The Impact of Artificial Intelligence-Driven Predictive Models on Public Health Policy Planning and Epidemic Outbreak Management

Authors

  • Fazliddin Arziqulov, Sayfullayeva Dilbar Izzatillayevna, Maxsudov Valijon Gafurjonovich Author

Abstract

Artificial Intelligence (AI)-driven predictive models are increasingly being utilized in public health to support policy planning and epidemic outbreak management. This study evaluates the effectiveness of AI-based predictive systems in forecasting disease outbreaks, optimizing resource allocation, and supporting decision-making processes in public health systems. A convergent mixed-methods approach was employed, combining quantitative data from 190 public health professionals, epidemiologists, and data scientists with qualitative insights from case studies and expert interviews. The findings demonstrate that AI-driven models significantly improve outbreak prediction accuracy, enhance response efficiency, and support proactive policy development. However, challenges such as data reliability, ethical concerns, and model transparency remain critical barriers. The study provides strategic recommendations for integrating AI into public health systems.

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Published

18.04.2025

How to Cite

The Impact of Artificial Intelligence-Driven Predictive Models on Public Health Policy Planning and Epidemic Outbreak Management. (2025). The New Uzbekistan Journal of Medicine, 1(2), 154-158. https://ijournal.uz/index.php/nujm/article/view/2593

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