Article

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

2021-04-14

Abstract excerpt

<h4>Background</h4> Improving the knowledge and understanding of the environmental determinants of malaria vectors abundances at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work aimed at exploring the environmental tenets of human-biting activity in the main malaria vectors ( Anopheles gambiae s.s. , Anopheles coluzzi i and Anopheles funestus) in the hea...

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Literature Corpus work: f9ea0920-3801-5234-b622-9135e5f70570
DOI: 10.1101/2021.04.13.439583

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