COVID-19 in Italy: An Analysis of Death Registry Data.
Identifieur interne : 001527 ( Main/Exploration ); précédent : 001526; suivant : 001528COVID-19 in Italy: An Analysis of Death Registry Data.
Auteurs : Gabriele Ciminelli [Malaisie, États-Unis] ; Sílvia Garcia-Mandic [France]Source :
- Journal of public health (Oxford, England) [ 1741-3850 ] ; 2020.
Abstract
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.
DOI: 10.1093/pubmed/fdaa165
PubMed: 32935849
Affiliations:
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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.</p></div><div type="abstract" xml:lang="en"><p><b>METHODS</b></p><p>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.</p></div><div type="abstract" xml:lang="en"><p><b>RESULTS</b></p><p>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.</p></div><div type="abstract" xml:lang="en"><p><b>CONCLUSIONS</b></p><p>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.</p></div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32935849</PMID><DateRevised><Year>2020</Year><Month>09</Month><Day>16</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1741-3850</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Sep</Month><Day>16</Day></PubDate></JournalIssue><Title>Journal of public health (Oxford, England)</Title><ISOAbbreviation>J Public Health (Oxf)</ISOAbbreviation></Journal><ArticleTitle>COVID-19 in Italy: An Analysis of Death Registry Data.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">fdaa165</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1093/pubmed/fdaa165</ELocationID><Abstract><AbstractText Label="BACKGROUND" NlmCategory="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.</AbstractText><AbstractText Label="METHODS" NlmCategory="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.</AbstractText><AbstractText Label="RESULTS" NlmCategory="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.</AbstractText><AbstractText Label="CONCLUSIONS" NlmCategory="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.</AbstractText><CopyrightInformation>© The Author(s) 2020. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. 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