SEIR Subregion Model Analysis: a case study of Curitiba
The novel coronavirus SARS-CoV-2 was identified first in December of 2019, in Wuhan City, China. In a short 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 propo...
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| Veröffentlicht in: | Revista IEEE América Latina 2021-06, Vol.19 (6), p.1050-1056 |
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| creator | Spengler, Hellen Cristina Valentim Loch, Gustavo Tadeu Scarpin, Cassius |
| description | The novel coronavirus SARS-CoV-2 was identified first in December of 2019, in Wuhan City, China. In a short 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 pandemic and its impact on decisions to mitigate this progression. This paper proposes a modified Susceptible Exposed Infectious Recovered (SEIR) model to describe the behavior of the Covid-19 epidemic, based on characteristics of subregions. It was applied in data of the city of Curitiba, Brazil, and showed the best and worst scenarios to estimate the saturate and exceeded states on the health system. |
| doi_str_mv | 10.1109/TLA.2021.9451251 |
| format | Article |
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| subjects | Analytical models Coronaviruses COVID-19 epidemic models health system hospital capacity Hospitals IEEE transactions Mathematical models SEIR models Severe acute respiratory syndrome coronavirus 2 Solid modeling subregion models Urban areas Viral diseases |
| title | SEIR Subregion Model Analysis: a case study of Curitiba |
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