Neural networks to model COVID-19 dynamics and allocate healthcare resources
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.
Authors
- Yashpal Singh Raghav (ORCID: https://orcid.org/0000-0002-9410-9079)
- Irfan Ali (ORCID: https://orcid.org/0000-0002-1790-5450)
- Ali M. Mahnashi (ORCID: https://orcid.org/0009-0004-8068-068X)
- Khalid Ul Islam Rather (ORCID: https://orcid.org/0000-0002-4631-5652)
- Abdullah Ali H. Ahmadini (ORCID: https://orcid.org/0000-0002-9740-7207)
Institutions
- Aligarh Muslim University (IN)
- Sher-e-Kashmir University of Agricultural Sciences and Technology of Jammu (IN)
- Jazan University (SA)
Publication Details
- Journal
- Scientific Reports
- Published
- 2025-05-02
- DOI
- https://doi.org/10.1038/s41598-025-00153-9
- Citations
- 3
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 4.08
Funders
- Jazan University