Abstract
The COVID-19 epidemic has recently led in Italy to the implementation of different external strategies in order to limit the spread of the disease in response to its transmission rate: strict national lockdown rules, followed first by a weakening of the social distancing and contact reduction feedback interventions and finally the implementation of coordinated intermittent regional actions, up to the application, in this last context, of an age-stratified vaccine prioritization strategy. This paper originally aims at identifying, starting from the available age-structured real data at the national level during the specific aforementioned scenarios, external-scenario-dependent sets of virulence parameters for a two-age-structured COVID-19 epidemic compartmental model, in order to provide an interpretation of how each external scenario modifies the age-dependent patterns of social contacts and the spread of COVID-19.
Highlights
COVID-19 (SARS-CoV-2) is at the root of the recent economic and public health crisis worldwide
By October 2020, over 36 million people were definitely reported to be infected with COVID-19 and more than one million people had died from virus-related complications
[10], which fit an age-structured mathematical model to epidemic data from China, Italy, Japan, Singapore, Canada and South Korea, shows that susceptibility to infection in individuals under 20 years of age is approximately half that in adults aged over 20 years, and that clinical symptoms manifest in 21% of infections in 10- to 19-year-olds, rising to 69% of infections in people aged over 70 years
Summary
COVID-19 (SARS-CoV-2) is at the root of the recent economic and public health crisis worldwide. Since it was reported in December 2019 in China, the virus quickly took pandemic proportions throughout six continents and over 210 countries. A method for the joint optimal lockdown and release design in a pandemic is proposed in [4] and applied in a realistic simulation scenario based on the data of COVID-19’s evolution in Italy. A dynamical model designed for COVID19 is used in [6] to describe the epidemic evolution in Italy, with different kinds of control actions (social, political, and medical) being explicitly modeled. A parameter-varying modification of the SIRD model is proposed in [7] for describing and predicting the behavior of the COVID-19 contagion in Italy through identification of model parameters, written as linear combinations of basis functions
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