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The Effects of Government Intervention and Rehabilitation on Prostitution

Undergraduate #91
Discipline: Mathematics and Statistics
Subcategory: Mathematics and Statistics

Zakar White - Virginia Tech
Co-Author(s): David Morrison, Norfolk State University, VA



In the United States, prostitution is considered illegal in all but one state; Nevada allows some legal activities in exchange for substantial guidelines. In 2010, approximately 43,600 females were arrested for prostitution. Numerous intervention programs were established in order to obstruct the lifestyle of a prostitute (PRP, Project ROSE, etc.). There are many documentations and programs that share their forethought on prostitution; however, few target prostitution directly. To determine the dynamics of prostitution, this paper constructs a four-class compartmental model that focuses on the effectiveness of government intervention and rehabilitation of prostitutes mathematically. The basic reproductive number, $mathscr{R}_0$, helps discover the threshold values for the dynamics of prostitution to become both prevalent and absent in a society. This project predominately observes government intervention to curtail a prostitution prevalent society. Various parameters and variables help define and indicate the dynamics of prostitution to construct viable simulations. Successful prostitution interaction prevention deemed essential in prostitution prevention; however, government intervention corresponding with successful rehabilitation competitively challenges prostitution interaction prevention in reducing basic reproductive values. Development of a two-patch compartmental model is considered for future work to examine the dynamics of both male and female prostitution and their interactions.

Funder Acknowledgement(s): Support for this Mathematical Association of America (MAA) program is jointly provided by the National Science Foundation (grant DMS-1359016) and the National Security Administration (grant H98230-15-1-0020)

Faculty Advisor: Aprillya Lanz,

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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