EconPapers    
Economics at your fingertips  
 

Prioritizing Hepatitis C Treatment in U.S. Prisons

Turgay Ayer (), Can Zhang (), Anthony Bonifonte (), Anne C. Spaulding () and Jagpreet Chhatwal ()
Additional contact information
Turgay Ayer: H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia 30318
Can Zhang: Fuqua School of Business, Duke University, Durham, North Carolina 27708
Anthony Bonifonte: Data Analytics Program, Denison University, Granville, Ohio 43023
Anne C. Spaulding: Rollins School of Public Health, Emory University, Atlanta, Georgia 30322
Jagpreet Chhatwal: Massachusetts General Hospital Institute for Technology Assessment, Harvard Medical School, Boston, Massachusetts 02114

Operations Research, 2019, vol. 67, issue 3, 853-873

Abstract: Hepatitis C virus (HCV) prevalence in prison systems is about 10 times higher than in the community. As such, prison systems offer a unique opportunity to control the HCV epidemic. New HCV-treatment drugs are very effective, but providing treatment to all inmates is prohibitively expensive unless prices fall. Current practice is to prioritize treatment based on disease severity and puts less emphasis on other factors such as the remaining sentence length and injection drug use behavior. In “Prioritizing Hepatitis C Treatment in U.S. Prisons,” T. Ayer, C. Zhang, A. Bonifonte, A. Spaulding, and J. Chhatwal analyze optimal approaches for treatment prioritization under resource constraints by developing a restless bandit modeling framework. They present an easy-to-implement closed-form index policy to support hepatitis C treatment prioritization decisions in U.S. prisons. They also test their proposed policy using a detailed, realistic agent-based simulation model and shed light on several controversial health policy decisions related to hepatitis C treatment prioritization.

Keywords: public health; hepatitis C; resource allocation; treatment prioritization; multi-armed bandits; agent-based simulation (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
https://doi.org/10.1287/opre.2018.1812 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:inm:oropre:v:67:y:2019:i:3:p:853-873

Access Statistics for this article

More articles in Operations Research from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().

 
Page updated 2025-03-19
Handle: RePEc:inm:oropre:v:67:y:2019:i:3:p:853-873