How do epidemics induce behavioral changes?

Presented at GLOBELICS 2009, 7th International Conference, 6-8 October, Dakar, Senegal.Parallel session 2: Population, health and growthThis paper develops a theory of optimal fertility behavior under mortality shocks. In an OLG model, young adults determine their optimal fertility, labor supply and life-cycle consumption with both exogenous child and adult mortality risks. We show that a rise in adult mortality exerts an ambiguous effect on both net and total fertility in a general equilibrium framework, while child mortality shocks unambiguously lead to a rise in total fertility, leaving net fertility unchanged. We complement our theory with an empirical analysis using a sample of 39 Sub-Saharan African (SSA) countries over the 1980-2004 period, examining the overall effects of the child and adult mortality channels on both total and net fertility. We find child mortality to exert a robust, positive impact on total fertility but no impact on net fertility, whereas a rise in adult mortality is found to negatively influence both total and net fertility. Given the particular demographic profile of the HIV/AIDS epidemic (killing essentially young, active adults), we then conclude in favor of an unambiguous negative effect of the HIV/AIDS epidemic on net fertility in SS

Hiv treatment as prevention: Models, data, and questions-towards evidence-based decision-making

textabstractAntiretroviral therapy (ART) for those infected with HIV can prevent onward transmission of infection, but biological efficacy alone is not enough to guide policy decisions about the role of ART in reducing HIV incidence. Epidemiology, economics, demography, statistics, biology, and mathematical modelling will be central in framing key decisions in the optimal use of ART. PLoS Medicine, with the HIV Modelling Consortium, has commissioned a set of articles that examine different aspects of HIV treatment as prevention with a forward-looking research agenda. Interlocking themes across these articles are discussed in this introduction. We hope that this article, and others in the collection, will provide a foundation upon which greater collaborations between disciplines will be formed, and will afford deeper insights into the key factors involved, to help strengthen the support for evidence-based decision-making in HIV prevention