SEIR Subregion Model Analysis: a case study of Curitiba



Covid-19, SEIR models, subregion models, hospital capacity, health system, epidemic models


The novel coronavirus SARS-CoV-2 was identified first on December 30, 2019, in Wuhan City, China. In a short time period thousands of infectious cases were reported in the world, and the hospital capacity was exceeded or saturated in some countries. For this reason, mathematical models were largely proposed to estimate the progression of Covid-19 sicky and its impact in decisions to mitigate this progression. This paper propose a modified “Susceptible Exposed Infectious Recovered” (SEIR) model to describe the comportment of the Covid-19 epidemic, based in characteristics of subregions. It was applicated in data of city of Curitiba, Brazil and showed the best and worst scenarios to estimate the saturate and exceeded states on health system.

Author Biographies

G. V. Loch, Federal University of Paraná

Gustavo Valentim Loch is PhD (2014) and Master (2010) in Operational Research at UFPR. Graduated in Industrial Mathematics (2007) at UFPR. Works on the following themes: Combinatorial Optimization, Transport Problem and Quality Engineering.

C. T. Scarpin, Federal University of Paraná

Cassius Tadeu Scarpin is PhD (2012) and Master (2007) in Operational Research at UFPR. He graduated in Mathematics (2002) and in Production Engineering (2010). Has experience in Production Engineering, with an interest in Operations Research and Logistics.


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