Evidence map›Paper›PMID 41851272›Full record

ArticleScientific reports2026

Dynamic behavior of a stochastic epidemic model for skin sores: theoretical and computational perspectives.

Ali Raza, Marek Lampart, Eugénio M Rocha, Dumitru Baleanu, Hala H Taha, Emad Fadhal

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Ali RazaIT4Innovations, VSB-Technical University of Ostrava , 17 Listopadu 2172/15, 708 33, Ostrava, Czech Republic. ali.raza@vsb.cz.
Marek LampartIT4Innovations, VSB-Technical University of Ostrava , 17 Listopadu 2172/15, 708 33, Ostrava, Czech Republic.
Eugénio M RochaDepartment of Mathematics, Center for Research and Development in Mathematics and Applications (CIDMA), University of Aveiro, 3810-193, Aveiro, Portugal.
Dumitru BaleanuDepartment of Computer Science and Mathematics, Lebanese American University, Beirut, 1102 2801, Lebanon.
Hala H TahaDepartment of Mathematical Sciences, College of Science, Princess Nourah bint Abdlrahman University, P. O. Box 84428, 11671, Riyadh, Saudi Arabia.
Emad FadhalDepartment of Mathematics and Statistics, College of Science, King Faisal University, 31982, Al Ahsa, Saudi Arabia. efadhal@kfu.edu.sa.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The present research work introduces a novel computational approach to the study of a nonlinear stochastic epidemic model for skin sores and also a deterministic model. Theoretical analyzing leads to establishing the existence, positive nature, and boundedness of solutions along with the local stability of equilibria. The application of multiple numeric methods including classical Euler, Runge-Kutta, and Euler-Maruyama methods as well as a stochastic nonstandard finite difference (NSFD) approach together with the model's dynamic behavior exploration is the main method of research for this project. The NSFD scheme stands out for its ability to give better precision and stability in numerical computations, besides being time-efficient and not dependent on the size of the time step. A complete comparison reveals the proposed scheme's capability and consistency in seizing both deterministic and stochastic dynamics of the epidemic system. The results of the study lead to a connection between theoretical analysis and practical computation and still give considerable understanding of the reliable simulations of stochastic epidemic processes.

Indexed as

EpidemicsModels, BiologicalAlgorithmsComputer SimulationHumansStochastic ProcessesComputational modelingNonstandard finite difference methodNumerical simulationSkin soresStability analysisStochastic differential equationsStochastic epidemic modelingStochastic Euler methodStochastic Runge–Kutta method

Identifiers

PMID41851272
PMCPMC13136327

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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.