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A Bayesian Monte Carlo approach for predicting the spread of infectious diseases
In this paper, a simple yet interpretable, probabilistic model is proposed for the prediction of reported case counts of infectious diseases. A spatio-temporal kernel is derived from training data to capture the typical interaction effects of reported infections across time and space, which provides...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Public Library of Science
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6919583/ https://www.ncbi.nlm.nih.gov/pubmed/31851680 http://dx.doi.org/10.1371/journal.pone.0225838 |