalized epidemic, while projections for countries without an epidemic remain essentially unchanged.

Keywords: Bayesian hierarchical model, probabilistic population projections, generalized HIV epidemic, antiretroviral therapy, demography