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A joint Bayesian spatiotemporal risk prediction model of COVID-19 incidence, IC admission, and death with application to Sweden
Faculty of Spatial Sciences, University of Groningen, Groningen, Netherlands.ORCID iD: 0000-0003-1391-4138
Faculty of Spatial Sciences, University of Groningen, Groningen, Netherlands; Statistics Department, Padjadjaran University, Bandung, Indonesia.
Umeå University, Faculty of Social Sciences, Centre for Regional Science (CERUM).ORCID iD: 0000-0002-7905-1825
2022 (English)In: The annals of regional science, ISSN 0570-1864, E-ISSN 1432-0592Article in journal (Refereed) Epub ahead of print
Abstract [en]

The three closely related COVID-19 outcomes of incidence, intensive care (IC) admission and death, are commonly modelled separately leading to biased estimation of the parameters and relatively poor forecasts. This paper presents a joint spatiotemporal model of the three outcomes based on weekly data that is used for risk prediction and identification of hotspots. The paper applies a pure spatiotemporal model consisting of structured and unstructured spatial and temporal effects and their interaction capturing the effects of the unobserved covariates. The pure spatiotemporal model limits the data requirements to the three outcomes and the population at risk per spatiotemporal unit. The empirical study for the 21 Swedish regions for the period 1 January 2020–4 May 2021 confirms that the joint model predictions outperform the separate model predictions. The fifteen-week-ahead spatiotemporal forecasts (5 May–11 August 2021) show a significant decline in the relative risk of COVID-19 incidence, IC admission, death and number of hotspots.

Place, publisher, year, edition, pages
Springer, 2022.
National Category
Probability Theory and Statistics Economics
Research subject
Statistics
Identifiers
URN: urn:nbn:se:umu:diva-201307DOI: 10.1007/s00168-022-01191-1ISI: 000889414600002PubMedID: 36465998Scopus ID: 2-s2.0-85142866490OAI: oai:DiVA.org:umu-201307DiVA, id: diva2:1714224
Funder
Public Health Agency of Sweden Available from: 2022-11-29 Created: 2022-11-29 Last updated: 2023-09-05

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Lundberg, Johan

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