Analysis and simulation of a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures: A case study of the outbreak in Urumqi, China in August 2022

Ting Zeng; Zhidong Teng; Ramziya Rifhat; Xiaodong Wang; Lei Wang; Kai Wang

doi:10.1016/j.idm.2023.03.004

Analysis and simulation of a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures: A case study of the outbreak in Urumqi, China in August 2022

Infect Dis Model. 2023 Jun;8(2):356-373. doi: 10.1016/j.idm.2023.03.004. Epub 2023 Mar 31.

Authors

Ting Zeng^{1

2}, Zhidong Teng², Ramziya Rifhat², Xiaodong Wang², Lei Wang², Kai Wang²

Affiliations

¹ College of Public Health, Xinjiang Medical University, Urumqi, 830017, PR China.
² Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, 830017, PR China.

Abstract

In this paper, a stochastic COVID-19 model with large-scale nucleic acid detection and isolation measures is proposed. Firstly, the existence and uniqueness of the global positive solution is obtained. Secondly, threshold criteria for the stochastic extinction and persistence in the mean with probability one are established. Moreover, a sufficient condition for the existence of unique ergodic stationary distribution for any positive solution is also established. Finally, numerical simulations are carried out in combination with real COVID-19 data from Urumqi, China and the theoretical results are verified.

Keywords: Extinction persistence in the mean; Numerical simulation; Stationary distribution; Stochastic COVID-19 model.