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A hierarchical spatio-temporal model to analyze relative risk variations of COVID-19: a focus on Spain, Italy and Germany.
Jalilian, Abdollah; Mateu, Jorge.
  • Jalilian A; Department of Statistics, Razi University, Kermanshah, 67149-67346 Iran.
  • Mateu J; Universitat Jaume I, Castellón, Spain.
Stoch Environ Res Risk Assess ; 35(4): 797-812, 2021.
Article in English | MEDLINE | ID: covidwho-1148894
ABSTRACT
The novel coronavirus disease (COVID-19) has spread rapidly across the world in a short period of time and with a heterogeneous pattern. Understanding the underlying temporal and spatial dynamics in the spread of COVID-19 can result in informed and timely public health policies. In this paper, we use a spatio-temporal stochastic model to explain the temporal and spatial variations in the daily number of new confirmed cases in Spain, Italy and Germany from late February 2020 to mid January 2021. Using a hierarchical Bayesian framework, we found that the temporal trends of the epidemic in the three countries rapidly reached their peaks and slowly started to decline at the beginning of April and then increased and reached their second maximum in the middle of November. However decline and increase of the temporal trend seems to show different patterns in Spain, Italy and Germany.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Etiology study / Risk factors Language: English Journal: Stoch Environ Res Risk Assess Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Etiology study / Risk factors Language: English Journal: Stoch Environ Res Risk Assess Year: 2021 Document Type: Article