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Spatially resolved simulations of the spread of COVID-19 in European countries
Andrea Parisi; Samuel P C Brand; Joe Hilton; Rabia Aziza; Matt J Keeling; D. James Nokes.
Affiliation
  • Andrea Parisi; University of Warwick
  • Samuel P C Brand; University of Warwick
  • Joe Hilton; University of Warwick
  • Rabia Aziza; University of Warwick
  • Matt J Keeling; University of Warwick
  • D. James Nokes; Kemri-Wellcome Trust
Preprint in English | medRxiv | ID: ppmedrxiv-20238600
Journal article
A scientific journal published article is available and is probably based on this preprint. It has been identified through a machine matching algorithm, human confirmation is still pending.
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ABSTRACT
We explore the spatial and temporal spread of the novel SARS-CoV-2 virus under containment measures in three European countries based on fits to data of the early outbreak. Using data from Spain and Italy, we estimate an age dependent infection fatality ratio for SARS-CoV-2, as well as risks of hospitalization and intensive care admission. We use them in a model that simulates the dynamics of the virus using an age structured, spatially detailed agent based approach, that explicitly incorporates governamental interventions, changes in mobility and contact patterns occurred during the COVID-19 outbreak in each country. Our simulations reproduce several of the features of its spatio-temporal spread in the three countries studied. They show that containment measures combined with high density are responsible for the containment of cases within densely populated areas, and that spread to less densely populated areas occurred during the late stages of the first wave. The capability to reproduce observed features of the spatio-temporal dynamics of SARS-CoV-2 makes this model a potential candidate for forecasting the dynamics of SARS-CoV-2 in other settings, and we recommend its application in low and lower-middle countries which remain understudied.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Type of study: Prognostic study Language: English Year: 2020 Document type: Preprint
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