Neural networks to model COVID-19 dynamics and allocate healthcare resources

Abstract This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data and enables dynamic resource allocation....

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Abdullah Ali H. Ahmadini, Yashpal Singh Raghav, Ali M. Mahnashi, Khalid Ul Islam Rather, Irfan Ali
Format: Article
Language:English
Published: Nature Portfolio 2025-05-01
Subjects:
Neural networks
COVID-19 forecasting
Healthcare resource optimization
Epidemiological modeling
Machine learning
Online Access:https://doi.org/10.1038/s41598-025-00153-9
Description
Summary:Abstract This study presents a neural network-based framework for COVID-19 transmission prediction and healthcare resource optimization. The model achieves high prediction accuracy by integrating epidemiological, mobility, vaccination, and environmental data and enables dynamic resource allocation. The results demonstrate significant improvements in forecasting performance and healthcare preparedness compared to traditional models. This work enhances decision-making in pandemic management by leveraging machine learning for real-time operational efficiency.
ISSN:2045-2322

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