journal article·2024-01-01Open access

A robust computational study for assessing the dynamics and control of emerging zoonotic viral infection with a case study: A novel epidemic modeling approach

Shuo Li, Saif Ullah, Samreen, Ihsan Ullah Khan, Salman A. AlQahtani, Muhammad Bilal Riaz

AIP Advances· Volume 14· Issue 1

Abstract

Fractional calculus and fractal theory remain significant tools in modeling complex real-world problems in biology and life science. In this study, we formulated a compartmental mathematical model using the Caputo fractional and fractal–fractional operators to study the dynamics and transmission of Nipah virus infection. Initially, the model is developed by a system of seven nonlinear ordinary differential equations that govern the dynamics of viral concentration, the flying fox, and the human populations. Furthermore, the model is restructured using more general modeling approaches based on fractional calculus and fractal theory to gain valuable insights into the dynamics of Nipah virus transmission. The necessary properties of the model, such as uniqueness and existence in both cases, were investigated, and possible equilibrium points with their existence were presented. The model parameters are estimated on the basis of the clinical epidemiology of the Nipah outbreak in Bangladesh, one of the most affected regions. The stability of the fractional model is studied by applying the Ulam–Hyers and Ulam–Hyers–Rassias stability conditions. Moreover, computational schemes for the model in fractional and fractal–fractional cases are developed using interpolation techniques. Finally, a detailed simulation was presented to validate the theoretical findings. We affirm that the present findings will help researchers incorporate advanced computational techniques in infectious disease modeling and control studies.
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Research context

OpenAlex topics: Fractional Differential Equations Solutions · Mathematical and Theoretical Epidemiology and Ecology Models · COVID-19 epidemiological studies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Mathematics and Data Sciences, Changji University 1 , Changji, Xinjiang 831100, People’s Republic of China

Department of Mathematics, University of Peshawar 2 , Peshawar 25000, Khyber Pukhtunkhwa, Pakistan

Department of Mathematics, Abdul Wali Khan University Mardan 3 , Mardan 23200, Khyber Pukhtunkhwa, Pakistan

Department of Mathematics, Institute of Numerical Sciences, Gomal University 4 , Dera Ismail Khan 29050, Khyber Pukhtunkhwa, Pakistan

Computer Engineering Department, College of Computer and Information Sciences, King Saud University 5 , Riyadh, Saudi Arabia

IT4Innovations, VSB – Technical University of Ostrava 6 , Ostrava, Czech Republic

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