| Autor: |
Di Loro, Pierfrancesco Alaimo, Divino, Fabio, Farcomeni, Alessio, Lasinio, Giovanna Jona, Lovison, Gianfranco, Maruotti, Antonello, Mingione, Marco |
| Rok vydání: |
2020 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
A novel parametric regression model is proposed to fit incidence data typically collected during epidemics. The proposal is motivated by real-time monitoring and short-term forecasting of the main epidemiological indicators within the first outbreak of COVID-19 in Italy. Accurate short-term predictions, including the potential effect of exogenous or external variables are provided; this ensures to accurately predict important characteristics of the epidemic (e.g., peak time and height), allowing for a better allocation of health resources over time. Parameters estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided. |
| Databáze: |
arXiv |
| Externí odkaz: |
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