Spatial variability in the risk of death from COVID-19 in Italy

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  • K. Mizumoto
    Graduate School of Advanced Integrated Studies in Human Survivability, Hakubi Center for Advanced Research, Kyoto University, Japan, Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
  • S. Dahal
    Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA
  • G. Chowell
    Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, GA, USA

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<jats:p><jats:bold>OBJECTIVES:</jats:bold> Italy has been badly affected by the COVID-19 pandemic and has one of the highest death tolls. We analyzed the severity of COVID-19 across all 20 Italian regions.<jats:bold>METHOD:</jats:bold> We manually retrieved the daily cumulative numbers of laboratory-confirmed cases and deaths attributed to COVID-19 in each region, and estimated the crude case fatality ratio and time delay-adjusted case fatality ratio (aCFR). We then assessed the association between aCFR and sociodemographic, health care and transmission factors using multivariate regression analysis.<jats:bold>RESULTS:</jats:bold> The overall aCFR in Italy was estimated at 17.4%. Lombardia exhibited the highest aCFR (24.7%), followed by Marche (19.3%), Emilia Romagna (17.7%) and Liguria (17.6%). Our aCFR estimate was greater than 10% for 12 regions. Our aCFR estimates were statistically associated with population density and cumulative morbidity rate in a multivariate analysis.<jats:bold>CONCLUSION:</jats:bold> Our aCFR estimates for Italy as a whole and for seven out of the 20 regions exceeded those reported for the most badly affected region in China. These findings highlight the importance of social distancing to suppress transmission to avoid overwhelming the health care system and reduce the risk of death.</jats:p>

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