Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

SEIR Modeling of the Italian Epidemic of SARS-CoV-2

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)

A peer-reviewed article of this Preprint also exists.

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 Health 2020, 17, 3535.

Journal reference: International Journal of Environmental Research and Public Health 2020, 17
DOI: 10.3390/ijerph17103535

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, 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 their results also with data and predictions of Spain and South Korea. We discuss the effectiveness of policies taken by different regions and countries and how they have an impact on past and future infection scenarios.

Subject Areas

SARS-CoV-2; COVID-19; SEIR modeling; Italy; stochastic modeling; swarm intelligence

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