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Early assessment of the impact of mitigation measures on the COVID-19 outbreak in Italy.
Vicentini, C; Bordino, V; Gardois, P; Zotti, C M.
Afiliación
  • Vicentini C; Department of Public Health and Paediatrics, University of Turin, Via Santena 5 bis, 10126, Turin, Italy. Electronic address: costanza.vicentini@unito.it.
  • Bordino V; Department of Public Health and Paediatrics, University of Turin, Via Santena 5 bis, 10126, Turin, Italy.
  • Gardois P; Department of Public Health and Paediatrics, University of Turin, Via Santena 5 bis, 10126, Turin, Italy.
  • Zotti CM; Department of Public Health and Paediatrics, University of Turin, Via Santena 5 bis, 10126, Turin, Italy.
Public Health ; 185: 99-101, 2020 Aug.
Article en En | MEDLINE | ID: mdl-32593056
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 (R2 = 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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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía Viral / Brotes de Enfermedades / Infecciones por Coronavirus / Pandemias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Public Health Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neumonía Viral / Brotes de Enfermedades / Infecciones por Coronavirus / Pandemias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans País/Región como asunto: Europa Idioma: En Revista: Public Health Año: 2020 Tipo del documento: Article Pais de publicación: Países Bajos