Prediction of bifurcations by varying critical parameters of COVID-19
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ORIGINAL PAPER
Prediction of bifurcations by varying critical parameters of COVID-19 Fahimeh Nazarimehr . Viet-Thanh Pham . Tomasz Kapitaniak
Received: 25 April 2020 / Accepted: 4 June 2020 Ó The Author(s) 2020
Abstract Coronavirus disease 2019 is a recent strong challenge for the world. In this paper, an epidemiology model is investigated as a model for the development of COVID-19. The propagation of COVID-19 through various sub-groups of society is studied. Some critical parameters, such as the background of mortality without considering the disease state and the speed of moving people from infected to resistance, affect the conditions of society. In this paper, early warning indicators are used to predict the bifurcation points in the system. In the interaction of various sub-groups of society, each sub-group can have various parameters. Six cases of the sub-groups interactions are studied. By coupling these sub-groups, F. Nazarimehr Biomedical Engineering Department, Amirkabir University of Technology, Tehran 15875-4413, Iran V.-T. Pham (&) Faculty of Electrical and Electronic Engineering, Phenikaa Institute for Advanced Study (PIAS), Phenikaa University, Yen Nghia, Ha Dong district, Hanoi 100000, Vietnam e-mail: [email protected] V.-T. Pham Phenikaa Research and Technology Institute (PRATI), A&A Green Phoenix Group, 167 Hoang Ngan, Hanoi 100000, Vietnam V.-T. Pham T. Kapitaniak Division of Dynamics, Lodz University of Technology, Stefanowskiego 1/15, 90-924 Lodz, Poland
various dynamics investigated. Keywords Coupling
of
the
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society
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SEIR model Bifurcation Prediction
1 Introduction Recently, many countries are dealing with coronavirus disease 2019 (COVID-19). COVID-19 is a dangerous disease with many death cases in many countries [1, 2]. COVID-19 causes respiratory illness and many other symptoms. The disease was first detected in Wuhan, China. Soon after that, it was seen in many other countries [3]. The study of epidemic outbreak in infectious disease is an interesting topic. Modeling of various biological and social facts has been a hot topic for many years [4–7]. Various methods have been used to model infectious diseases [8]. Compartmental models are useful tools in the modeling of such diseases [9, 10]. One of those models is the SEIR model. This model consists of four individuals, susceptible, exposed, infected, and resistant. This model is popular in the studies of epidemiology [11]. Many studies have been done in the modeling of COVID-19 [12]. Recently, the SEIR model has been used in [13–15]. In [16], the SIR model is used to investigate COVID-19 behavior. The prediction of COVID-19 is done in [17].
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Predicting bifurcation points of the dynamical disease are important [18, 19]. Many types of research have been done to predict the bifurcation points of biological systems [19, 20]. There are some evidences that near the bifurcation points of a dynamical system, the dynamic becomes slo
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