A machine learning approach to integrating genetic and ecological data in tsetse flies (Glossina pallidipes) for spatially explicit vector control planning

A machine learning approach to integrating genetic and ecological data in tsetse flies (Glossina pallidipes) for spatially explicit vector control planning

Abstract Vector control is an effective strategy for reducing vector‐borne disease transmission, but requires knowledge of vector habitat use and dispersal patterns. Our goal was to improve this knowledge for the tsetse species Glossina pallidipes, a vector of human and animal African trypanosomiasi...

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Bibliographic Details
Main Authors: Anusha P. Bishop, Giuseppe Amatulli, Chaz Hyseni, Evlyn Pless, Rosemary Bateta, Winnie A. Okeyo, Paul O. Mireji, Sylvance Okoth, Imna Malele, Grace Murilla, Serap Aksoy, Adalgisa Caccone, Norah P. Saarman
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:Evolutionary Applications
Subjects:
disease vector
gene flow
habitat suitability
landscape genetics
random forest
spatial modeling
Online Access:https://doi.org/10.1111/eva.13237

Internet

https://doi.org/10.1111/eva.13237

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