GeoHealth Dynamics Research Lab (GeoHDR Lab)
GeoHealth Dynamics Research Lab (GeoHDR Lab)
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  • Home
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    • Geospatial & Genomics
    • AI & GeoHealth
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Geospatial & Genomics

Malaria parasites migration simulation

Understanding the genetic structure of natural populations provides insight into the demographic and adaptive processes that have affected those populations. Such information, particularly when integrated with geospatial data, can have translational applications for a variety of fields, including public health. In this study, we developed a workflow to optimize the resolution of spatial grids used to generate EEMS migration maps and applied this optimized workflow to estimate migration of Plasmodium falciparum in Cambodia and bordering regions of Thailand and Vietnam.



Related publications:
1. Yao Li, Amol C. Shetty, Chanthap Lon, Michele Spring, David L. Saunders, Mark M. Fukuda, Tran Tinh Hien et al. "Detecting geospatial patterns of Plasmodium falciparum parasite migration in Cambodia using optimized estimated effective migration surfaces." International Journal of Health Geographics 19, no. 1 (2020): 1-11.

2. Shetty, Amol C., Christopher G. Jacob, Fang Huang, Yao Li, Sonia Agrawal, David L. Saunders, Chanthap Lon et al. "Genomic structure and diversity of Plasmodium falciparum in Southeast Asia reveal recent parasite migration patterns." Nature communications 10, no. 1 (2019): 1-11.


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Department of Earth, Environmental and Geographical Sciences

University of North Carolina at Charlotte



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