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...

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Detalles Bibliográficos
Autores principales: Galasso, Joseph, Cao, Duy M., Hochberg, Robert
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2022
Materias:
Article
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

Internet

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

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