How mobility habits influenced the spread of the COVID-19 pandemic: Results from the Italian case study
- PMID: 32599395
- PMCID: PMC7313484
- DOI: 10.1016/j.scitotenv.2020.140489
How mobility habits influenced the spread of the COVID-19 pandemic: Results from the Italian case study
Abstract
Starting from December 2019 the world has faced an unprecedented health crisis caused by the new Coronavirus (COVID-19) due to the SARS-CoV-2 pathogen. Within this topic, the aim of the paper was to quantify the effect of mobility habits in the spread of the Coronavirus in Italy through a multiple linear regression model. Estimation results showed that mobility habits represent one of the variables that explains the number of COVID-19 infections jointly with the number of tests/day and some environmental variables (i.e. PM pollution and temperature). Nevertheless, a proximity variable to the first outbreak was also significant, meaning that the areas close to the outbreak had a higher risk of contagion, especially in the initial stage of infection (time-decay phenomena). Furthermore, the number of daily new cases was related to the trips performed three weeks before. This threshold of 21 days could be considered as a sort of positivity detection time, meaning that the mobility restrictions quarantine commonly set at 14 days, defined only according to incubation-based epidemiological considerations, is underestimated (possible delays between contagion and detection) as a containment policy and may not always contribute to effectively slowing down the spread of virus worldwide. This result is original and, if confirmed in other studies, will lay the groundwork for more effective containment of COVID-19 in countries that are still in the health emergency, as well as for possible future returns of the virus.
Keywords: Coronavirus; Mobility; Pandemic; SARS-CoV-2; Transport accessibility; Transportation.
Copyright © 2020 Elsevier B.V. All rights reserved.
Conflict of interest statement
Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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References
-
- Apple Inc COVID-19 mobility trends (driving data) 2020. https://www.apple.com/covid19/mobility (WWW document)
-
- ARPA - Agenzia Regionale per la Protezione Ambientale 2020. https://www.arpae.it/qualita-aria/bollettino-qa/?idlivello=1924 (WWW document)
-
- Cheng J., Bertolini L. Measuring urban job accessibility with distance decay, competition and diversity. J. Transp. Geogr. 2013;30:100–109. doi: 10.1016/j.jtrangeo.2013.03.005. - DOI
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