Sampling for malaria molecular surveillance

Abstract

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.

Keywords: antimalarial drug resistance; genomics; malaria; malaria transmission; molecular surveillance; sampling.

Figure 1

Steps for designing a malaria molecular surveillance (MMS) approach. To draw valid conclusions from MMS efforts, it is key to carefully decide how to select a sample that is representative of the target population. The surveillance purpose, and therefore the programmatic action expected from those efforts, will inform the relevant population to be sampled (which should be driven by the intervention target), the sampling method and the periodicity. All these parameters, which should be specific to the pre-defined population of interest as well as reflective of the logistical and biological sources of bias at the time of sampling, together with assumptions about the distribution of the marker of interest in the study population, need to be considered to calculate the appropriate sample size. Here we exemplify the different steps for three specific surveillance objectives: the detection of emerging variants of concern (such as mutations in pfkelch13 associated with artemisinin resistance), the classification of cases as local or imported, and the detection of changes in transmission.

Figure I

Factors that determine the ability to detect parasite connectivity.

Figure I

Factors that determine the ability to infer malaria transmission.