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

TL;DR

This paper introduces a Bayesian projection method for life expectancy that incorporates HIV prevalence, epidemic dynamics, and ART coverage, improving accuracy for countries affected by HIV/AIDS.

Contribution

It extends existing Bayesian life expectancy models to explicitly include HIV-related covariates, enhancing projections for countries with generalized HIV/AIDS epidemics.

Findings

Improved projection accuracy for HIV-affected countries

No significant change for countries without HIV epidemics

Method outperforms previous models that ignore HIV factors

Abstract

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 find 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.