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Dynamics of a stochastic COVID-19 epidemic model considering asymptomatic and isolated infected individuals

Jiying Ma1, Wei Lin1

  • 1College of Science, University of Shanghai for Science and Technology, Shanghai 200093, China.

Mathematical Biosciences and Engineering : MBE
|April 18, 2022
PubMed

Insights

This study analyzes a stochastic COVID-19 model with asymptomatic and isolated cases. Noise intensity in infections significantly impacts disease control, with implications for public health strategies.

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Stochastic Processes

Background:

  • The COVID-19 pandemic has had profound global public health and economic impacts since 2020.
  • Understanding disease dynamics, including asymptomatic and isolated cases, is crucial for effective control.
  • Stochastic modeling provides a framework to incorporate randomness in epidemic spread.

Purpose of the Study:

  • To develop and analyze a stochastic high-dimensional model for COVID-19 transmission.
  • To establish conditions for disease extinction and the existence of a stationary distribution.
  • To investigate the role of noise intensity in disease dynamics and control.

Main Methods:

  • Proving the existence and uniqueness of positive solutions for the stochastic differential equation model.
  • Deriving analytical conditions for the extinction and persistence of the disease.
  • Conducting numerical simulations to validate theoretical findings and compare with real-world data.

Main Results:

  • The existence and uniqueness of a positive solution to the stochastic COVID-19 model were demonstrated.
  • Conditions governing the extinction of the disease and the existence of a stationary distribution were established.
  • The intensity of noise, particularly on asymptomatic and symptomatic infections, was identified as a critical factor in disease control.

Conclusions:

  • The stochastic model provides valuable insights into COVID-19 dynamics, accounting for crucial factors like asymptomatic transmission.
  • Noise intensity is a key parameter that can be modulated to influence disease spread and achieve control.
  • The findings, supported by numerical simulations and comparison with Indian data, offer a basis for informed public health interventions.

Keywords:
COVID-19asymptomatic infectionsextinctionstationary distributionstochastic epidemic model

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