Yale University

Public Health Impact and Cost-Effectiveness of HIV Interventions

Principle Investigator(s):

Funder: National Institute on Drug Abuse
Project period: 06/15/1996 - 08/31/2002
Grant Type: Research
Further Detail

Abstract Text:

This study aims to promote reasoned decision making in the realm of AIDS and drug-abuse prevention policy. We propose to develop and apply mathematical and economic models to evaluate interventions and thereby to inform the allocation of scarce resources. The proposed research ranges from methods development to applied policy analysis Our methodological aims are to produce formal, model-based characterizations of the relationship between resource expenditures and their impact on program performance measures of interest to decision makers: the goal is to determine what society gets for its AIDS prevention dollar. We will: 1) construct production functions that characterize the relationship between money spent to modify risky behaviors and the behavior change that results; 2) develop model-based methods for translating the behavioral impact of HIV-related interventions into epidemiologically meaningful outcome measures; 3) attach policy outcome measures (such as economic cost, public health impact, and cost-effectiveness) to models of HIV intervention programs. Our applied objectives build on this methodological foundation. These are: 4) to assess the impact and cost-effectiveness of specific interventions to prevent HIV and 5) to guide the process of resource allocation among competing prevention strategies. Our final objective is: 6) to explore the interface between formal analysis and the policy process. Specifically, we will examine how AIDS and drug-abuse policy makers understand and manage analytic information and presentation of findings. Working with policy makers, we will develop evaluation frameworks and reporting formats that can best be incorporated into the policy process. Our methods fall into three categories (a) Data analysis. We will analyze and synthesize extensive data on HIV risk behaviors, epidemic factors, and health and economic outcomes. Data will underlie each aim, assuring realistic representation of geographic settings, risk groups, and interventions. (b) Mathematical modeling. We will develop epidemic models to describe current conditions and to assess the impact of interventions. We will balance detailed portrayal of the epidemic with a focus on policy choices. (c) Collaboration with policy makers. We will obtain the regular input of individuals involved in decision making, to maximize the value of our analyses to policy issues.

Outcome(s):