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Olabode, Damilola; Culp, Jordan; Fisher, Allison; Tower, Angela; Hull-Nye, Dylan; Wang, Xueying

Deterministic and stochastic models for the epidemic dynamics of COVID-19 in Wuhan, China. (English) Zbl 1471.92340

Math. Biosci. Eng. 18, No. 1, 950-967 (2021).
This paper develops deterministic and stochastic models to investigate the evolution of the COVID-19 in short term and in long term. The paper relies on SEIR model and performs analyses on the local and global dynamics of the ordinary differential equation with constant parameters. The stochastic model is also formulated with a theoretical estimate of the probability of disease extinction. Parameter estimation is conducted to fit the publicly reported data and numerical simulations of deterministic and stochastic models is done. In particular, it is shown that the basic reproduction number \(R_0\) is a sharp disease threshold, where the disease dies out if \(R_0\le1\) and persists if \(R_0>1\). It is revealed that if the non-pharmaceutical interventions were not implemented properly, the second wave is likely to happen at that time.
Reviewer: Yilun Shang (Newcastle)

Cited in 4 Documents

MSC:

92D30 Epidemiology

Keywords:

COVID-19; SEIR model; ODE model; CTMC model; disease extinction; disease outbreak; second wave

Software:

GitHub
Cite Review PDF
Full Text: DOI
OA License

References:

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