Supporting elimination of lymphatic filariasis in Samoa by predicting locations of residual infection using machine learning and geostatistics
Abstract 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...
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
Nature Portfolio
2020
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| Sujets: | |
| Accès en ligne: | https://doaj.org/article/cb04387885e54caa9663c31ec57feff6 |
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