Abstract
This study presents a dynamic modeling framework that combines epidemiological and Input-Output analyses to evaluate the impact of a pandemic on essential occupational sectors in a nation and to assess the downstream consequences of the unavailability of essential workforce, due to the presence of interdependency relations among infrastructures or sectors. In particular, the proposed approach relies on a compartmental SIR epidemiological model that considers different age classes. Based on such a model, the amount of unavailable essential workforce due to the pandemics is identified and fed into a Dynamic Inoperability Input-Output model (D-IIM), which in turn provides the dynamics of the degree of inoperability of the different sectors due to both the initial perturbation caused by the lack of essential workforce and to the effect of interdependency relations. The potential of the framework is demonstrated via a proof-of-concept simulation analysis for a scenario in Italy at the beginning of the COVID-19 pandemic, considering realistic data.
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Bartolucci, S., Setola, R., Scala, A., Panzieri, S., Oliva, G. (2024). Assessing the Effect of the Lack of Essential Workforce on the Economic Sectors During a Pandemic. In: Pickl, S., Hämmerli, B., Mattila, P., Sevillano, A. (eds) Critical Information Infrastructures Security. CRITIS 2023. Lecture Notes in Computer Science, vol 14599. Springer, Cham. https://doi.org/10.1007/978-3-031-62139-0_2
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