Construction of a Computational Scheme for the Fuzzy HIV/AIDS Epidemic Model with a Nonlinear Saturated Incidence Rate

Abstract

This work aimed to construct an epidemic model with fuzzy parameters. Since the classical epidemic model does not elaborate on the successful interaction of susceptible and infective people, the constructed fuzzy epidemic model discusses the more detailed versions of the interactions between infective and susceptible people. The next-generation matrix approach is employed to find the reproduction number of a deterministic model. The sensitivity analysis and local stability analysis of the system are also provided. For solving the fuzzy epidemic model, a numerical scheme is constructed which consists of three time levels. The numerical scheme has an advantage over the existing forward Euler scheme for determining the conditions of getting the positive solution. The established scheme also has an advantage over existing non-standard finite difference methods in terms of order of accuracy. The stability of the scheme for the considered fuzzy model is also provided. From the plotted results, it can be observed that susceptible people decay by rising interaction parameters.

Introduction to the Special Issue on Recent Developments on Computational Biology-I

“…Also, they presented the conditions of existence for a solution to the proposed epidemic model and calculated the reproduction number in certain state Conditions of the analyzed dynamic system. In [12], authors constructed an epidemic model with fuzzy parameters. Since the classical epidemic model does not elaborate on the successful interaction of susceptible and infective people, the constructed fuzzy epidemic model discusses the more detailed versions of the interactions between infective and susceptible people.…”

A Third-order Two Stage Numerical Scheme and Neural Network Simulations for SEIR Epidemic Model: A Numerical Study

“…Our investigation into a higher-order method is driven by the deficiencies of traditional numerical systems like those found in Hussain et al [3] and Arif et al [4]. During the pivotal stages of an epidemic, when accuracy is crucial for making educated decisions, our third-order, two-stage numerical technique strives to improve the precision of simulations using the SEIR model.…”

Modelling Infectious Disease Dynamics: A Robust Computational Approach for Stochastic SIRS with Partial Immunity and an Incidence Rate

“…Using it, we may better manage infectious disease outbreaks, distribute scarce resources, and prepare for emergencies, all of which improve public health and lessen these crises' toll on the world's population. Upon the conclusion of this project, it is possible to propose further applications for the existing strategy [54][55][56]. This model will continue to be at the forefront of attempts to address the ever-changing environment of infectious illnesses as research in this field develops.…”