Academic Journal of Computing & Information Science, 2021, 4(2); doi: 10.25236/AJCIS.2021.040204.

## Mathematical Modeling and Analysis of COVID-19 Epidemic Situation Based on Markov Chain

Author(s)

Zixi Zhao, Longqiao Liu, Songen Ma

Corresponding Author:
Zixi Zhao
Affiliation(s)

The Third Department of China Medical University, Shenyang, Liaoning, 110122

### Abstract

Based on the statistical data of COVID-19 from January 22, 2020 to June 7, 2020 in Hubei, China, the states are divided according to the standard deviation, and based on the Markov chain theory, the mathematical analysis model of daily confirmed, dead and cured number of COVID-19 in Hubei, China was established, and the probability of steady distribution of each state and the average return time were used to analyze the prevention and control of COVID-19 epidemic situation in Hubei, China. The analysis shows that by June 2020, the daily confirmed number of COVID-19 in Hubei, China is basically in state Ⅰ, the number of daily deaths is basically in state Ⅰ-Ⅱ, and the number of people cured per day is basically in state Ⅰ-Ⅱ.

### Keywords

Markov chain, COVID-19 epidemic situation, Mathematical modeling

### Cite This Paper

Zixi Zhao, Longqiao Liu, Songen Ma. Mathematical Modeling and Analysis of COVID-19 Epidemic Situation Based on Markov Chain. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 2: 20-23. https://doi.org/10.25236/AJCIS.2021.040204.

### References

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