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Demographic and Socio-Economic Factors, and Healthcare Resource Indicators Associated with the Rapid Spread of COVID-19 in Northern Italy: An Ecological Study
Alessandra Buja; Matteo Paganini; Silvia Cocchio; Manuela Scioni; Vincenzo Rebba; Vincenzo Baldo.
Affiliation
  • Alessandra Buja; Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy.
  • Matteo Paganini; Department of Biomedical Sciences, University of Padova.
  • Silvia Cocchio; Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy.
  • Manuela Scioni; Statistics Department, University of Padova. Via C. Battisti, 241, 35121, Padova, Italy.
  • Vincenzo Rebba; 'Marco Fanno' Department of Economics and Management, University of Padova. Via U. Bassi, 1, 35131, Padova, Italy.
  • Vincenzo Baldo; Department of Cardiologic, Vascular and Thoracic Sciences, and Public Health, University of Padova. Via Loredan, 18, 35131, Padova, Italy.
Preprint in English | medRxiv | ID: ppmedrxiv-20078311
Journal article
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ABSTRACT
BackgroundCOVID-19 rapidly escalated into a pandemic, threatening 213 countries, areas, and territories the world over. We aimed to identify potential province-level socioeconomic determinants of the viruss dissemination, and explain between-province differences in the speed of its spread, based on data from 36 provinces of Northern Italy. MethodsThis is an ecological study. We included all confirmed cases of SARS-CoV-2 reported between February 24th and March 30th, 2020. For each province, we calculated the trend of contagion as the relative increase in the number of individuals infected between two time endpoints, assuming an exponential growth. Pearsons test was used to correlate the trend of contagion with a set of healthcare-associated, economic, and demographic parameters by province. The viruss spread was input as a dependent variable in a stepwise OLS regression model to test the association between rate of spread and province-level indicators. FindingsMultivariate analysis showed that the spread of COVID-19 was correlated negatively with aging index (p-value=0.003), and positively with public transportation per capita (p-value=0.012), the % of private long-term care hospital beds and, to a lesser extent (p-value=0.070), the % of private acute care hospital beds (p-value=0.006). InterpretationDemographic and socioeconomic factors, and healthcare organization variables were found associated with a significant difference in the rate of COVID-19 spread in 36 provinces of Northern Italy. An aging population seemed to naturally contain social contacts. The availability of healthcare resources and their coordination could play an important part in spreading infection.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2020 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2020 Document type: Preprint
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