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10.1073/pnas.2007658117

http://scihub22266oqcxt.onion/10.1073/pnas.2007658117
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32554604!7355033!32554604
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suck abstract from ncbi


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pmid32554604      Proc+Natl+Acad+Sci+U+S+A 2020 ; 117 (27): 15530-15535
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  • Economic and social consequences of human mobility restrictions under COVID-19 #MMPMID32554604
  • Bonaccorsi G; Pierri F; Cinelli M; Flori A; Galeazzi A; Porcelli F; Schmidt AL; Valensise CM; Scala A; Quattrociocchi W; Pammolli F
  • Proc Natl Acad Sci U S A 2020[Jul]; 117 (27): 15530-15535 PMID32554604show ga
  • 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.
  • |COVID-19[MESH]
  • |Coronavirus Infections/*economics[MESH]
  • |Humans[MESH]
  • |Italy[MESH]
  • |Pandemics/*economics[MESH]
  • |Pneumonia, Viral/*economics[MESH]
  • |Quarantine/*economics/statistics & numerical data[MESH]
  • |Socioeconomic Factors[MESH]


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