期刊
PLOS COMPUTATIONAL BIOLOGY
卷 18, 期 4, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1009973
关键词
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资金
- Vienna Science and Technology Fund WWTF [MA16-045]
- Medizinisch-Wissenschaftlichen Fonds des Buergermeisters der Bundeshauptstadt Wien [CoVid004]
- Austrian Science Promotion Agency FFG [857136]
This study develops a data-driven modelling approach to explain the regional variations in SARS-CoV-2 spread in 116 Austrian regions based on meteorological factors, non-pharmaceutical interventions, and mobility. The findings show 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.
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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