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      Economic and social consequences of human mobility restrictions under COVID-19


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          This paper presents a large-scale analysis of the impact of lockdown measures introduced in response to the spread of novel coronavirus disease 2019 (COVID-19) on socioeconomic conditions of Italian citizens. We leverage a massive near–real-time dataset of human mobility and we model mobility restrictions as an exogenous shock to the economy, similar to a natural disaster. We find that lockdown measures have a twofold effect: First, their impact on mobility is stronger in municipalities with higher fiscal capacity; second, they induce a segregation effect: mobility contraction is stronger in municipalities where inequality is higher and income per capita is lower. We highlight the necessity of fiscal measures that account for these effects, targeting poverty and inequality mitigation.


          In response to the coronavirus disease 2019 (COVID-19) pandemic, several national governments have applied lockdown restrictions to reduce the infection rate. Here we perform a massive analysis on near–real-time Italian mobility data provided by Facebook to investigate how lockdown strategies affect economic conditions of individuals and local governments. We model the change in mobility as an exogenous shock similar to a natural disaster. We identify two ways through which mobility restrictions affect Italian citizens. First, we find that the impact of lockdown is stronger in municipalities with higher fiscal capacity. Second, we find evidence of a segregation effect, since mobility contraction is stronger in municipalities in which inequality is higher and for those where individuals have lower income per capita. Our results highlight both the social costs of lockdown and a challenge of unprecedented intensity: On the one hand, the crisis is inducing a sharp reduction of fiscal revenues for both national and local governments; on the other hand, a significant fiscal effort is needed to sustain the most fragile individuals and to mitigate the increase in poverty and inequality induced by the lockdown.

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          Most cited references18

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          The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak

          Motivated by the rapid spread of COVID-19 in Mainland China, we use a global metapopulation disease transmission model to project the impact of travel limitations on the national and international spread of the epidemic. The model is calibrated based on internationally reported cases, and shows that at the start of the travel ban from Wuhan on 23 January 2020, most Chinese cities had already received many infected travelers. The travel quarantine of Wuhan delayed the overall epidemic progression by only 3 to 5 days in Mainland China, but has a more marked effect at the international scale, where case importations were reduced by nearly 80% until mid February. Modeling results also indicate that sustained 90% travel restrictions to and from Mainland China only modestly affect the epidemic trajectory unless combined with a 50% or higher reduction of transmission in the community.
            • Record: found
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            The effect of human mobility and control measures on the COVID-19 epidemic in China

            The ongoing COVID-19 outbreak expanded rapidly throughout China. Major behavioral, clinical, and state interventions have been undertaken to mitigate the epidemic and prevent the persistence of the virus in human populations in China and worldwide. It remains unclear how these unprecedented interventions, including travel restrictions, affected COVID-19 spread in China. We use real-time mobility data from Wuhan and detailed case data including travel history to elucidate the role of case importation on transmission in cities across China and ascertain the impact of control measures. Early on, the spatial distribution of COVID-19 cases in China was explained well by human mobility data. Following the implementation of control measures, this correlation dropped and growth rates became negative in most locations, although shifts in the demographics of reported cases were still indicative of local chains of transmission outside Wuhan. This study shows that the drastic control measures implemented in China substantially mitigated the spread of COVID-19.
              • Record: found
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              • Article: not found

              Efficient Behavior of Small-World Networks

              We introduce the concept of efficiency of a network as a measure of how efficiently it exchanges information. By using this simple measure, small-world networks are seen as systems that are both globally and locally efficient. This gives a clear physical meaning to the concept of "small world," and also a precise quantitative analysis of both weighted and unweighted networks. We study neural networks and man-made communication and transportation systems and we show that the underlying general principle of their construction is in fact a small-world principle of high efficiency.

                Author and article information

                Proc Natl Acad Sci U S A
                Proc. Natl. Acad. Sci. U.S.A
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                7 July 2020
                18 June 2020
                18 June 2020
                : 117
                : 27
                : 15530-15535
                [1] aImpact, Department of Management, Economics and Industrial Engineering, Politecnico di Milano , 20156 Milano, Italy;
                [2] bDepartment of Electronics, Information and Bioengineering, Politecnico di Milano , 20133 Milano, Italy;
                [3] cIstituto dei Sistemi Complessi, Consiglio Nazionale delle Ricerche , 00185 Rome, Italy;
                [4] dDepartment of Information Engineering, Università di Brescia , 25121 Brescia, Italy;
                [5] eDepartment of Law, Università di Bari , 70121 Bari, Italy;
                [6] fDepartment of Environmental Sciences, Informatics and Statistics, Università Ca’Foscari di Venezia , 30123 Venizia, Italy;
                [7] gDepartment of Physics, Politecnico di Milano , 20133 Milano, Italy;
                [8] hJoint Center for Analysis, Decisions and Society, Human Technopole and Politecnico di Milano , 20157 Milano, Italy
                Author notes
                2To whom correspondence may be addressed. Email: giovanni.bonaccorsi@ 123456polimi.it or fabio.pammolli@ 123456polimi.it .

                Edited by Arild Underdal, University of Oslo, Oslo, Norway, and approved June 5, 2020 (received for review April 24, 2020)

                Author contributions: A.F., A.S., W.Q., and F. Pammolli designed research; G.B., F. Pierri, M.C., A.G., and F. Porcelli performed research; G.B., F. Pierri, M.C., A.G., and F. Porcelli analyzed data; G.B., F. Pierri, M.C., A.F., A.G., F. Porcelli, A.L.S., C.M.V., A.S., W.Q., and F. Pammolli wrote the paper; and G.B., F. Pierri, and A.L.S. collected data.

                1G.B. and F. Pierri contributed equally to this work.

                Copyright © 2020 the Author(s). Published by PNAS.

                This open access article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                Page count
                Pages: 6
                Social Sciences
                Economic Sciences
                Physical Sciences

                covid-19,economic segregation,human mobility,national lockdown


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