Stability analysis of fuzzy HTLV-I infection model: a dynamic approach

Bera, Sovan; Khajanchi, Subhas; Roy, Tapan Kumar

doi:10.1007/s12190-022-01741-y

Cited by 27 publications

(5 citation statements)

References 31 publications

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“…

{R}_u

is a critical measure in the context of COVID‐19 disease, representing the disease threshold quantity. It is the average number of secondary infections that arise from a single infected individual within a population of susceptible individuals, considering the demographic steady state with some susceptible individuals being vaccinated; see previous studies [18, 19]. In the following theorem, we use

{R}_u

to describe the stability of the DFE.…”

Section: Stability Analysis For Equilibriamentioning

confidence: 99%

Mathematical modeling and optimal control for COVID‐19 with population behavior

Al‐arydah

2023

Math Methods in App Sciences

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To describe the spread of COVID‐19, we develop a simple susceptible‐vaccinated‐infectious‐recovery (SVIR) model. The transmission rate in this model incorporates the impact of caution and sense of safety on the transmission rate, making it biologically valid. The biological validity of the model is demonstrated by proving that a positive bound solution exists for this model. We find a formula for the basic reproduction function and use it to discuss the local asymptotic stability of the disease‐free equilibrium (DFE). The existence of the endemic equilibrium (EE) is shown to be dependent not only on the basic reproduction number value but also on the level of caution. By fitting the model to COVID‐19 data from several countries, we estimate parameter values with 95% confidence intervals. Sensitivity analysis reveals that the time‐series solution is affected by both the level of caution and the sense of safety, indicating the importance of population behavior in disease spread. We introduce an optimal control problem for vaccination and show that the optimal strategy exists and is unique. Our simulations demonstrate that optimal vaccination is most effective for low sense of safety, leading to fewer infections and lower costs. For high levels of sense of safety, vaccines may have a negative impact, highlighting the importance of combining vaccination efforts with educational initiatives.

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“…

{R}_u

{R}_u

to describe the stability of the DFE.…”

Section: Stability Analysis For Equilibriamentioning

confidence: 99%

Mathematical modeling and optimal control for COVID‐19 with population behavior

Al‐arydah

2023

Math Methods in App Sciences

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“…Khajanchi et al [18,4] studied brain tumor and fuzzy HTLV-I infection model. The brain tumor model analysed with Immune System interactions.…”

Section: Introductionmentioning

confidence: 99%

Dynamical Analysis of Stochastic Predator-prey Model with Scavenger

Prasad,,

Kumar,

2024

MJMS

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In this paper, we studied the dynamic properties of predator-prey and scavenger three species system by using ergodic invariant measures. Pengyu Ma. find the five points of dynamical bifurcation of the stochastic model, which happened between extinction and survival of each species. Environmental noise was added and proved by the fact that driving force produced by environmental noise influence the system and it was find that system may extinct or partially extinct. Here, we have analysed the stochastic bifurcation phenomena of the prey-predator with scavenger system from the nature of dynamic bifurcation. The phase plots and time diagram plotted for the different values of parameters. We have verified all the results by numerical simulations.

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“…The ongoing novel coronavirus has started at the end of December 2019, various mathematical models have been studied by several authors to describe successful ways to combat against COVID-19 pandemic [17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36].…”

Section: Introductionmentioning

confidence: 99%

How do the contaminated environment influence the transmission dynamics of COVID-19 pandemic?

Sarkar

Mondal

Khajanchi

2022

Eur. Phys. J. Spec. Top.

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COVID-19 is an infectious disease caused by the SARS-CoV-2 virus that first appeared in Wuhan city and then globally. The COVID-19 pandemic exudes public health and socio-economic burden globally. Mathematical modeling plays a significant role to comprehend the transmission dynamics and controlling factors of rapid spread of the disease. Researchers focus on the human-to-human transmission of the virus but the SARS-CoV-2 virus also contaminates the environment. In this study we proposed a nonlinear mathematical model for the COVID-19 pandemic to analyze the transmission dynamics of the disease in India. We have also incorporated the environment contamination by the infected individuals as the population density is very high in India. The model is fitted and parameterized using daily new infection data from India. Analytical study of the proposed COVID-19 model, including feasibility of critical points and their stability reveals that the infection-free steady state is stable if the basic reproduction number is less than unity otherwise the system shows significant outbreak. Numerical illustrations demonstrates that if the rate of environment contamination increased then the number of infected persons also increased. But if the environment is disinfected by sanitization then the number of infected persons cannot drastically increase.

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Stability analysis of fuzzy HTLV-I infection model: a dynamic approach

Cited by 27 publications

References 31 publications

Mathematical modeling and optimal control for COVID‐19 with population behavior

Mathematical modeling and optimal control for COVID‐19 with population behavior

Dynamical Analysis of Stochastic Predator-prey Model with Scavenger

How do the contaminated environment influence the transmission dynamics of COVID-19 pandemic?

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