Value of information analysis in decision-analytic modeling for malaria control in africa

The Malaria Decision Analysis Support Tool (MDAST) project employs a comprehensive framework to assess the full range of health, social, and environmental risks and benefits associated with alternative malaria control strategies in order to promote evidence-based, multi-sectoral malaria control policymaking. While more broadly relevant, the tool has been initially tailored for use in Kenya, Tanzania, and Uganda. The tool provides a platform for decision-makers to enter information about the malaria control situation in their country, which is then automatically combined with peer-reviewed scientific research through the underlying MDAST structure, and estimates the potential impacts of proposed malaria control policies. However, substantial information gaps and uncertainties were identified in developing MDAST, especially regarding insecticide resistance, the effectiveness of larvicide alternatives, and baseline vector recruitment. To assess the importance of the information gaps, we: (1) identified areas where influential parameters are missing or involve high levels of uncertainty due to lack of evidence in the literature; (2) determined which parameters are more influential in determining key model results and examined how sensitive the modeling output measures are to each parameter; and (3) estimated a quantitative value of information (VOI). The outcome from these three steps can promote collaboration among researchers and policymakers to prioritize the most policy-relevant malaria research agenda in each country. This research enables MDAST users to invest optimally in the acquisition of new information that will in turn support better choices among malaria control options and improve the implementation of MDAST.