Analysis of a SEIR model measuring the impact of testing with application to the COVID-19 pandemic
J. Valero, J. L. Sainz-Pardo
We modify the epidemic SEIR model in such a way that the impact of tracing and random testing can be measured separately. The parameters of the model are time-dependent and are defined piecewise as they can change abruptly due to the impact of governmental actions.
We make a qualitative analysis of the model in the case where the coefficients are constants. We prove that the limit number of susceptible individuals is an increasing function of the parameters of tracing and testing. After that we carry out numerical simulations, estimating first the parameters of the model during the first wave of the COVID-19 epidemic in Spain if no massive testing is used. After that we study the evolution of the epidemic when a constant number of tests is carried out each day, calculating the number of infected individuals who are saved in the long term for several values for the parameters which characterize tracing and testing.
We also measure the impact of vaccination.
Keywords: Epidemic nodel, SEIR model, COVID-19, testing
Scheduled
Invited Session Contributions of Statistics and Operations Research to COVID-19 II
June 10, 2022 4:00 PM
Auditorium
Other papers in the same session
A. Mateos Caballero, E. Vicente Cestero, A. Jiménez Martín, H. Muñoz García, P. Sánchez Escalonilla, J. García Moreno
G. Gomez Melis, C. Tebé Cordomí
J. L. Sainz-Pardo Auñón, J. Valero
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6/8/22
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5/31/22
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5/27/22
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5/23/22
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5/16/22
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