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Stochastic SIRC epidemic model with time-delay for COVID-19.
F A Rihan1, H J Alsakaji1, C Rajivganthi2
1Department of Mathematical Sciences, College of Science, United Arab Emirates University, Al-Ain, 15551 UAE.
Advances in Difference Equations
|September 23, 2020
Summary
Environmental factors influence COVID-19 spread. Stochastic modeling reveals white noise can control disease spread, while time delays may cause re-infections and outbreaks.
Area of Science:
- Epidemiology
- Mathematical Biology
- Environmental Science
Background:
- COVID-19 transmission is influenced by environmental factors like temperature and humidity.
- Stochastic epidemic models are crucial for understanding disease dynamics.
Purpose of the Study:
- To analyze a stochastic SIRC model for COVID-19 spread incorporating environmental factors and time delays.
- To investigate the impact of stochasticity and time delays on disease dynamics and control.
Main Methods:
- Developed a stochastic SIRC model with cross-immunity and time-delayed transmission.
- Proved existence and uniqueness of positive global solutions.
- Deduced the basic reproduction number and analyzed conditions for disease extinction and stable distributions.
Main Results:
- The stochastic model's reproduction number is lower than its deterministic counterpart.
- Sufficient white noise can lead to disease extinction.
- Time delays in transmission can result in re-infections and periodic outbreaks.
Conclusions:
- Environmental factors significantly impact COVID-19.
- Stochasticity, particularly white noise, offers a potential control mechanism for COVID-19.
- Time delays introduce complexities like re-infection and cyclical outbreaks, necessitating careful consideration in epidemic management.
Keywords:
Brownian motionCOVID-19Cross-immunityExtinctionStationary distributionStochastic SIRC modelMore Related Videos
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