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Predicting the distribution of urinary schistosomiasis in Tanzania using satellite sensor data
In this paper, remotely sensed (RS) satellite sensor environmental data, using logistic regression, are used to develop prediction maps of the probability of having infection prevalence exceeding 50%, and warranting mass treatment according to World Health Organization (WHO) guidelines. The model wa...
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| Main Authors: | , , , , , , , , |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2001
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3166845/ https://ncbi.nlm.nih.gov/pubmed/11737837 |
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