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Dynamics of COVID-19 transmission with comorbidity: a data driven modelling based approach
Parthasakha Das1, Sk Shahid Nadim2, Samhita Das1
1Department of Mathematics, Indian Institute of Engineering Science and Technology, Shibpur, Howrah 711103 India.
Nonlinear Dynamics
|March 15, 2021
Summary
This study models COVID-19 transmission dynamics in individuals with comorbidity. Findings reveal backward bifurcation, indicating increased infection risk for susceptible populations with comorbidities.
Area of Science:
- Epidemiology
- Mathematical Biology
- Public Health
Background:
- The COVID-19 pandemic poses significant challenges, particularly for individuals with comorbidities.
- Comorbidity is known to exacerbate COVID-19 complications and increase risk factors.
Purpose of the Study:
- To develop and analyze a mathematical framework for understanding COVID-19 transmission dynamics in populations with comorbidities.
- To calibrate the model using daily confirmed COVID-19 cases in India and investigate its qualitative properties.
Main Methods:
- Development of a mathematical transmission model incorporating comorbidity.
- Calibration of the model with real-world data on daily confirmed COVID-19 cases in India.
- Analysis of model stability, equilibrium points, and bifurcation scenarios.
Main Results:
- The model demonstrates a backward bifurcation, suggesting heightened susceptibility to infection among individuals with comorbidities.
- Asymptotic stability of the endemic equilibrium is observed when comorbidity recruitment outpaces infection acquisition.
- A larger backward bifurcation regime correlates with increased infection prevalence in susceptible individuals.
Conclusions:
- Comorbidity significantly influences COVID-19 transmission dynamics, potentially increasing infection risk.
- Mathematical modeling provides valuable insights into disease spread and stability under varying comorbidity levels.
- A correlation between the force of infection and Shannon entropy suggests widespread infection among susceptible groups.
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