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

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

Authors

  • Yuri Matteo Falzone a:1:{s:5:"en_US";s:72:"1. Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy";}
  • Luca Bosco
  • Giacomo Sferruzza
  • Tommaso Russo
  • Marco Vabanesi
  • Carlo Signorelli
  • Massimo Filippi

Keywords:

SARS-CoV2, UV, environmental factors, transmissibility, GAM analysis

Abstract

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 (Rt), 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 Rt.

UV-index was the most effective environmental variable in predicting Rt. An optimal two-week lag-effect between changes in explanatory variables and Rt was selected. The association between Rt variations and individually taken mobility indices differed: Grocery & Pharmacy, Transit Station and Workplaces displayed the best performances in predicting Rt when individually added to the multivariate model together with UV-index, accounting for 85.0%, 85.5% and 82.6% of Rt 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.

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Published

31-08-2022

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Section

ORIGINAL INVESTIGATIONS/COMMENTARIES - SPECIAL COVID19

How to Cite

1.
Falzone YM, Bosco L, Sferruzza G, Russo T, Vabanesi M, Signorelli C, et al. Evaluation of the combined effect of mobility and seasonality on the COVID-19 pandemic: a Lombardy-based study. Acta Biomed [Internet]. 2022 Aug. 31 [cited 2024 Jul. 17];93(4):e2022212. Available from: https://mattioli1885journals.com/index.php/actabiomedica/article/view/12645