Faculty Collaboration Database

Economic implications of failure to reduce incident HIV infections by 50% by 2005 in the United States. J Acquir Immune Defic Syndr 2003 Jun 01;33(2):171-4

Date

06/10/2003

Pubmed ID

12794550

DOI

10.1097/00126334-200306010-00009

Scopus ID

2-s2.0-0038078716 (requires institutional sign-in at Scopus site)   11 Citations

Abstract

BACKGROUND: The Centers for Disease Control and Prevention have set a national goal of reducing new HIV infections by 50% by 2005 in the United States. There are no available published estimates of the economic consequences of failure to meet this national goal, however.

OBJECTIVES: The purpose of this article is to calculate the potential net economic implications of a failure to meet the national HIV prevention goal of reducing new HIV infections by 50% by 2005.

METHODS: Standard methods of cost-effectiveness analysis were used to determine 1) the excess number of HIV infections incurred if the goal is not met and 2) the excess net medical costs (without the cost of an expanded HIV prevention program in the United States) incurred if the goal is not achieved.

RESULTS: Base case results indicate that if the goal is not met, 130,000 excess HIV infections will occur between the present and 2010 and that the excess net medical costs incurred will total over $18 billion during the same time frame. Sensitivity analyses indicate that although changes in some parameter values do alter the quantitative results, none alter the basic qualitative finding that even dramatically expanded HIV prevention efforts that reduce new HIV infections by 50% are actually cost saving to society.

CONCLUSIONS: The human and fiscal stakes of meeting the CDC's national HIV prevention goal of reducing new infections by 50% by 2005 are sufficiently large to make the achievement of this goal an urgent public health priority.

Author List

Holtgrave DR, Pinkerton SD

MESH terms used to index this publication - Major topics in bold

Costs and Cost Analysis
Forecasting
HIV Infections
Humans
Incidence
Models, Econometric
Time Factors
United States