The management of COVID-19 epidemic: estimate of the actual infected population, impact of social distancing and directions for an efficient testing strategy. The case of Italy

Federico Brogi, Barbara Guardabascio and Giulio Barcaroli

International Journal of Computational Economics and Econometrics, 2022, vol. 12, issue 4, 342-365

Abstract: This work focuses on the so called 'first wave' of COVID-19 epidemic (21 February-10 April 2020) and aims at outlining a viable strategy to contain the COVID-19 spread and efficiently plan an exit from lockdown measures. It offers a model to estimate the total number of actual infected among the population at national and regional level inferring from the lethality rate, to fill the proven gap with the number of officially reported cases. The result is the reference population used to develop a forecasting exercise of new daily cases, compared to the reported ones. The eventual discrepancy is analysed in terms of compliance with the restrictive measures or to an insufficient number of tests performed. This simulation indicates that an efficient testing policy is the main actionable measure. Furthermore, the paper estimates the optimal number of tests to be performed at national and regional level, in order to be able to release an increasing number of individuals from restrictive measures.

Keywords: COVID-19; policy evaluation; scenario analysis; infected population; testing strategy; compliance; Italy. (search for similar items in EconPapers)
Date: 2022
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