Computational solutions for fractional-order modeling of Visceral Leishmaniasis using Caputo derivatives.

A M Khan, S Gaur, D L Suthar, S D Purohit

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Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

A M KhanDepartment of Mathematics, Jodhpur Institute of Engineering & Technology, Jodhpur, India.

S GaurDepartment of Electronics and Communication, Jodhpur Institute of Engineering & Technology, Jodhpur, India.

D L SutharDepartment of Mathematics, Wollo University, Dessie, Amhara, Ethiopia. dl.suthar@wu.edu.et.

S D PurohitDepartment of HEAS (Mathematics), Rajasthan Technical University, Kota, Rajasthan, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, we explored novel fractional Visceral Leishmaniasis (VL) disease models with Caputo fractional derivatives. The computational solution of the fractional VL model is derived using the Generalized Euler's method (GEM). The compartment structure of the five-dimensional model includes susceptible, infected, public treatment, private treatment, and recovered classes. This study considers two treatment strategies: public and private. The fractional-order novel model was graphically simulated using MATLAB. Furthermore, the stability of the equilibrium points was investigated. The findings obtained using the proposed method are computationally efficient and easy to implement.

Indexed as

Leishmaniasis, VisceralModels, BiologicalAlgorithmsAnimalsComputer SimulationHumansCaputo fractional derivativeGeneralized Euler methodMittag-Leffler functionVisceral-Leishmaniasis

Identifiers

PMID42144413

DOI10.1038/s41598-026-50007-1

PMCPMC13377169

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LicenceCC BY-NC-ND

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.