ArticleNonlinear dynamics2021
Dynamics of COVID-19 transmission with comorbidity: a data driven modelling based approach.
Article in Nonlinear dynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 42 citations in OpenAlex.
- Targeted epidemic mitigation through age-specific dose-response recovery modeling.BMC infectious diseases · 2026Article
- Dynamics of an SEIDW epidemic model for primary amebic meningoencephalitis threshold analysis, bifurcation, and optimal environmental control.Frontiers in public health · 2026Article
- Modelling the dynamically consistent numerical methods for COVID-19 disease with cost effectiveness strategies.Scientific reports · 2025Article
- Revisiting the complex time-varying effect of non-pharmaceutical interventions on COVID-19 transmission in the United States.Frontiers in public health · 2024Article
- The impact of comorbidities and economic inequality on COVID-19 mortality in Mexico: a machine learning approach.Frontiers in big data · 2024Article
- High-income ZIP codes in New York City demonstrate higher case rates during off-peak COVID-19 waves.Frontiers in public health · 2024Article
- Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive.Mathematics and computers in simulation · 2023Article
- Modelling policy combinations of vaccination and transmission suppression of SARS-CoV-2 in Rio de Janeiro, Brazil.Infectious Disease Modelling · 2022Article
- Is Peracetic Acid Fumigation Effective in Public Transportation?International journal of environmental research and public health · 2022Article
- Dynamics and control of delayed rumor propagation through social networks.Journal of applied mathematics & computing · 2022Article
- Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model.Nonlinear dynamics · 2022Article
- Dynamics of Caputo Fractional Order SEIRV Epidemic Model with Optimal Control and Stability Analysis.International journal of applied and computational mathematics · 2022Article
- Study of COVID-19 epidemiological evolution in India with a multi-wave SIR model.Nonlinear dynamics · 2022Article
- A multicompartment mathematical model to study the dynamic behaviour of COVID-19 using vaccination as control parameter.Nonlinear dynamics · 2022Article
- Estimation of exogenous drivers to predict COVID-19 pandemic using a method from nonlinear control theory.Nonlinear dynamics · 2021Article
- Mathematical model of COVID-19 with comorbidity and controlling using non-pharmaceutical interventions and vaccination.Nonlinear dynamics · 2021Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
An outbreak of the COVID-19 pandemic is a major public health disease as well as a challenging task to people with comorbidity worldwide. According to a report, comorbidity enhances the risk factors with complications of COVID-19. Here, we propose and explore a mathematical framework to study the transmission dynamics of COVID-19 with comorbidity. Within this framework, the model is calibrated by using new daily confirmed COVID-19 cases in India. The qualitative properties of the model and the stability of feasible equilibrium are studied. The model experiences the scenario of backward bifurcation by parameter regime accounting for progress in susceptibility to acquire infection by comorbidity individuals. The endemic equilibrium is asymptotically stable if recruitment of comorbidity becomes higher without acquiring the infection. Moreover, a larger backward bifurcation regime indicates the possibility of more infection in susceptible individuals. A dynamics in the mean fluctuation of the force of infection is investigated with different parameter regimes. A significant correlation is established between the force of infection and corresponding Shannon entropy under the same parameters, which provides evidence that infection reaches a significant proportion of the susceptible.
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