Supporting elimination of lymphatic filariasis in Samoa by predicting locations of residual infection using machine learning and geostatistics

The global elimination of lymphatic filariasis (LF) is a major focus of the World Health Organization. One key challenge is locating residual infections that can perpetuate the transmission cycle. We show how a targeted sampling strategy using predictions from a geospatial model, combining random fo...

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Detalles Bibliográficos
Autores principales: Mayfield, Helen J., Sturrock, Hugh, Arnold, Benjamin F., Andrade-Pacheco, Ricardo, Kearns, Therese, Graves, Patricia, Naseri, Take, Thomsen, Robert, Gass, Katherine, Lau, Colleen L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689447/
https://www.ncbi.nlm.nih.gov/pubmed/33239779
http://dx.doi.org/10.1038/s41598-020-77519-8

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7689447/
https://www.ncbi.nlm.nih.gov/pubmed/33239779
http://dx.doi.org/10.1038/s41598-020-77519-8

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