Abstract
BACKGROUND: Vector control tools have contributed significantly to a reduction in malaria burden since 2000, primarily through insecticidal-treated bed nets (ITNs) and indoor residual spraying. In the face of increasing insecticide resistance in key malaria vector species, global progress in malaria control has stalled. Innovative tools, such as dual active ingredient (dual-AI) ITNs that are effective at killing insecticide-resistant mosquitoes have recently been introduced. However, large-scale uptake has been slow for several reasons, including higher costs and limited evidence on their incremental effectiveness and cost-effectiveness. The present report describes the design of several observational studies aimed to determine the effectiveness and cost-effectiveness of dual-AI ITNs, compared to standard pyrethroid-only ITNs, at reducing malaria transmission across a variety of transmission settings. METHODS: Observational pilot studies are ongoing in Burkina Faso, Mozambique, Nigeria, and Rwanda, leveraging dual-AI ITN rollouts nested within the 2019 and 2020 mass distribution campaigns in each country. Enhanced surveillance occurring in select study districts include annual cross-sectional surveys during peak transmission seasons, monthly entomological surveillance, passive case detection using routine health facility surveillance systems, and studies on human behaviour and ITN use patterns. Data will compare changes in malaria transmission and disease burden in districts receiving dual-AI ITNs to similar districts receiving standard pyrethroid-only ITNs over three years. The costs of net distribution will be calculated using the provider perspective including financial and economic costs, and a cost-effectiveness analysis will assess incremental cost-effectiveness ratios for Interceptor® G2, Royal Guard®, and piperonyl butoxide ITNs in comparison to standard pyrethroid-only ITNs, based on incidence rate ratios calculated from routine data. CONCLUSIONS: Evidence of the effectiveness and cost-effectiveness of the dual-AI ITNs from these pilot studies will complement evidence from two contemporary cluster randomized control trials, one in Benin and one in Tanzania, to provide key information to malaria control programmes, policymakers, and donors to help guide decision-making and planning for local malaria control and elimination strategies. Understanding the breadth of contexts where these dual-AI ITNs are most effective and collecting robust information on factors influencing comparative effectiveness could improve uptake and availability and help maximize their impact.