Stochastic Dynamics of Epidemic Models with Resource Constraints: Extinction and Ergodicity
DOI:
https://doi.org/10.29020/nybg.ejpam.v18i4.6776Keywords:
Stochastic modeling, SIR model, Backward bifurcation, Medical resourcesAbstract
Recent studies highlight how stochastic e ects, such as environmental noise and resource constraints, alter epidemic dynamics, diverging from deterministic predictions. Unlike classical models with bifurcations, stochastic models capture more realistic outbreak scenarios. Research suggests that limited medical resources, coupled with stochastic uctuations, signi cantly in uence disease spread and control strategies. Numerical simulations support these ndings, emphasizing the need for randomness in epidemic modeling to improve predictive accuracy and public health interventions.Understanding these stochastic in uences can aid in developing more adaptive policies for epidemic mitigation. Future research aims to re ne these models by incorporating spatial heterogeneity, population diversity, and pathogen evolution for better epidemic control.
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Copyright (c) 2025 J. Leo Amalraj, Manivannan Balamurugan, N. Avinash, Pankaj Shukla, M. V. Rajesh, Vediyappan Govindan, Siriluk Donganont Donganont
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