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Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria

The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions...

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Autores principales: Ledebur, Katharina, Kaleta, Michaela, Chen, Jiaying, Lindner, Simon D., Matzhold, Caspar, Weidle, Florian, Wittmann, Christoph, Habimana, Katharina, Kerschbaumer, Linda, Stumpfl, Sophie, Heiler, Georg, Bicher, Martin, Popper, Nikolas, Bachner, Florian, Klimek, Peter
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009775/
https://www.ncbi.nlm.nih.gov/pubmed/35377873
http://dx.doi.org/10.1371/journal.pcbi.1009973
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author Ledebur, Katharina
Kaleta, Michaela
Chen, Jiaying
Lindner, Simon D.
Matzhold, Caspar
Weidle, Florian
Wittmann, Christoph
Habimana, Katharina
Kerschbaumer, Linda
Stumpfl, Sophie
Heiler, Georg
Bicher, Martin
Popper, Nikolas
Bachner, Florian
Klimek, Peter
author_facet Ledebur, Katharina
Kaleta, Michaela
Chen, Jiaying
Lindner, Simon D.
Matzhold, Caspar
Weidle, Florian
Wittmann, Christoph
Habimana, Katharina
Kerschbaumer, Linda
Stumpfl, Sophie
Heiler, Georg
Bicher, Martin
Popper, Nikolas
Bachner, Florian
Klimek, Peter
author_sort Ledebur, Katharina
collection PubMed
description The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves.
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spelling pubmed-90097752022-04-15 Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria Ledebur, Katharina Kaleta, Michaela Chen, Jiaying Lindner, Simon D. Matzhold, Caspar Weidle, Florian Wittmann, Christoph Habimana, Katharina Kerschbaumer, Linda Stumpfl, Sophie Heiler, Georg Bicher, Martin Popper, Nikolas Bachner, Florian Klimek, Peter PLoS Comput Biol Research Article The drivers behind regional differences of SARS-CoV-2 spread on finer spatio-temporal scales are yet to be fully understood. Here we develop a data-driven modelling approach based on an age-structured compartmental model that compares 116 Austrian regions to a suitably chosen control set of regions to explain variations in local transmission rates through a combination of meteorological factors, non-pharmaceutical interventions and mobility. We find that more than 60% of the observed regional variations can be explained by these factors. Decreasing temperature and humidity, increasing cloudiness, precipitation and the absence of mitigation measures for public events are the strongest drivers for increased virus transmission, leading in combination to a doubling of the transmission rates compared to regions with more favourable weather. We conjecture that regions with little mitigation measures for large events that experience shifts toward unfavourable weather conditions are particularly predisposed as nucleation points for the next seasonal SARS-CoV-2 waves. Public Library of Science 2022-04-04 /pmc/articles/PMC9009775/ /pubmed/35377873 http://dx.doi.org/10.1371/journal.pcbi.1009973 Text en © 2022 Ledebur et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Ledebur, Katharina
Kaleta, Michaela
Chen, Jiaying
Lindner, Simon D.
Matzhold, Caspar
Weidle, Florian
Wittmann, Christoph
Habimana, Katharina
Kerschbaumer, Linda
Stumpfl, Sophie
Heiler, Georg
Bicher, Martin
Popper, Nikolas
Bachner, Florian
Klimek, Peter
Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title_full Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title_fullStr Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title_full_unstemmed Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title_short Meteorological factors and non-pharmaceutical interventions explain local differences in the spread of SARS-CoV-2 in Austria
title_sort meteorological factors and non-pharmaceutical interventions explain local differences in the spread of sars-cov-2 in austria
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9009775/
https://www.ncbi.nlm.nih.gov/pubmed/35377873
http://dx.doi.org/10.1371/journal.pcbi.1009973
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