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Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study

Restrictions to human mobility had a significant role in limiting SARS-CoV-2 spread. It has been suggested that seasonality might affect viral transmissibility. Our study retrospectively investigates the combined effect that seasonal environmental factors and human mobility played on transmissibilit...

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Bibliographic Details
Published in:Acta bio-medica de l'Ateneo Parmense 2022-08, Vol.93 (4)
Main Authors: Falzone, Yuri Matteo, Bosco, Luca, Sferruzza, Giacomo, Russo, Tommaso, Vabanesi, Marco, Carlo, Signorelli, Filippi, Massimo
Format: Article
Language:English
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Summary:Restrictions to human mobility had a significant role in limiting SARS-CoV-2 spread. It has been suggested that seasonality might affect viral transmissibility. Our study retrospectively investigates the combined effect that seasonal environmental factors and human mobility played on transmissibility of SARS-CoV-2 in Lombardy, Italy, in 2020; Environmental data were collected from accredited open-source web services. Aggregated mobility data for different points of interests were collected from Google Community Reports. The Reproduction number (R t ), based on the weekly counts of confirmed symptomatic COVID-19, non-imported cases, was used as a proxy for SARS-CoV-2 transmissibility. Assuming a non-linear correlation between selected variables, we used a Generalized Additive Model (GAM) to investigate with univariate and multivariate analyses the association between seasonal environmental factors (UV-index, temperature, humidity, and atmospheric pressure), location-specific mobility indices, and R t ; UV-index was the most effective environmental variable in predicting R t . An optimal two-week lag-effect between changes in explanatory variables and R t was selected. The association between R t variations and individually taken mobility indices differed: Grocery & Pharmacy, Transit Station and Workplaces displayed the best performances in predicting R t when individually added to the multivariate model together with UV-index, accounting for 85.0%, 85.5% and 82.6% of R t variance, respectively. According to our results, both seasonality and social interaction policies played a significant role in curbing the pandemic. Non-linear models including UV-index and location-specific mobility indices can predict a considerable amount of SARS-CoV-2 transmissibility in Lombardy during 2020, emphasizing the importance of social distancing policies to keep viral transmissibility under control, especially during colder months. ( www.actabiomedica.it )
ISSN:0392-4203
2531-6745
DOI:10.23750/abm.v93i4.12645