De Novo Mutations Resolve Disease Transmission Pathways in Clonal Malaria

Malaria has declined significantly in The Gambia and determining transmission dynamics of Plasmodium falciparum can help targeting control interventions towards elimination. This can be inferred from genetic similarity between parasite isolates from different sites and timepoints. Here, we imposed a P. falciparum life cycle time on a genetic distance likelihood model to determine transmission paths from a 54 SNP barcode of 355 isolates. Samples were collected monthly during the 2013 malaria season from six pairs of villages spanning 300 km from western to eastern Gambia. There was spatial and temporal hierarchy in pairwise genetic relatedness, with the most similar barcodes from isolates within the same households and village. Constrained by travel data, the model detected 60 directional transmission events, with 27% paths linking persons from different regions. We identified 13 infected individuals (4.2% of those genotyped) responsible for 2 to 8 subsequent infections within their communities. These super-infectors were mostly from high transmission villages. When considering paths between isolates from the most distant regions (west vs east) and travel history, there were 3 transmission paths from eastern to western Gambia, all at the peak (October) of the malaria transmission season. No paths with known travel originated from the extreme west to east. Although more than half of all paths were within-village, parasite flow from east to west may contribute to maintain transmission in western Gambia, where malaria transmission is already low. Therefore, interrupting malaria transmission in western Gambia would require targeting eastern Gambia, where malaria prevalence is substantially higher, with intensified malaria interventions