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

HIGHLIGHTS

  • who: Paul Taconet from the MIVEGEC, Université de Montpellier, CNRS, IRD, Montpellier, France have published the research: Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso, in the Journal: (JOURNAL)
  • what: This work is aimed at exploring the environmental tenets of human-biting activity in the main malaria (Anopheles gambiae s.s. To overcome this issue, the authors propose the use of high-resolution Earth observation (EO) data and develop novel statistical modeling approaches. The aim of this study was to . . .

     

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