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Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy

BACKGROUND: On March 11, 2020, the World Health Organization characterized the novel coronavirus disease 2019 (COVID-19) outbreak as a pandemic. The first cases in Italy were reported on January 30, 2020, and the outbreak quickly escalated. On March 19, 2020, deaths in Italy surpassed those in China...

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Autores principales: Vicentini, C., Bordino, V., Gardois, P., Zotti, C.M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society for Public Health. Published by Elsevier Ltd. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306704/
https://www.ncbi.nlm.nih.gov/pubmed/32593056
http://dx.doi.org/10.1016/j.puhe.2020.06.028
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author Vicentini, C.
Bordino, V.
Gardois, P.
Zotti, C.M.
author_facet Vicentini, C.
Bordino, V.
Gardois, P.
Zotti, C.M.
author_sort Vicentini, C.
collection PubMed
description BACKGROUND: On March 11, 2020, the World Health Organization characterized the novel coronavirus disease 2019 (COVID-19) outbreak as a pandemic. The first cases in Italy were reported on January 30, 2020, and the outbreak quickly escalated. On March 19, 2020, deaths in Italy surpassed those in China. The Italian government implemented progressively restrictive measures leading to a nationwide lockdown on March 8, 2020. This study aimed to assess the impact of mitigation measures implemented in Italy on the spread of COVID-19. METHODS: Publicly available data were used to evaluate changes in the growth curve of the number of patients hospitalized in intensive care (IC) at three time intervals between February 19, 2020, and April 9, 2020, after the implementation of progressive measures: (1) containment and travel restrictions, (2) lockdown of the epicenter of the outbreak, and (3) school closures and nationwide lockdown. The models that showed the highest reliability according to the Akaike information criterion and based on data from the three time intervals were projected to assess how the epidemic would have evolved if no other measure had been implemented. RESULTS: The most reliable models were (1) exponential, (2) quadratic, and (3) cubic (R(2) = 0.99, >0.99, and > 0.99 respectively), indicating a progressive decrease in the growth of the curve. CONCLUSION: This study suggests the measures were effective in flattening the epidemic curve and bought valuable time, allowing for the number of IC beds to be nearly doubled before the national health system reached maximum capacity.
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spelling pubmed-73067042020-06-22 Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy Vicentini, C. Bordino, V. Gardois, P. Zotti, C.M. Public Health Article BACKGROUND: On March 11, 2020, the World Health Organization characterized the novel coronavirus disease 2019 (COVID-19) outbreak as a pandemic. The first cases in Italy were reported on January 30, 2020, and the outbreak quickly escalated. On March 19, 2020, deaths in Italy surpassed those in China. The Italian government implemented progressively restrictive measures leading to a nationwide lockdown on March 8, 2020. This study aimed to assess the impact of mitigation measures implemented in Italy on the spread of COVID-19. METHODS: Publicly available data were used to evaluate changes in the growth curve of the number of patients hospitalized in intensive care (IC) at three time intervals between February 19, 2020, and April 9, 2020, after the implementation of progressive measures: (1) containment and travel restrictions, (2) lockdown of the epicenter of the outbreak, and (3) school closures and nationwide lockdown. The models that showed the highest reliability according to the Akaike information criterion and based on data from the three time intervals were projected to assess how the epidemic would have evolved if no other measure had been implemented. RESULTS: The most reliable models were (1) exponential, (2) quadratic, and (3) cubic (R(2) = 0.99, >0.99, and > 0.99 respectively), indicating a progressive decrease in the growth of the curve. CONCLUSION: This study suggests the measures were effective in flattening the epidemic curve and bought valuable time, allowing for the number of IC beds to be nearly doubled before the national health system reached maximum capacity. The Royal Society for Public Health. Published by Elsevier Ltd. 2020-08 2020-06-22 /pmc/articles/PMC7306704/ /pubmed/32593056 http://dx.doi.org/10.1016/j.puhe.2020.06.028 Text en © 2020 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Vicentini, C.
Bordino, V.
Gardois, P.
Zotti, C.M.
Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title_full Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title_fullStr Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title_full_unstemmed Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title_short Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy
title_sort early assessment of the impact of mitigation measures on the covid-19 outbreak in italy
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306704/
https://www.ncbi.nlm.nih.gov/pubmed/32593056
http://dx.doi.org/10.1016/j.puhe.2020.06.028
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