A novel methodology for epidemic risk assessment of COVID-19 outbreak

Abstract We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the...

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Main Authors: A. Pluchino, A. E. Biondo, N. Giuffrida, G. Inturri, V. Latora, R. Le Moli, A. Rapisarda, G. Russo, C. Zappalà
Format: Article
Language:English
Published: Nature Publishing Group 2021-03-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-021-82310-4
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spelling doaj-1f894c474cfd405a96a5e4af3bad6b9e2021-03-11T12:17:46ZengNature Publishing GroupScientific Reports2045-23222021-03-0111112010.1038/s41598-021-82310-4A novel methodology for epidemic risk assessment of COVID-19 outbreakA. Pluchino0A. E. Biondo1N. Giuffrida2G. Inturri3V. Latora4R. Le Moli5A. Rapisarda6G. Russo7C. Zappalà8Dipartimento di Fisica e Astronomia “Ettore Majorana”, INFN Sezione di Catania, Università di CataniaDipartimento di Economia e Impresa, Università di CataniaDipartimento di Ingegneria Civile e Architettura, Università di CataniaDipartimento di Ingegneria Elettrica Elettronica e Informatica, Università di CataniaDipartimento di Fisica e Astronomia “Ettore Majorana”, INFN Sezione di Catania, Università di CataniaDipartimento di Medicina Clinica e Sperimentale - UO di Endocrinologia - Ospedale Garibaldi Nesima, Università di CataniaDipartimento di Fisica e Astronomia “Ettore Majorana”, INFN Sezione di Catania, Università di CataniaDipartimento di Matematica e Informatica, Università di CataniaDipartimento di Fisica e Astronomia “Ettore Majorana”, INFN Sezione di Catania, Università di CataniaAbstract We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.https://doi.org/10.1038/s41598-021-82310-4
collection DOAJ
language English
format Article
sources DOAJ
author A. Pluchino
A. E. Biondo
N. Giuffrida
G. Inturri
V. Latora
R. Le Moli
A. Rapisarda
G. Russo
C. Zappalà
spellingShingle A. Pluchino
A. E. Biondo
N. Giuffrida
G. Inturri
V. Latora
R. Le Moli
A. Rapisarda
G. Russo
C. Zappalà
A novel methodology for epidemic risk assessment of COVID-19 outbreak
Scientific Reports
author_facet A. Pluchino
A. E. Biondo
N. Giuffrida
G. Inturri
V. Latora
R. Le Moli
A. Rapisarda
G. Russo
C. Zappalà
author_sort A. Pluchino
title A novel methodology for epidemic risk assessment of COVID-19 outbreak
title_short A novel methodology for epidemic risk assessment of COVID-19 outbreak
title_full A novel methodology for epidemic risk assessment of COVID-19 outbreak
title_fullStr A novel methodology for epidemic risk assessment of COVID-19 outbreak
title_full_unstemmed A novel methodology for epidemic risk assessment of COVID-19 outbreak
title_sort novel methodology for epidemic risk assessment of covid-19 outbreak
publisher Nature Publishing Group
series Scientific Reports
issn 2045-2322
publishDate 2021-03-01
description Abstract We propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.
url https://doi.org/10.1038/s41598-021-82310-4
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