How mobility habits influenced the spread of the COVID-19 pandemic: Results from the Italian case study - Cartenì, Armando; Di Francesco, Luigi; Martino, Maria (The Science of the total environment, 2020)
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. [Display omitted] •We quantify the effect of mobility habits in the spread of the Coronavirus in Italy.•Daily COVID-19 cases are directly related to the mobility habits performed 21 days before.•Population density, PM pollutant and number of tests per day have a direct relationship with the infection.•Temperature has an inverse relationship with the spread of the virus.•The areas close to the outbreak had a higher risk of contagion (time-decay phenomena).