Betting on the fastest horse: Using computer simulation to design a combination HIV intervention for future projects in Maharashtra, India

Kelly V Ruggles, Anik R Patel, Stephen Schensul, Jean Schensul, Kimberly Nucifora, Qinlian Zhou, Kendall Bryant and R Scott Braithwaite

PLOS ONE, 2017, vol. 12, issue 9, 1-19

Abstract: Objective: To inform the design of a combination intervention strategy targeting HIV-infected unhealthy alcohol users in Maharashtra, India, that could be tested in future randomized control trials. Methods: Using probabilistic compartmental simulation modeling we compared intervention strategies targeting HIV-infected unhealthy alcohol users on antiretroviral therapy (ART) in Maharashtra, India. We tested interventions targeting four behaviors (unhealthy alcohol consumption, risky sexual behavior, depression and antiretroviral adherence), in three formats (individual, group based, community) and two durations (shorter versus longer). A total of 5,386 possible intervention combinations were tested across the population for a 20-year time horizon and intervention bundles were narrowed down based on incremental cost-effectiveness analysis using a two-step probabilistic uncertainty analysis approach. Results: Taking into account uncertainty in transmission variables and intervention cost and effectiveness values, we were able to reduce the number of possible intervention combinations to be used in a randomized control trial from over 5,000 to less than 5. The most robust intervention bundle identified was a combination of three interventions: long individual alcohol counseling; weekly Short Message Service (SMS) adherence counseling; and brief sex risk group counseling. Conclusions: In addition to guiding policy design, simulation modeling of HIV transmission can be used as a preparatory step to trial design, offering a method for intervention pre-selection at a reduced cost.

Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0184179

DOI: 10.1371/journal.pone.0184179

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