dc.contributor.author | Alaimo Di Loro, Pierfrancesco | |
dc.contributor.author | Divino, Fabio | |
dc.contributor.author | Farcomeni, Alessio | |
dc.contributor.author | Jona Lasinio, Giovanna | |
dc.contributor.author | Lovison, Gianfranco | |
dc.contributor.author | Maruotti, Antonello | |
dc.contributor.author | Mingione, Marco | |
dc.date.accessioned | 2022-04-28T12:11:39Z | |
dc.date.available | 2022-04-28T12:11:39Z | |
dc.date.created | 2022-01-16T16:56:07Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 0277-6715 | |
dc.identifier.uri | https://hdl.handle.net/11250/2993216 | |
dc.description.abstract | 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. Parameter estimation is carried out in a maximum likelihood framework. All computational details required to reproduce the approach and replicate the results are provided. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | Wiley | en_US |
dc.rights | Navngivelse 4.0 Internasjonal | * |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/deed.no | * |
dc.title | Nowcasting COVID-19 incidence indicators during the Italian first outbreak | en_US |
dc.type | Journal article | en_US |
dc.type | Peer reviewed | en_US |
dc.description.version | publishedVersion | en_US |
dc.rights.holder | Copyright 2021 The Author(s) | en_US |
cristin.ispublished | true | |
cristin.fulltext | original | |
cristin.qualitycode | 2 | |
dc.identifier.doi | 10.1002/sim.9004 | |
dc.identifier.cristin | 1982022 | |
dc.source.journal | Statistics in Medicine | en_US |
dc.source.pagenumber | 3843-3864 | en_US |
dc.identifier.citation | Statistics in Medicine. 2021, 40 (16), 3843-3864. | en_US |
dc.source.volume | 40 | en_US |
dc.source.issue | 16 | en_US |