| Abstract: | To study the effects of malaria-control interventions on parasite population genomics, we examined a set of 1,007 samples of the malaria parasite Plasmodium falciparum collected in Thiès, Senegal between 2006 and 2013. The parasite samples were genotyped using a molecular barcode of 24 SNPs. About 35% of the samples grouped into subsets with identical barcodes, varying in size by year and sometimes persisting across years. The barcodes also formed networks of related groups. Analysis of 164 completely sequenced parasites revealed extensive sharing of genomic regions. In at least two cases we found first-generation recombinant offspring of parents whose genomes are similar or identical to genomes also present in the sample. An epidemiological model that tracks parasite genotypes can reproduce the observed pattern of barcode subsets. Quantification of likelihoods in the model strongly suggests a reduction of transmission from 2006–2010 with a significant rebound in 2012–2013. The reduced transmission and rebound were confirmed directly by incidence data from Thiès. These findings imply that intensive intervention to control malaria results in rapid and dramatic changes in parasite population genomics. The results also suggest that genomics combined with epidemiological modeling may afford prompt, continuous, and cost-effective tracking of progress toward malaria elimination.Intensive intervention to reduce the burden of malaria has proven successful in a number of countries in Africa (1). In certain regions of Senegal, implementation of a redesigned National Malaria Control Program (NMCP) in 2006 that included rapid diagnostic tests, artemisinin combination therapies, enhanced insecticide-treated bed nets, and indoor residual spraying resulted in a more than 95% decrease in the number of confirmed cases by 2009 (2). We had been collecting parasite samples in one of these regions annually since 2006. These samples afford a unique opportunity to determine the extent to which intensive intervention is manifested in genetic changes in the parasite population. Genetic changes would be expected to include bottlenecks in the parasite population size, increased random genetic drift, reduced genetic variation, greater self-fertilization during transmission, and increased allele sharing and identity by descent.A key question for tracking malaria elimination is whether such genomic changes would be large enough to be detected in a cost-effective manner in samples of reasonable size. If changes in parasite population genomics took place rapidly enough after intervention, and if they were large enough to be detected, then parasite genomics could play an important role in malaria elimination. Given sufficiently rapid onset and detectability of changes in parasite genomics, an epidemiological model that incorporates parasite genotypes could in principle be used to estimate the epidemiological parameters that most closely match the genomic observations. Estimates of epidemiological parameters such as transmission intensity would aid in understanding the disease situation on the ground, so that the efficacy of intervention strategies could be evaluated in real time and adjustments made as necessary. This approach could prove especially useful in regions of low transmission where classical epidemiological approaches can be applied only with great difficulty and in regions that are not easily or safely accessed by personnel committed to malaria control.In this paper, we show that data from a barcode of 24 SNPs in longitudinal samples from Thiès, Senegal over an 8-y period of moderate numbers of samples (100–200 samples/y) reveals rapid and easily detectable signals of changes in parasite population genomics following enhanced intervention. Moreover, an epidemiological model that incorporates parasite genotypes can reproduce the observed barcode patterns. Estimates of epidemiological parameters in the transmission model using likelihoods strongly suggest a reduction of transmission from 2006–2010 with a significant rebound in 2012–2013. The decrease in transmission of malaria in 2006–2010 after enhanced intervention followed by a rebound in 2012–2013 was confirmed directly by incidence data from Thiès. Our findings suggest that genomics combined with epidemiological modeling may afford rapid, continuous, and cost-effective tracking of progress toward malaria elimination. |
