Journal
LANCET GLOBAL HEALTH
Volume 4, Issue 7, Pages E474-E484Publisher
ELSEVIER SCI LTD
DOI: 10.1016/S2214-109X(16)30073-0
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Funding
- Bill & Melinda Gates Foundation
- UK Medical Research Council
- UK Medical Research Council (MRC), under the MRC/DFID Concordat agreement
- UK Department for International Development (DFID), under the MRC/DFID Concordat agreement
- National Institute for General Medical Sciences MIDAS initiative
- MRC under the MRC/DFID Concordat agreement
- MRC Centre for Outbreak Analysis and Modelling
- Medical Research Council [MR/L012189/1, G1002284, MR/K010174/1, MR/K010174/1B] Funding Source: researchfish
- MRC [MR/K010174/1, MR/L012189/1, G1002284] Funding Source: UKRI
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Background Reducing the burden of malaria is a global priority, but financial constraints mean that available resources must be allocated rationally to maximise their effect. We aimed to develop a model to estimate the most efficient (ie, minimum cost) ordering of interventions to reduce malaria burden and transmission. We also aimed to estimate the efficiency of different spatial scales of implementation. Methods We combined a dynamic model capturing heterogeneity in malaria transmission across Africa with financial unit cost data for key malaria interventions. We combined estimates of patterns of malaria endemicity, seasonality in rainfall, and mosquito composition to map optimum packages of these interventions across Africa. Using non-linear optimisation methods, we examined how these optimum packages vary when control measures are deployed and assessed at national, subnational first administrative (provincial), or fine-scale (5 km(2) pixel) spatial scales. Findings The most efficient package in a given setting varies depending on whether disease reduction or elimination is the target. Long-lasting insecticide-treated nets are generally the most cost-effective first intervention to achieve either goal, with seasonal malaria chemoprevention or indoor residual spraying added second depending on seasonality and vector species. These interventions are estimated to reduce malaria transmission to less than one case per 1000 people per year in 43.4% (95% CI 40.0-49.0) of the population at risk in Africa. Adding three rounds of mass drug administration per year is estimated to increase this proportion to 90.9% (95% CI 86.9-94.6). Further optimisation can be achieved by targeting policies at the provincial level, achieving an estimated 32.1% (95% CI 29.6-34.5) cost saving relative to adopting country-wide policies. Nevertheless, we predict that only 26 (95% CI 22-29) of 41 countries could reduce transmission to these levels with these approaches. Interpretation These results highlight the cost-benefits of carefully tailoring malaria interventions to the ecological landscape of different areas. However, novel interventions are necessary if malaria eradication is to be achieved.
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