Assessment of an organizational model during the first wave of COVID -19 in the South-Eastern Tuscany Health Unit: intensifying community services as prescribed by Ministerial Decree 77 of 2022

Ann Ig. 2024 Nov-Dec;36(6):644-651. doi: 10.7416/ai.2024.2633.

Abstract

Introduction: At the end of 2019 a new virus, called SARS-CoV-2, emerged in Wuhan, China. The aim of the present study was to assess the impact of the first wave of the COVID-19 pandemic on the health system of the Tuscany Region and the response implemented by the South-Eastern Local Health Unit, also in view of the new reform of territorial healthcare established by Ministerial Decree No. 77 of 2022.

Methods: Data were taken from the "OpenToscana" database beginning when the first case was recorded in Italy (18 February 2020) until July 2020. We analyzed infections and deaths in each Local Heal.th Unit in the Tuscany Region and calculated the fatality rate (number of deaths/cases x 100) following COVID-19 infection. We subsequently compared the fatality rates among the Local Health Units by means of the Kruskal Wallis test.

Results: During the first wave, the South-Eastern Local Health Unit had fewer infections (a total of 1,532 by July) and fewer deaths (total: 107 by July) than the other Local Health Units. In the South-Eastern Local Health Unit, the fatality rate in July was 6.98%. The comparison of the fatality rates among the various LHUs and the whole Region showed statistically significant differences (p<0.001).

Conclusions: The organizational models promptly implemented by the South-Eastern Local Health Unit for good territorial care and the management of COVID-19-positive patients limited the spread of infection, and consequently the deaths, thus reducing the fatality rate in the first wave of the pandemic.

Keywords: Covid-19; fatality; organizational model.

Publication types

  • Evaluation Study

MeSH terms

  • COVID-19* / epidemiology
  • Community Health Services* / organization & administration
  • Humans
  • Italy / epidemiology
  • Models, Organizational*
  • Pandemics
  • SARS-CoV-2