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SIMULATION, Vol. 71, No. 4, 262-275 (1998)
DOI: 10.1177/003754979807100406

Other

The Effects of Protease Inhibitors on the Spread of HIV and the Development of Drug-Resistant HIV Strains: A Simulation Study

Gregory S. Zaric

Department of Industrial Engineering and Engineering Management Stanford University, Stanford, CA

Margaret L. Brandeau

Department of Industrial Engineering and Engineering Management Stanford University, Stanford, CA

Ahmed M. Bayoumi

VA Palo Alto Health Care System, Palo Alto, CA, Division of Infectious Diseases, Wellesley Central Hospital, Toronto, Canada

Douglas K. Owens

VA Palo Alto Health Care System General Internal Medicine, Palo Alto, CA, Departments of Medicine, Health Research and Policy Stanford University, Stanford, CA

Recent advances in the development of protease inhibi tors offer the promise of significantly longer lives for many HIV-infected individuals. However, the drug dosing regimens are often difficult for patients to follow, and non-compliance can enhance the development of drug-resistant strains of HIV. This paper uses com puter simulation to analyze the effects of such "multi- drug therapy" and treatment compliance on the spread of HIV and of multi-drug-resistant HIV strains. The analysis is based on a dynamic compartmental model of the epidemic simulated using Excel, a spreadsheet package. Our analysis shows that multi-drug therapy can lead to significantly high prevalence of multi-drug- resistant HIV strains. Even under optimistic assump tions about rates of compliance and rates at which drug resistance develops, the development of multi-drug- resistant HIV strains in the population may be sig nificant. Our analysis shows that the most important factors affecting the development of multi-drug-resis tant HIV strains are initial and continuing compli ance with treatment. New treatments that are easier to comply with or behavioral interventions that increase patients' compliance could significantly reduce the spread of multi-drug-resistant HIV strains.

Key Words: Biology • operations research • HIV • AIDS • drug-resistant HIV • Excel


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