Objective: Communities need to identify cost-effective interventions for HIV prevention to optimize limited resources.
Methods: The authors developed a spreadsheet tool using Bernoulli and proportionate change models to estimate the relative cost-effectiveness for 26 HIV prevention interventions including biomedical interventions, structural interventions, and interventions designed to change risk behaviors of individuals. They also conducted sensitivity analyses to assess patterns of the cost-effectiveness across different populations using various assumptions.
Results: The 2 factors most strongly determining the cost-effectiveness of the different interventions were the HIV prevalence of the population at risk and the cost per person reached. In low-prevalence populations (eg, heterosexuals) the most cost-effective interventions were structural interventions (eg, mass media, condom distribution), whereas in high-prevalence populations (eg, men who have sex with men) individually focused interventions to change risk behavior were also relatively cost-effective. Among the most cost-effective interventions overall were showing videos in STD clinics and raising alcohol taxes. School-based HIV prevention programs appeared to be the least cost-effective. Needle exchange and needle deregulation programs were relatively cost-effective only when injection drug users have a high HIV prevalence.
Conclusions: Comparing estimates of the cost-effectiveness of HIV interventions provides insight that can help local communities maximize the impact of their HIV prevention resources.
From the *RAND Corporation, Santa Monica, California; and †Tulane University School of Public Health and Tropical Medicine, New Orleans, LA.
Received for publication May 23, 2003;
accepted February 6, 2004.
Supported in part by The Center for HIV Identification, Prevention, and Treatment Services (CHIPTS) and the Centers for Diseases Control, PA# 01158; #R18/CCR920939-01.
This work is the sole responsibility of the authors.
Reprints: Deborah A. Cohen, RAND Corporation, 1700 Main Street, Santa Monica, CA 90405 (e-mail: firstname.lastname@example.org).