Beria, Paolo and Lunkar, Vardhman (2020): Presence and mobility of the population during Covid-19 outbreak and lockdown in Italy.
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Abstract
The non-medical policies implemented to “flatten the curve” and to reduce the stress on the health system during the COVID-19 outbreak represents a critical event in the history of Italy. This kind of “lockdown” has left people stranded in their homes and, for some, out of their homes unable to return to their region of residence due to the disruptions in the mobility network. As a consequence, a vast scale of research is being performed to understand the patterns of mobility of people during the emergency. The availability of rich datasets has made it possible to quantify the dynamics of spatial distribution of people as a response to the strict measures. With the help of the data provided by the Facebook – Data for Good program, an effort is made to describe and to reason on the presence and of mobility patterns of the population at a regional and provincial scale during the lockdown. Our interpretation is that, initially, tourists left the country and later Italians abroad managed to return from abroad stabilising the population. Concerning internal mobility, it is evident that the earliest affected Regions see a higher number of stationary users in the initial days of the outbreak. On the other hand, the central and the southern regions does not display a positive relative change of staying home until the official lockdown is announced on the 9th of March, 2020. Before the stricter lockdown started there was not a significant exodus of people from the North to the rest of the country. To the contrary, a visible relocation of people occurred between the cities and their urban belts.
Item Type: | MPRA Paper |
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Original Title: | Presence and mobility of the population during Covid-19 outbreak and lockdown in Italy |
Language: | English |
Keywords: | covid-19; outbreak; lockdown; mobility; Facebook data for good; location based mobility, big data; social network; Italy |
Subjects: | J - Labor and Demographic Economics > J6 - Mobility, Unemployment, Vacancies, and Immigrant Workers > J61 - Geographic Labor Mobility ; Immigrant Workers R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R2 - Household Analysis > R23 - Regional Migration ; Regional Labor Markets ; Population ; Neighborhood Characteristics R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R4 - Transportation Economics > R41 - Transportation: Demand, Supply, and Congestion ; Travel Time ; Safety and Accidents ; Transportation Noise |
Item ID: | 100896 |
Depositing User: | Paolo Beria |
Date Deposited: | 10 Jun 2020 07:44 |
Last Modified: | 10 Jun 2020 07:44 |
References: | Snibbe, K. (2018). How technology is helping responders save lives during disasters like the California wildfires. The Orange County Register. https://www.ocregister.com/2018/08/21/how-technology-is-helping-those-responding-to-disasters-like-the-california-wildfires-save-lives/ Gupta M (2018). Shedding light on displacement trends in disasters through technology? https://www.linkedin.com/pulse/shedding-light-displacement-trends-disasters-through-technology-manu/ Jia, S., Kim, S.H., Nghiem, S.V., Doherty, P. and Kafatos, M.C., (2020, in press). Patterns of population displacement during mega-fires in California detected using Facebook Disaster Maps. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ab8847 Bonaccorsi, G., Pierri, F., Cinelli, M., Porcelli, F., Galeazzi, A., Flori, A., Schmidt, AL., Valensise, M., Sacala, A., Quattrociocchi, W., and Pammolli, F. (2020). Economic and Social Consequences of Human Mobility Restrictions Under COVID-19 – The case of Italy. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3573609 Galeazzi, A., Cinelli, M., Bonaccorsi, G., Pierri, F., Schmidt, A.L., Scala, A., Pammolli, F. and Quattrociocchi, W. (2020). Human Mobility in Response to COVID-19 in France, Italy and UK. arXiv preprint arXiv:2005.06341. Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C. and Tizzoni, M. (2020). COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown. medRxiv. Klein, B., LaRocky, T., McCabey, S., Torresy, L., Privitera, F., Lake, B., Kraemer, M.U., Brownstein, J.S., Lazer, D., Eliassi-Rad, T. and Scarpino, S.V., (2020). Assessing changes in commuting and individual mobility in major metropolitan areas in the United States during the COVID-19 outbreak. https://www.networkscienceinstitute.org/publications/assessing-changes-in-commuting-and-individual-mobility-in-major-metropolitan-areas-in-the-united-states-during-the-covid-19-outbreak Kissler, S., Kishore, N., Prabhu, M., Goffman, D., Beilin, Y., Landau, R., Gyamfi-Bannerman, C., Bateman, B., Katz, D., Gal, J. and Bianco, A., (2020). Reductions in commuting mobility predict geographic differences in SARS-CoV-2 prevalence in New York City. http://nrs.harvard.edu/urn-3:HUL.InstRepos:42665370 Denis, E., Telle, O., Benkimoun, S., Mukhopadhyay, P., & Nath, S. (2020). Mapping the lockdown effects in India: how geographers can contribute to tackle Covid-19 diffusion. The Conversation. https://theconversation.com/mapping-the-lockdown-effects-in-india-how-geographers-can-contribute-to-tackle-covid-19-diffusion-136323 Burstein, R., Hu, H., Thakkar, N., Schroeder, A., Famulare, M. and Klein, D. (2020). Understanding the impact of COVID-19 policy change in the greater Seattle area using mobility data. Institute for Disease Modeling. https://covid.idmod.org/data/Understanding_impact_of_COVID_policy_change_Seattle.pdf Chang, M.C., Kahn, R., Li, Y.A., Lee, C.S., Buckee, C.O. and Chang, H.H. (2020). Modeling the impact of human mobility and travel restrictions on the potential spread of SARS-CoV-2 in Taiwan. medRxiv. Maas, P., Iyer, S., Gros, A., Park, W., McGorman, L., Nayak, C. and Dow, P.A. (2019). Facebook Disaster Maps: Aggregate Insights for Crisis Response and Recovery. In Proceedings of the 16th International Conference on Information Systems for Crisis Response and Management (ISCRAM), Valencia, Spain (pp. 19-22). |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/100896 |