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

BACKGROUND: Improving the knowledge and understanding of the environmental determinants of malaria vector abundance at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work is aimed at exploring the environmental tenets of human-biting activity in...

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Detalles Bibliográficos
Autores principales: Taconet, Paul, Porciani, Angélique, Soma, Dieudonné Diloma, Mouline, Karine, Simard, Frédéric, Koffi, Alphonsine Amanan, Pennetier, Cedric, Dabiré, Roch Kounbobr, Mangeas, Morgan, Moiroux, Nicolas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243492/
https://www.ncbi.nlm.nih.gov/pubmed/34187546
http://dx.doi.org/10.1186/s13071-021-04851-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243492/
https://www.ncbi.nlm.nih.gov/pubmed/34187546
http://dx.doi.org/10.1186/s13071-021-04851-x

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