Sampling for malaria molecular surveillance

Evidence generated from malaria molecular surveillance (MMS) can inform decision making by malaria control programs, that is, early detection of genetic variants that confer partial resistance to malaria therapy drugs (pfkeltch13), identifying transmission sources, and characterizing malaria transmission dynamics.Clear and accessible guidance for appropriately designing and powering MMS use-cases does not yet exist.Designing MMS and studies for each use-case requires defining the target population, the sampling technique, the sampling period and frequency, and the appropriate sample size required to draw valid and unbiassed conclusions.Sample size calculations require defining assumptions about the expected prevalence of the outcome of interest, its heterogeneity in the population, the desired confidence, and the design effect in cluster-based sampling. Strategic use of Plasmodium falciparum genetic variation has great potential to inform public health actions for malaria control and elimination. Malaria molecular surveillance (MMS) begins with a strategy to identify and collect parasite samples, guided by public-health priorities. In this review we discuss sampling design practices for MMS and point out epidemiological, biological, and statistical factors that need to be considered. We present examples for different use cases, including detecting emergence and spread of rare variants, establishing transmission sources and inferring changes in malaria transmission intensity. This review will potentially guide the collection of samples and data, serve as a starting point for further methodological innovation, and enhance utilization of MMS to support malaria elimination. Strategic use of Plasmodium falciparum genetic variation has great potential to inform public health actions for malaria control and elimination. Malaria molecular surveillance (MMS) begins with a strategy to identify and collect parasite samples, guided by public-health priorities. In this review we discuss sampling design practices for MMS and point out epidemiological, biological, and statistical factors that need to be considered. We present examples for different use cases, including detecting emergence and spread of rare variants, establishing transmission sources and inferring in malaria transmission intensity. This review will potentially guide the collection of samples and data, serve as a starting point for further methodological innovation, and enhance utilization of MMS to suppo