Version 1
: Received: 3 April 2020 / Approved: 7 April 2020 / Online: 7 April 2020 (01:13:15 CEST)
Version 2
: Received: 5 May 2020 / Approved: 5 May 2020 / Online: 5 May 2020 (16:10:48 CEST)
Godio, A.; Pace, F.; Vergnano, A. SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. Int. J. Environ. Res. Public Health2020, 17, 3535.
Godio, A.; Pace, F.; Vergnano, A. SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. Int. J. Environ. Res. Public Health 2020, 17, 3535.
Godio, A.; Pace, F.; Vergnano, A. SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. Int. J. Environ. Res. Public Health2020, 17, 3535.
Godio, A.; Pace, F.; Vergnano, A. SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. Int. J. Environ. Res. Public Health 2020, 17, 3535.
Abstract
We applied a generalized SEIR epidemiological model to the recent SARS-CoV-2 outbreak in the world, with a focus on Italy and its Lombardia, Piemonte, and Veneto regions. We focus on the application of a stochastic approach in fitting the model numerous parameters using a Particle Swarm Optimization (PSO) solver, to improve the reliability of predictions in the medium term (30 days). We analyze the official data and the predicted evolution of the epidemic in the Italian regions, and we compare the results with data and predictions of Spain and South Korea. We link the model equations to the changes in people’s mobility, with reference to Google’s COVID-19 Community Mobility Reports. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.
Keywords
SARS-CoV-2; COVID-19; SEIR modeling; Italy; stochastic modeling; swarm intelligence; Google COVID 19 Community Mobility Reports
Subject
Computer Science and Mathematics, Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
5 May 2020
Commenter:
Andrea Vergnano
Commenter's Conflict of Interests:
Author
Comment:
This is the result of a major revision after the first peer revision of MDPI journal Interational Journal of Environmental Research and Public Health.
Commenter: Andrea Vergnano
Commenter's Conflict of Interests: Author