Evidence map›Paper›PMID 40424449›Full record

ArticlePloS one2025

Finite-time analysis of epidemic reaction-diffusion models: Stability, synchronization, and numerical insights.

Iqbal Batiha, Nidal Anakira, Issam Bendib, Adel Ouannas, Amel Hioual, Irianto Irianto, Ala Amourah

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Iqbal BatihaDepartment of Mathematics, Al Zaytoonah University of Jordan, Amman, Jordan.ORCID https://orcid.org/0000-0002-8443-8848
Nidal AnakiraFaculty of Education and Arts, Sohar University, Sohar, Oman.
Issam BendibDepartment Applied Mathematics, Brothers Mentouri University of Constantine, Constantine, Algeria.
Adel OuannasDepartment of Mathematics and Computer Science, University of Oum EL-Bouaghi, Oum EL-Bouaghi, Algeria.
Amel HioualDepartment of Mathematics and Computer Science, University of Oum EL-Bouaghi, Oum EL-Bouaghi, Algeria.
Irianto IriantoDepartment General Education, Faculty of Resilience, Rabdan Academy, Abu Dhabi, United Arab Emirates.
Ala AmourahFaculty of Education and Arts, Sohar University, Sohar, Oman.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents an innovative approach to analyzing finite-time stability (FTS) and synchronization (FTSYN) in integer-order reaction-diffusion systems (RDs), particularly in the context of epidemiological modeling. By integrating Gronwall's inequality, Lyapunov functionals (LFs), and linear control strategies, a comprehensive framework is developed to address transient dynamics within finite time frames. The proposed methodology advances the theoretical understanding of FTS and FTSYN by addressing the relatively unexplored dynamics of spatially extended systems. MATLAB simulations validate the theoretical findings, demonstrating the effectiveness of the control schemes and their practical applicability in modeling real-world disease transmission. Integrating spatial diffusion and disease dynamics provides critical insights into the influence of parameters such as diffusion rates and mortality on system behavior. This work contributes a robust framework for enhancing the analysis and management of nonlinear systems, with significant implications for epidemiology and other fields requiring rapid convergence and synchronization.

Indexed as

EpidemicsEpidemiological ModelsModels, TheoreticalAlgorithmsComputer SimulationHumansNonlinear Dynamics

Identifiers

PMID40424449
PMCPMC12178015

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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.