Work

Dynamics and forecasting of an age-structured stochastic SIR model with Lévy perturbations via physics-informed neural networks

Year: 2025

Type: article

Abstract: markedly suppresses transmission. Finally, the efficacy of physics-informed neural network based on stochastic SIR model (PINN-SIR), is demonstrated through its application to the fitting and forecasting of COVID-19 case in Zhejiang, China. The method shows promise for extension to more complex dynamical systems and diseases.

Source: Infectious Disease Modelling

DOI: 10.1016/j.idm.2025.11.003

Authors: Ge Zhang, Zhihao Wang, Zhiming Li, Shenglong Chen, Qiaoling Chen

Institutions: Xinjiang University of Finance and Economics, Xinjiang University, Xi'an Polytechnic University

Language: English

Topic: Mathematical and Theoretical Epidemiology and Ecology Models

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $1,100