Harnessing Big Data and Artificial Intelligence for Health Crisis Management: Opportunities and Challenges in Public Health Informatics

Abstract

The integration of Big Data and Artificial Intelligence (AI) in health crisis management represents a transformative opportunity in public health informatics. These technologies enable real-time data analysis, predictive modeling, and resource optimization, crucial for addressing crises such as pandemics. Big Data supports public health decision-making by aggregating vast datasets from various sources, while AI enhances predictive capabilities and operational efficiency. Together, they facilitate early outbreak detection, optimize healthcare delivery, and improve patient outcomes. However, significant challenges, including data privacy, ethical concerns, and infrastructure limitations, must be addressed to harness their full potential. This review explores the opportunities and challenges in leveraging Big Data and AI for health crisis management.
Aim of Work
This review aims to evaluate the role of Big Data and AI in managing health crises, focusing on their applications, benefits, and challenges. It seeks to highlight how these technologies can enhance public health responses, streamline healthcare operations, and improve crisis outcomes. Furthermore, the review examines the ethical, legal, and logistical barriers to their implementation, offering insights into strategies for overcoming these hurdles. By exploring these dimensions, the work aims to provide a comprehensive understanding of the potential and limitations of Big Data and AI in public health crisis management.