Fuzzy Approach Analyzing SEIR-SEI Dengue Dynamics

Bhuju, Gauri; Phaijoo, Ganga Ram; Gurung, Dil Bahadur

doi:10.1155/2020/1508613

Cited by 20 publications

(13 citation statements)

References 21 publications

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“…We analyzed the model of the spread of the amoebiasis virus for a general class of parameters taken from the scientific literature in this study. The execution of these findings on real-time data is our future research plan as presented in [47][48][49].…”

Section: Discussionmentioning

confidence: 99%

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New Trends in Fuzzy Modeling Through Numerical Techniques

Alqarni¹,

Rafiq²,

Dayan³

et al. 2023

Computers, Materials &Amp; Continua

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Amoebiasis is a parasitic intestinal infection caused by the highly pathogenic amoeba Entamoeba histolytica. It is spread through person-toperson contact or by eating or drinking food or water contaminated with feces. Its transmission rate depends on the number of cysts present in the environment. The traditional models assumed a homogeneous and contradictory transmission with reality. The heterogeneity of its transmission rate is a significant factor when modeling disease dynamics. The heterogeneity of disease transmission can be described mathematically by introducing fuzzy theory. In this context, a fuzzy SEIR Amoebiasis disease model is considered in this study. The equilibrium analysis and reproductive number are studied with fuzziness. Two numerical schemes forward Euler method and a nonstandard finite difference (NSFD) approach, are developed for the learned model, and the results of numerical simulations are presented. The numerical and simulation results reveal that the proposed NSFD method provides an adequate representation of the dynamics of the disease despite the uncertainty and heterogeneity. Moreover, the obtained method generates plausible predictions that regulators can use to support decision-making to design and develop control strategies.

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Section: Discussionmentioning

confidence: 99%

“…The method developed in this work can be extended to delayed, stochastic, and fractional models in fuzzy environments. The idea can also be implemented in machine learning problems [47]. We analyzed the model of the spread of the amoebiasis virus for a general class of parameters taken from the scientific literature in this study.…”

Section: Discussionmentioning

confidence: 99%

New Trends in Fuzzy Modeling Through Numerical Techniques

Alqarni¹,

Rafiq²,

Dayan³

et al. 2023

Computers, Materials &Amp; Continua

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“…we use the membership function introduced firstly by L.C. de Barros [5] and used by G. Bhuju et al [4] and Renu Verma et al [22] defined as:…”

Section: The Fuzzy Seirs-sei Model For Malaria Transmissionmentioning

confidence: 99%

“…As said above, we consider the recovery rate h γ as a fuzzy variable depending on the amount of parasites ν . In this paper, we use the fuzzy recovery rate introduced by Renu Verma et al [22] and modified by G. Bhuju et al [4] as:…”

Section: The Fuzzy Seirs-sei Model For Malaria Transmissionmentioning

confidence: 99%

Fuzzy Global Stability Analysis of the Dynamics of Malaria with Fuzzy Transmission and Recovery Rates

Mangongo¹,

Bukweli²,

Kampempe³

2021

AJOR

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In this paper, fuzzy techniques have been used to track the problem of malaria transmission dynamics. The fuzzy equilibrium of the proposed model was discussed for different amounts of parasites in the body. We proved that when the amounts of parasites are less than the minimum amounts required for disease transmission ( min ν ν ≤ ), we reach the model disease-free equilibrium. Using Choquet integral, the fuzzy basic reproduction number through the expected value of fuzzy variable was introduced for the fuzzy Susceptible, Exposed, Infected, Recovered, susceptible-Susceptible, Exposed and Infected (SEIRS-SEI) malaria model. The fuzzy global stabilities were introduced and discussed. The disease-free equilibrium 0Y is globally asymptotically stable if min

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“…by solving the linear higher-order deformation Equation ( 15) using the well-known symbolic computation software such as Maple, Matlab, or Mathematica. Prediction and controlling the infection was studied in detail not only in [22] but also in other papers, for example [4,[23][24][25][26][27][28][29][30][31][32][33][34][35][36]. We discuss in the next section the homotopy analysis method.…”

Section: Lemma 3 ([20]mentioning

confidence: 99%

Numerical Solution of an Interval-Based Uncertain SIR (Susceptible–Infected–Recovered) Epidemic Model by Homotopy Analysis Method

Bakare

Chakraverty

Potůček

2021

Axioms

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This work proposes an interval-based uncertain Susceptible–Infected–Recovered (SIR) epidemic model. The interval model has been numerically solved by the homotopy analysis method (HAM). The SIR epidemic model is proposed and solved under different uncertain intervals by the HAM to obtain the numerical solution of the model. Furthermore, the SIR ODE model was transformed into a stochastic differential equation (SDE) model and the results of the stochastic and deterministic models were compared using numerical simulations. The results obtained were compared with the numerical solution and found to be in good agreement. Finally, various simulations were done to discuss the solution.

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Fuzzy Approach Analyzing SEIR-SEI Dengue Dynamics

Cited by 20 publications

References 21 publications

New Trends in Fuzzy Modeling Through Numerical Techniques

New Trends in Fuzzy Modeling Through Numerical Techniques

Fuzzy Global Stability Analysis of the Dynamics of Malaria with Fuzzy Transmission and Recovery Rates

Numerical Solution of an Interval-Based Uncertain SIR (Susceptible–Infected–Recovered) Epidemic Model by Homotopy Analysis Method

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