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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F24%3A10253975" target="_blank" >RIV/61989100:27740/24:10253975 - isvavai.cz</a>

Výsledek na webu

<a href="https://pubs.aip.org/aip/adv/article/14/1/015051/3061514/A-robust-computational-study-for-assessing-the" target="_blank" >https://pubs.aip.org/aip/adv/article/14/1/015051/3061514/A-robust-computational-study-for-assessing-the</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1063/5.0188703" target="_blank" >10.1063/5.0188703</a>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10300 - Physical sciences

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

AIP Advances

ISSN

2158-3226

e-ISSN

2158-3226

Svazek periodika

14

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

28

Strana od-do

1-28

Kód UT WoS článku

001147174600005

EID výsledku v databázi Scopus

2-s2.0-85183057224