Evidence map›Paper›PMID 40118920›Full record

ArticleScientific reports2025

A numerical study on the dynamics of SIR epidemic model through Genocchi wavelet collocation method.

Darshan Kumar Chiranahalli Vijaya, Prakasha Doddabhadrappla Gowda, Balachandra Hadimani

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Darshan Kumar Chiranahalli VijayaDepartment of Mathematics, Davangere University, Shivagangotri, Davangere, 577007, India.
Prakasha Doddabhadrappla GowdaDepartment of Mathematics, Davangere University, Shivagangotri, Davangere, 577007, India.
Balachandra HadimaniDepartment of Mathematics, Manipal Academy of Higher Education, Manipal Institute of Technology, Manipal, 576104, India. bs.hadimani@manipal.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epidemic models can play a major role in understanding the spread of diseases and their control. These mathematical models have plenty of significance in various scientific domains, including public health, to investigate disease propagation and ecology. This article explains the dynamics of SIR epidemic model of arbitrary order with aid of a precise numerical approach called Genocchi wavelet collocation method. The main purpose of this investigation is to explore and discover the results for system of nonlinear ordinary differential equations arising in the considered mathematical model and to investigate the dynamical aspects of SIR model via Caputo fractional derivative which is non-local in behaviour. The projected method depicts rapid algorithms and is extremely precise, reliable, and uses fewer computational resources. Also, this method is simpler than the other traditional numerical methods as it merges the operational matrix with the collocation method in order to transform fractional-order problem into algebraic equations which enables to obtain satisfactory results. The approximate solution obtained using proposed algorithm exposes the nature of their interactions. Furthermore, the numerical outcomes are represented through graphs for different fractional order and compared the results with Runge-Kutta method and residual power series method. The projected technique is very effective, accurate, free from controlling parameters and consume less time to investigate nonlinear complications arising in diverse fields of epidemical and biological models. Ultimately, the current study help to inspect the wild class of models and their performance which are occurring in real world.

Indexed as

Communicable DiseasesEpidemicsEpidemiological ModelsModels, TheoreticalAlgorithmsHumansWavelet AnalysisCaputo fractional derivativeEpidemic modelFractional differential equationGenocchi wavelets

Identifiers

PMID40118920
PMCPMC11928466

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