CoViD-19 in Italy: a mathematical model to analyze the epidemic containment strategy and the economic impacts
The objective of this paper is to evaluate the potential costs deriving from the adoption of the CoViD-19 epidemic management strategy. For this purpose, we developed a specific methodology that combines an epidemiological model, known in the literature as "SIR" (Susceptible - Infected - Recovered), and a probabilistic state model, also known as "multi-state". The model was then parameterized using the dataset published by the Italian Government through the Civil Protection and the Istituto Superiore di Sanità. Leveraging the identified parameters, we estimated the total amount of ICU hospital, non-ICU hospital and home isolation days that needed to extinguish a single-wave pandemic. Then we proceeded estimating the related hospital costs in the ongoing pandemic management strategy. We furthermore analyzed different scenarios that can be useful to assess choices the Government could adopt to face unforeseen events and outlined a way to exploit the results of the model (and in particular, the total amount of home isolation days and the overall timespan of the pandemic wave). These considerations represent a first step to assess the overall direct impact on Gross Domestic Product (GDP) of the pandemic..
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2020 |
|---|---|
| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
|---|---|
| Enthalten in: |
Risk Management Magazine - 15(2020), 2, Seite 23-34 |
| Sprache: |
Englisch ; Italienisch |
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| Beteiligte Personen: |
Fabio Verachi [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
“asymptomatic cases” |
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| doi: |
10.47473/2020rmm0013 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ007514964 |
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| 520 | |a The objective of this paper is to evaluate the potential costs deriving from the adoption of the CoViD-19 epidemic management strategy. For this purpose, we developed a specific methodology that combines an epidemiological model, known in the literature as "SIR" (Susceptible - Infected - Recovered), and a probabilistic state model, also known as "multi-state". The model was then parameterized using the dataset published by the Italian Government through the Civil Protection and the Istituto Superiore di Sanità. Leveraging the identified parameters, we estimated the total amount of ICU hospital, non-ICU hospital and home isolation days that needed to extinguish a single-wave pandemic. Then we proceeded estimating the related hospital costs in the ongoing pandemic management strategy. We furthermore analyzed different scenarios that can be useful to assess choices the Government could adopt to face unforeseen events and outlined a way to exploit the results of the model (and in particular, the total amount of home isolation days and the overall timespan of the pandemic wave). These considerations represent a first step to assess the overall direct impact on Gross Domestic Product (GDP) of the pandemic. | ||
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