Plasmodium falciparum genomic surveillance reveals spatial and temporal trends, association of genetic and physical distance, and household clustering

Molecular epidemiology using genomic data can help identify relationships
between malaria parasite population structure, malaria transmission
intensity, and ultimately help generate actionable data to assess the
effectiveness of malaria control strategies. Genomic data, coupled with
geographic information systems data, can further identify clusters or
hotspots of malaria transmission, parasite genetic and spatial
connectivity, and parasite movement by human or mosquito mobility over
time and space.  In this study, we performed longitudinal genomic
surveillance in a cohort of 70 participants over four years from different
neighborhoods and households in Thiès, Senegal—a region of exceptionally
low malaria transmission (entomological inoculation rate (EIR) less than
1). Genetic identity (identity by state) was established using a 24 single
nucleotide polymorphism molecular barcode and a multivariable linear
regression model was used to establish genetic and spatial relationships.
Our results show clustering of genetically similar parasites within
households and a decline in genetic similarity of parasites with
increasing distance.  One household showed extremely high
diversity and warrants further investigation as to the source of these
diverse genetic types. This study illustrates the utility of genomic data
with traditional epidemiological approaches for surveillance and detection
of trends and patterns in malaria transmission not only by neighborhood
but also by household. This approach can be implemented regionally and
countrywide to strengthen and support malaria control and elimination
efforts.