The Value of Information in Decision‐Analytic Modeling for Malaria Vector Control in East Africa |
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| Authors: | Dohyeong Kim Zachary Brown Richard Anderson Clifford Mutero Marie Lynn Miranda Jonathan Wiener Randall Kramer |
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| Affiliation: | 1. School of Economic, Political and Policy Sciences, The University of Texas at Dallas, TX, USA;2. Department of Agricultural and Resource Economics and Genetic Engineering and Society Center, North Carolina State University, NC, USA;3. Puget Sound Institute, University of Washington, WA, USA;4. University of Pretoria, Pretoria, South Africa;5. International Centre of Insect Physiology and Ecology, Nairobi, Kenya;6. Children's Environmental Health Initiative, Rice University, TX, USA;7. Duke University Law School and Sanford School of Public Policy, Duke University, NC, USA;8. Nicholas School of the Environment and Duke Global Health Institute, Duke University, NC, USA |
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| Abstract: | Decision analysis tools and mathematical modeling are increasingly emphasized in malaria control programs worldwide to improve resource allocation and address ongoing challenges with sustainability. However, such tools require substantial scientific evidence, which is costly to acquire. The value of information (VOI) has been proposed as a metric for gauging the value of reduced model uncertainty. We apply this concept to an evidenced‐based Malaria Decision Analysis Support Tool (MDAST) designed for application in East Africa. In developing MDAST, substantial gaps in the scientific evidence base were identified regarding insecticide resistance in malaria vector control and the effectiveness of alternative mosquito control approaches, including larviciding. We identify four entomological parameters in the model (two for insecticide resistance and two for larviciding) that involve high levels of uncertainty and to which outputs in MDAST are sensitive. We estimate and compare a VOI for combinations of these parameters in evaluating three policy alternatives relative to a status quo policy. We find having perfect information on the uncertain parameters could improve program net benefits by up to 5–21%, with the highest VOI associated with jointly eliminating uncertainty about reproductive speed of malaria‐transmitting mosquitoes and initial efficacy of larviciding at reducing the emergence of new adult mosquitoes. Future research on parameter uncertainty in decision analysis of malaria control policy should investigate the VOI with respect to other aspects of malaria transmission (such as antimalarial resistance), the costs of reducing uncertainty in these parameters, and the extent to which imperfect information about these parameters can improve payoffs. |
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| Keywords: | Decision analysis malaria control value of information |
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