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Preventing HIV Transmission via HIV Exposure Laws: Applying Logic and Mathematical Modeling to Compare Statutory Approaches to Penalizing Undisclosed Exposure to HIV

Overview of attention for article published in The Journal of Law, Medicine & Ethics, January 2021
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Title
Preventing HIV Transmission via HIV Exposure Laws: Applying Logic and Mathematical Modeling to Compare Statutory Approaches to Penalizing Undisclosed Exposure to HIV
Published in
The Journal of Law, Medicine & Ethics, January 2021
DOI 10.1111/j.1748-720x.2008.306.x
Pubmed ID
Authors

Carol L. Galletly, Steven D. Pinkerton

Abstract

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.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 6%
Switzerland 1 6%
Unknown 14 88%

Demographic breakdown

Readers by professional status Count As %
Other 2 13%
Researcher 2 13%
Student > Master 2 13%
Lecturer > Senior Lecturer 1 6%
Professor 1 6%
Other 3 19%
Unknown 5 31%
Readers by discipline Count As %
Medicine and Dentistry 6 38%
Social Sciences 2 13%
Agricultural and Biological Sciences 1 6%
Environmental Science 1 6%
Nursing and Health Professions 1 6%
Other 1 6%
Unknown 4 25%