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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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| Publicado no: | Sci Rep |
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| Main Authors: | , , , , , , , , , |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Publishing Group UK
2020
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7689447/ https://ncbi.nlm.nih.gov/pubmed/33239779 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-77519-8 |
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