Modeling malaria genomics reveals transmission decline and rebound in Senegal

TLDR

Traditional methods for estimating malaria transmission based on mosquito sampling are not standardized and are unavailable in many sub‑Saharan African countries, making low‑transmission studies difficult and hindering elimination efforts. Genomic analysis in Senegal shows increased allele sharing and genomic identity among parasites, and modeling indicates a decline in transmission from 2006–2010 followed by a rebound in 2012–2013, confirming that genomic approaches can monitor transmission and evaluate intervention effectiveness.

Abstract

Significance Traditional methods for estimating malaria transmission based on mosquito sampling are not standardized and are unavailable in many countries in sub-Saharan Africa. Such studies are especially difficult to implement when transmission is low, and low transmission is the goal of malaria elimination. Malaria-control efforts in Senegal have resulted in changes in population genomics evidenced by increased allele sharing among parasite genomes, often including genomic identity between independently sampled parasites. Fitting an epidemiological model to the observed data indicates falling transmission from 2006–2010 with a significant rebound in 2012–2013, an inference confirmed by incidence data. These results demonstrate that genomic approaches may help monitor transmission to assess initial and ongoing effectiveness of interventions to control malaria.