Modeling malaria genomics reveals transmission decline and rebound in Senegal.

Proc Natl Acad Sci U S A
Authors
Keywords
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.

Year of Publication
2015
Journal
Proc Natl Acad Sci U S A
Volume
112
Issue
22
Pages
7067-72
Date Published
2015 Jun 02
ISSN
1091-6490
URL
DOI
10.1073/pnas.1505691112
PubMed ID
25941365
PubMed Central ID
PMC4460456
Links
Grant list
AI099105 / AI / NIAID NIH HHS / United States
R01 AI106734 / AI / NIAID NIH HHS / United States
T32 AI049928 / AI / NIAID NIH HHS / United States
U19AI089696 / AI / NIAID NIH HHS / United States
K23 AI072033 / AI / NIAID NIH HHS / United States
R01 AI099105 / AI / NIAID NIH HHS / United States
5D43TW001503 / TW / FIC NIH HHS / United States
K23AI072033 / AI / NIAID NIH HHS / United States
U54 GM088558 / GM / NIGMS NIH HHS / United States
U19 AI089696 / AI / NIAID NIH HHS / United States
U54GM088558 / GM / NIGMS NIH HHS / United States
AI034969 / AI / NIAID NIH HHS / United States
R01 AI034969 / AI / NIAID NIH HHS / United States
D43 TW001503 / TW / FIC NIH HHS / United States
AI106734 / AI / NIAID NIH HHS / United States