Editorial on the Research Topic Data science and health economics in precision public health
Overview of precision public healthAdvances in computational and data sciences, such as big data approaches, along with engineering innovations, such as geographic information system (GIS) and artificial intelligence (AI) technologies, have greatly enhanced our capabilities for data management, integration, and visualization (1-3). These scientific developments have prompted demands for more comprehensive and coherent but, most importantly, tailored and targeted strategies to address fundamental issues in public health (4, 5). Combining these novel approaches with more traditional health determinants such as lifestyle, socioeconomic, cultural, and environmental factors has resulted in an exciting new field in the health sciences, Precision Public Health (6).Theory, methods, and models from AI and data science are already changing the public health landscape in community settings (7) and have already shown promising results in multiple applications in public health, including geocoding health data (8), digital public health (9), predictive modeling and decision support (10), and mobile health (11). Overall, Precision Public Health utilizes tools and methods from the above technologies to extract health and non-health data at different levels of granularity, harmonize and integrate information about populations and communities to tailor costeffective interventions for specific population groups, improving people's health. The overarching goal of Precision Public Health is to provide the proper intervention to the right population at the right time (12).