Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics

Poisson random measure noise-induced coherence in epidemiological priors informed deep neural networks to identify the intensity of virus dynamics

Abstract Differential equations-based epidemiological compartmental systems and deep neural networks-based artificial intelligence can effectively analyze and combat monkeypox (MPV) transmission with Poisson random measure noise into a stochastic SEIQR (susceptible, exposed, infected, quarantined, r...

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Bibliographic Details
Main Authors: Saima Rashid, Ayesha Siddiqa, Fekadu Tesgera Agama, Nazeran Idrees, Mohammed Shaaf Alharthi
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Series:Scientific Reports
Subjects:
Epidemiological modeling
Poisson random measure noise
Monkeypox virus
Neural network
State-space models
Online Access:https://doi.org/10.1038/s41598-025-94086-y
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https://doi.org/10.1038/s41598-025-94086-y

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