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A random forest model for forecasting regional COVID-19 cases utilizing reproduction number estimates and demographic data
During the COVID-19 pandemic, predicting case spikes at the local level is important for a precise, targeted public health response and is generally done with compartmental models. The performance of compartmental models is highly dependent on the accuracy of their assumptions about disease dynamics...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier Ltd.
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8731233/ https://www.ncbi.nlm.nih.gov/pubmed/35013654 http://dx.doi.org/10.1016/j.chaos.2021.111779 |