A mathematical model for the co-dynamics of COVID-19 and tuberculosis

Ojo, Mayowa M.; Peter, Olumuyiwa James; Goufo, Emile Franc Doungmo; Nisar, Kottakkaran Sooppy

doi:10.1016/j.matcom.2023.01.014

Cited by 23 publications

(7 citation statements)

References 60 publications

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“…There was an exponential increase in the death rate during the dominance of the delta variant and before the initiation of the booster shot program. Also, the co-dynamical properties of COVID-19 and tuberculosis have been investigated in [17] , and a deterministic inversion reproduction of the two infectious diseases were obtained. Using numerical simulation of the fitted datasets, they reported that COVID-19 incidence increased with co-infection prevalence, as the burden of tuberculosis on the human population increased.…”

Section: Fig 1 Investigational Treatment Approaches Of Covid-19mentioning

confidence: 99%

Mathematical Modelling and Computational Dynamics of the impact of Quasi-Lockdown Policy in Control of COVID-19 in Akwa Ibom State, Nigeria

Joshua,

Akpan,

Inyang

2024

ARJOM

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Determining the impact of a local control strategy, implemented to curtail the spread of COVID-19 has become obligatory to enable policy makers to combat the so-called long covid. This research used a deterministic SEIAHR-model, incorporating a logistic function to investigate the effect of quasi-lockdown policy during reemergence of corona virus pandemic. The notion of uniform convergence and fixed point theory were used to establish positive invariant region, ultimate boundedness, and existence of unique solution of the model. Nonlinear dynamical behaviours of the model such as stability and oscillating flows occurred at the disease free, and endemic equilibrium points. Using centre manifold theory, a trans-critical bifurcation with hysteresis effect were established, when quasi-lockdown policy was used as a control parameter in the model. A forward sensitivity analysis was conducted to unfold parameters that contributed significantly towards the spread and control of the infection. These parameters were estimated and fitted using least square technique, comparative to the observed real datasets adapted from the Nigeria Centre for Disease Control (NCDC). The polynomial regression model fitted the observed datasets with an average coefficient of determination given as R2 = 0.94. Simulations in form of phase space diagrams were used to validate the theoretic results. Epidemiologically, the model demonstrated that quasi-lockdown policy was necessarily a strategic policy to curb the spread of the infection, but not sufficient to eradicate the disease as the disease persisted endemically. It was shown that the basic reproduction number of the infection was within the critical threshold (R0 \(\le\) 1), when the lockdown policy was enforced strictly, but otherwise on relaxation of the lockdown policy (R0 \(\ge\) 1) Thus a relaxation of the quasi-lockdown policy leads to increase in susceptibility of the populace as the infection risk ratio increases in the model. Similarly, the model predicted that a pre-mature lifting of the lockdown policy could have led to high infectivity on the susceptible class and disastrous to healthy living of the citizens.

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Section: Fig 1 Investigational Treatment Approaches Of Covid-19mentioning

confidence: 99%

Mathematical Modelling and Computational Dynamics of the impact of Quasi-Lockdown Policy in Control of COVID-19 in Akwa Ibom State, Nigeria

Joshua,

Akpan,

Inyang

2024

ARJOM

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“…This models a loss of immunity over time. This work took motivation from recent work on stochastic modeling and infectious diseases models as discussed by [26][27][28][29][30][31][32] . The stochastic model is given by…”

Section: Withmentioning

confidence: 99%

A stochastic approach for co-evolution process of virus and human immune system

Ain,

Shen,

et al. 2024

Sci Rep

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Infectious diseases have long been a shaping force in human history, necessitating a comprehensive understanding of their dynamics. This study introduces a co-evolution model that integrates both epidemiological and evolutionary dynamics. Utilizing a system of differential equations, the model represents the interactions among susceptible, infected, and recovered populations for both ancestral and evolved viral strains. Methodologically rigorous, the model’s existence and uniqueness have been verified, and it accommodates both deterministic and stochastic cases. A myriad of graphical techniques have been employed to elucidate the model’s dynamics. Beyond its theoretical contributions, this model serves as a critical instrument for public health strategy, particularly predicting future outbreaks in scenarios where viral mutations compromise existing interventions.

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“…Similarly, Moualeu et al [33] investigated the influence of diabetes mellitus on the transmission of TB among both diabetic and non-diabetic groups. Additionally, Ojo et al [36] developed and examined a deterministic model for the co-dynamics of COVID-19 and TB, and demonstrated the necessary conditions for the coexistence or elimination of both diseases in the population.…”

Section: Introductionmentioning

confidence: 99%

Exploring a Mathematical Model with Saturated Treatment for the Co-dynamics of Tuberculosis and Diabetes

Rasheed,

Iyiola,

Oke

et al. 2024

Preprint

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In this research, we present a deterministic epidemiological mathematical model that delves into the intricate dynamics of the co-existence of tuberculosis and diabetes. Our comprehensive analysis explores the interplay and the influence of diabetes on tuberculosis incidence within a human population segregated into diabetic and non-diabetic subgroups. The model incorporates saturated incidence rates and treatment regimens for latent tuberculosis infections, offering insights into their impact on tuberculosis control. Theoretical findings reveal the emergence of a phenomenon known as backward bifurcation, attributed to exogenous reinfection and saturated treatment. Additionally, our study employs both local and global sensitivity analyses to identify pivotal parameters crucial to the spread of tuberculosis within the population. This investigation contributes valuable insights to the understanding of the complex relationship between tuberculosis and diabetes, offering a foundation for more effective disease control strategies. 2020 MSC classification: 34A34, 92D30, 92B05, 65H10.

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A mathematical model for the co-dynamics of COVID-19 and tuberculosis

Cited by 23 publications

References 60 publications

Mathematical Modelling and Computational Dynamics of the impact of Quasi-Lockdown Policy in Control of COVID-19 in Akwa Ibom State, Nigeria

Mathematical Modelling and Computational Dynamics of the impact of Quasi-Lockdown Policy in Control of COVID-19 in Akwa Ibom State, Nigeria

A stochastic approach for co-evolution process of virus and human immune system

Exploring a Mathematical Model with Saturated Treatment for the Co-dynamics of Tuberculosis and Diabetes

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