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COVID-19 in Italy: An Analysis of Death Registry Data.
Ciminelli, Gabriele; Garcia-Mandicó, Sílvia.
  • Ciminelli G; Finance and Economics, Asia School of Business, 2 Jalan Dato Onn, 50480 Kuala Lumpur, Malaysia.
  • Garcia-Mandicó S; MIT Sloan School of Management, 100 Main St, Cambridge, MA 02142, USA.
J Public Health (Oxf) ; 42(4): 723-730, 2020 11 23.
Article in English | MEDLINE | ID: covidwho-772654
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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Registries / COVID-19 Type of study: Observational study / Prognostic study Limits: Female / Humans / Male Country/Region as subject: Europa Language: English Journal: J Public Health (Oxf) Year: 2020 Document Type: Article Affiliation country: Pubmed

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Registries / COVID-19 Type of study: Observational study / Prognostic study Limits: Female / Humans / Male Country/Region as subject: Europa Language: English Journal: J Public Health (Oxf) Year: 2020 Document Type: Article Affiliation country: Pubmed