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10.1093/pubmed/fdaa165

http://scihub22266oqcxt.onion/10.1093/pubmed/fdaa165
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32935849!7543414!32935849
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suck abstract from ncbi

pmid32935849      J+Public+Health+(Oxf) 2020 ; 42 (4): 723-730
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  • COVID-19 in Italy: An Analysis of Death Registry Data #MMPMID32935849
  • Ciminelli G; Garcia-Mandico S
  • J Public Health (Oxf) 2020[Nov]; 42 (4): 723-730 PMID32935849show ga
  • BACKGROUND: There are still many unknowns about COVID-19. We do not know its exact mortality rate nor the speed through which it spreads across communities. This lack of evidence complicates the design of appropriate response policies. METHODS: We source daily death registry data for 4100 municipalities in Italy's north and match them to Census data. We augment the dataset with municipality-level data on a host of co-factors of COVID-19 mortality, which we exploit in a differences-in-differences regression model to analyze COVID-19-induced mortality. RESULTS: We find that COVID-19 killed more than 0.15% of the local population during the first wave of the epidemic. We also show that official statistics vastly underreport this death toll, by about 60%. Next, we uncover the dramatic effects of the epidemic on nursing home residents in the outbreak epicenter: in municipalities with a high share of the elderly living in nursing homes, COVID-19 mortality was about twice as high as in those with no nursing home intown. CONCLUSIONS: A pro-active approach in managing the epidemic is key to reduce COVID-19 mortality. Authorities should ramp-up testing capacity and increase contact-tracing abilities. Adequate protective equipment should be provided to nursing home residents and staff.
  • |*Registries[MESH]
  • |Age Factors[MESH]
  • |COVID-19/*mortality[MESH]
  • |Female[MESH]
  • |Homes for the Aged[MESH]
  • |Humans[MESH]
  • |Italy/epidemiology[MESH]
  • |Male[MESH]
  • |Nursing Homes[MESH]
  • |Pandemics[MESH]
  • |Risk Assessment[MESH]
  • |Risk Factors[MESH]
  • |SARS-CoV-2[MESH]


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