Dynamics of Drug Resistance: Optimal Control of an Infectious Disease

Naveed Chehrazi (), Lauren E. Cipriano () and Eva A. Enns ()
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Naveed Chehrazi: Department of Information, Risk, and Operations Management, McCombs School of Business, The University of Texas at Austin, Austin, Texas 78705
Lauren E. Cipriano: Ivey Business School, Western University, London, Ontario N6G 0N1, Canada
Eva A. Enns: Division of Health Policy & Management, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455

Operations Research, 2019, vol. 67, issue 3, 619-650

Abstract: Antimicrobial use contributes to the growing public health challenge of infectious diseases that are resistant to all but a few remaining treatments via natural selection. When few treatment options remain, should the last effective treatment be reserved for controlling larger outbreaks in the future? In “Dynamics of Drug Resistance: Optimal Control of an Infectious Disease,” N. Chehrazi, L. E. Cipriano, and E. A. Enns formulate this important policy question as a control problem with two state variables—disease prevalence and the level of treatment resistance—for an established family of SIS infectious disease models with resistance. They prove that when the disease transmission rate is constant, it is optimal to treat everyone until the level of resistance is so high that it is no longer economical to treat anyone. Public health policies and social distancing can cause a nonconstant disease transmission rate; in these cases, it may be optimal to preserve the drug for relatively larger outbreaks or to use the drug to treat some, but not all, infected individuals.

Keywords: optimal control; antimicrobial resistance; healthcare management; infectious disease models; dynamic health policy (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)

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