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\begin{document}

\title{Implementing landscape genetics in molecular epidemiology to determine
drivers of vector-borne disease: A malaria case study}



\author[1]{Alfred Hubbard}%
\author[2]{Elizabeth Hemming-Schroeder}%
\author[3]{Yaw Afrane}%
\author[4]{Guiyun Yan}%
\author[1]{Eugenia Lo}%
\author[1]{Daniel Janies}%
\affil[1]{The University of North Carolina at Charlotte}%
\affil[2]{Colorado State University}%
\affil[3]{University of Ghana Medical School}%
\affil[4]{University of California Irvine}%


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  \date{May 15, 2024}


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\begin{abstract}
This study employs landscape genetics to investigate the environmental
drivers of a deadly vector-borne disease, malaria caused by Plasmodium
falciparum, in a more spatially comprehensive manner than any previous
work. With 1,804 samples from 44 sites collected in western Kenya in
2012 and 2013, we performed resistance surface analysis to show that
Lake Victoria acts as a barrier to transmission between areas north and
south of the Winam Gulf. In addition, Mantel correlograms clearly showed
significant correlations between genetic and geographic distance over
short distances (\textless{} 70 km). In both cases, we used an
identity-by-state measure of relatedness tailored to highly-related
individuals in order to focus on recent gene flow that is more relevant
to transmission. To supplement these results, we also performed
conventional population genetics analyses, including Bayesian clustering
methods and spatial ordination techniques. These revealed some
differentiation on the basis of geography and elevation and a cluster of
genetic similarity in the lowlands north of the Winam Gulf of Lake
Victoria. Taken as a whole, these results indicate low overall genetic
differentiation in the Lake Victoria region, but with some separation of
populations north and south of the Winam Gulf that is explained by the
presence of the lake as a geographic barrier to gene flow. We recommend
similar landscape genetics analyses in future molecular epidemiology
studies of vector-borne diseases to extend and contextualize the results
of traditional population genetics.%
\end{abstract}%



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