Preventing HIV transmission via HIV exposure laws: applying logic and mathematical modeling to compare statutory approaches to penalizing undisclosed exposure to HIV. J Law Med Ethics 2008;36(3):577-84
Date
10/09/2008Pubmed ID
18840251Pubmed Central ID
PMC2603033DOI
10.1111/j.1748-720X.2008.306.xScopus ID
2-s2.0-50249134864 (requires institutional sign-in at Scopus site) 17 CitationsAbstract
Twenty-four U.S. states have enacted HIV exposure laws that prohibit HIV-positive persons from engaging in sexual activities with partners to whom they have not disclosed their HIV status. There is little standardization among existing HIV exposure laws, which vary substantially with respect to the sexual activities that are prohibited without prior serostatus disclosure. Logical analysis and mathematical modeling were used to explore the HIV prevention effectiveness of two types of HIV exposure laws: "strict" laws that require HIV-positive persons to disclose their serostatus to prospective partners prior to any sexual activity and "flexible" laws that require seropositive status disclosure only prior to high-risk sex (e.g., unprotected anal or vaginal intercourse). These laws were compared relative to each other and to a no-law alternative. The results of these analyses indicate that, under most (though not necessarily all) circumstances, both strict and flexible exposure laws can be expected to reduce HIV transmission risk relative to the no-law alternative, with flexible exposure laws producing the greater reduction in risk. This study demonstrates how logical analysis and mathematical modeling techniques can make an important contribution to the construction of a rational basis for decisions about a highly contested public health policy issue.
Author List
Galletly CL, Pinkerton SDAuthor
Carol L. Galletly JD, PhD Associate Professor in the Psychiatry and Behavioral Medicine department at Medical College of WisconsinMESH terms used to index this publication - Major topics in bold
CrimeDisclosure
Female
HIV Infections
Humans
Male
Models, Theoretical
Risk Reduction Behavior
Sexual Behavior
United States