Epidemic threshold of a COVID-19 model with gaussian white noise and semi-Markov switching
Qianqian Sun1,2, Dejun Tan1, Shuwen Zhang1,2
1Xiamen Institute of Technology, China.
Abstract:
In this study, we investigate the COVID-19 propagation dynamics using a stochastic SIQR model with Gaussian white noise and semi-Markovian switching, focusing on the impacts of Gaussian white noise and semi-Markovian switching on the propagation dynamics of COVID-19. It is suggested that the fate of COVID-19 is entirely determined by the basic reproduction number , under mild extra conditions. By making sensitivity analysis on , we found that the effect of quarantine rate on was more significant compared to transmission rate. Our results demonstrate that: (i) The presence of Gaussian white noise, while reducing the basic reproduction number of COVID-19, also poses more challenges for the prediction and control of COVID-19 propagation. (ii) The conditional holding time distribution has a significant effect on the kinetics of COVID-19. (iii) The semi-Markov switching and Gaussian white noise can support irregular recurrence of COVID-19 outbreaks.
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