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A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates
The COVID-19 epidemic has raised major issues with regard to modelling and forecasting outcomes such as cases, deaths and hospitalisations. In particular, the forecasting of area-specific counts of infectious disease poses problems when counts are changing rapidly and there are infection hotspots, a...
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Springer Berlin Heidelberg
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9039004/ https://www.ncbi.nlm.nih.gov/pubmed/35496370 http://dx.doi.org/10.1007/s10109-021-00366-2 |