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Dynamical Analysis of COVID-19 Model Incorporating Environmental Factors
Preety Kumari1,2, Swarn Singh3, Harendra Pal Singh4
1Faculty of Mathematical Science, University of Delhi, Delhi, 110007 India.
Iranian Journal of Science and Technology. Transaction A, Science
|December 5, 2022
Summary
This study models coronavirus transmission in India using an extended SEIAQRDT mathematical model, incorporating environmental factors and asymptomatic cases. The model analyzes disease dynamics and equilibrium points, validating findings with data from India and Italy.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- The COVID-19 pandemic presents significant global challenges, with India being a major concern in Asia.
- Mathematical modeling is crucial for understanding and predicting the spread of novel coronaviruses.
Purpose of the Study:
- To extend the SEIAQRDT mathematical model by incorporating environmental transmission to analyze coronavirus spread in India.
- To investigate the impact of asymptomatic populations, quarantine measures, and environmental factors on COVID-19 transmission dynamics.
Main Methods:
- Development and analysis of an extended SEIAQRDT mathematical model.
- Theoretical calculation and analytical bifurcation analysis of the basic reproduction number ().
- Establishing the existence and stability of disease-free equilibrium (DFE) and endemic equilibrium (EE) points.
Main Results:
- The study analyzes the influence of environmental factors on COVID-19 pandemic spread.
- The model's predictions were compared with real-world data for India and Italy, showing good agreement.
- Key epidemiological parameters, including the basic reproduction number, were theoretically determined.
Conclusions:
- The extended mathematical model provides valuable insights into coronavirus transmission dynamics, especially considering environmental factors.
- The findings support the significance of asymptomatic individuals, quarantine, and environmental transmission in controlling the pandemic.
- The model's validation with data from India and Italy suggests its applicability for understanding and managing outbreaks in diverse settings.
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