Scientific Sessions

This session highlights the transformative role of data science and advanced analytics in strengthening public health decision-making, disease surveillance, and health system performance. With the rapid expansion of digital health records, mobile health platforms, and real-time data streams, public health professionals now have unprecedented opportunities to identify trends, predict risks, and design targeted interventions. Key topics include big data integration, machine learning applications, predictive modeling, geospatial analysis, and the use of AI-driven tools to support early detection and outbreak response. The session also explores ethical considerations, data governance, interoperability, and strategies for ensuring data quality, privacy, and equity. Participants will gain practical insights into how data-driven approaches can enhance policy planning, resource allocation, health monitoring, and community-level program design. This session aims to equip attendees with the analytical skills and strategic perspectives needed to harness big data for smarter, more responsive, and more impactful public health action.