We present a novel methodology in order to perform the epidemic risk assessment in terms of different factors which are useful to understand the different impact of an epidemic in different areas of a country. In particular we discuss the case of COVID-19 outbreak in Italy. We characterize each region of Italy by considering the available data on air pollution, mobility, winter temperature, housing concentration, health care density, total and aged population . We find that the epidemic risk is higher in some of the northern regions of Italy with respect to central and southern part . Our epidemic risk index shows strong correlations with the available official data of the COVID-19 outbreak in Italy and explain in particular why regions like Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country in terms of infected cases, intensive care units and deceased patients . Although the COVID-19 outbreak started almost in the same period, at the beginning of 2020, in both north (Lombardia and Veneto) and central part of Italy (Lazio)  , when the first infected were officially certified , the outbreak has been more diffuse and lethal only in those regions with higher epidemic risk. Due to the fact that a large part of infected people do not show evident symptoms of the disease, we claim that in the regions with a lower epidemic risk, i.e. the central and south part of Italy, the epidemic , although probably already very diffused, should not be as lethal as in the northern part of Italy due to a different a-priori risk exposure . We also discuss some policy implications directly connected with our methodology, which results to be very flexible and adaptable to different set of epidemic historical data and to different countries.
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 its vulnerability. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available data on air pollution, 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 . Our epidemic risk index shows strong correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto are suffering much more than the rest of the country . Although the COVID-19 outbreak started in both North (Lombardia and Veneto) and Central Italy (Lazio) almost at the same time , when the first infected 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 . We also discuss some policy implications directly connected with our methodology, which results to be very flexible and can be adopted for risk assessment in other countries.
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present a novel methodology in order to perform the epidemic risk assessment in terms of different factors which are useful to understand the different impact of an epidemic in different areas of a country. In particular
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 its vulnerability. As an application,
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region of Italy by considering the
of the twenty Italian regions by using
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total and aged population
population size and age
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northern regions of Italy
Northern regions
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central and southern part
Central and Southern Italy
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of the COVID-19 outbreak in Italy and explain in particular why regions like
on the number of infected individuals, patients in intensive care and deceased patients, and can explain why regions such as
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in terms of infected cases, intensive care units and deceased patients
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almost in the same period, at the beginning of 2020, in both north
in both North
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central part of
Central
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almost at the same time
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, the outbreak has been more diffuse and lethal only in those
at the beginning of 2020, the disease has spread faster and with heavier consequences in
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Due to the fact that a large part of infected people do not show evident symptoms of the disease, we claim that in the regions with a lower epidemic risk, i.e. the central and south part of Italy, the epidemic , although probably already very diffused, should not be as lethal as in the northern part of Italy due to a different a-priori risk exposure
Our framework can be extended and tested on other epidemic data, such as those on seasonal flu
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adaptable to different set of epidemic historical data and to different
can be adopted for risk assessment in other