Applying next-generation sequencing to track falciparum malaria in sub-Saharan Africa

Abstract

Next-generation sequencing (NGS) technologies are increasingly being used to address a diverse range of biological and epidemiological questions. The current understanding of malaria transmission dynamics and parasite movement mainly relies on the analyses of epidemiologic data, e.g. case counts and self-reported travel history data. However, travel history data are often not routinely collected or are incomplete, lacking the necessary level of accuracy. Although genetic data from routinely collected field samples provides an unprecedented opportunity to track the spread of malaria parasites, it remains an underutilized resource for surveillance due to lack of local awareness and capacity, limited access to sensitive laboratory methods and associated computational tools and difficulty in interpreting genetic epidemiology data. In this review, the potential roles of NGS in better understanding of transmission patterns, accurately tracking parasite movement and addressing the emerging challenges of imported malaria in low transmission settings of sub-Saharan Africa are discussed. Furthermore, this review highlights the insights gained from malaria genomic research and challenges associated with integrating malaria genomics into existing surveillance tools to inform control and elimination strategies.

Keywords: Malaria genomics; Molecular epidemiology; Next-generation sequencing; Tracking parasites.

Fig. 1

Variation in malaria transmission intensity in 45 sub-Saharan Africa countries (data from) (a). Distribution of malaria incidence in 2017. b Temporal change in the incidence of malaria in low (incidence 0–50 per 1000 population at risk), medium (incidence 50–100) and high (incidence > 100) transmission countries of SSA. Data source: http://apps.who.int/gho/data/node.imr.SDGMALARIA?lang=en

Fig. 2

Challenges and key priorities of genomic epidemiology in sub-Saharan Africa