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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
PubMed

Insights

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.

Keywords:
Backward bifurcationCOVID-19ComorbidityModel calibrationSensitivity analysisShannon entropy

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