ArticleScientific reports2026
Fractional-order analysis of a fear-induced ecoepidemiological predator-prey model with optimal control and bifurcation dynamics.
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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We propose and analyze a fractional-order ecoepidemiological predator-prey model that incorporates disease transmission within the prey population and predator-induced fear effects. The model is formulated using the Caputo fractional derivative to capture memory-dependent dynamics. Fundamental properties, including positivity, boundedness, and existence of solutions, are established. Equilibrium points are derived and their local stability is investigated using the Matignon criterion. Numerical bifurcation analysis reveals transitions between stable equilibria and oscillatory regimes under variations of key biological parameters. An optimal control problem is formulated to reduce infection levels and intervention costs, and necessary optimality conditions are obtained via the fractional Pontryagin Maximum Principle. Numerical simulations demonstrate that fractional dynamics and fear effects enhance system stability and reduce control effort.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.