Infectious disease outbreaks, either naturally occurring or caused by terror attacks, pose a critical threat to public health and national security. Information systems and infectious disease informatics (IDI) research are playing an increasingly important role in developing a comprehensive approach to prevent, detect, respond to, and manage infectious disease outbreaks. Computerized datasets on infectious diseases are currently used for disease reporting, including those developed by various federal, state, and local health, agriculture, and environment/wildlife agencies. However, such datasets are typically not interoperable, particularly in across jurisdiction and across species contexts, reducing their effective use in data modeling and analysis, disease surveillance, and disease management-related decision-making. In addition, the information management environment used by public health officials and researchers to analyze large amounts of infectious disease data and develop predictive models needs major improvements.
A partnership has been developed with expertise in IDI, mission-critical Web-based interoperable systems, data security and access control, advanced data mining and visualization techniques, disease surveillance and predictive modeling, and information systems evaluation. The partnership includes: (1) the Artificial Intelligence Laboratory at the University of Arizona, (2) the Information Systems Group at the University of Utah, (3) the New York State Department of Health and its partner Health Research, Inc., and (4) the California State Department of Health Services and its partner PHFE Management Solutions.
Building on ongoing IDI research and infrastructure development efforts, research is aimed at (a) developing an integrated and scalable information sharing, monitoring, and analysis environment across jurisdictions and species for major infectious diseases, (b) developing novel data analysis, surveillance, and visualization techniques to meet the critical needs of IDI, and (c) gaining a systematic understanding of related policy, user evaluation, and technology adoption issues.
The intended intellectual contributions are threefold: (1) developing and evaluating system performance and scalability models and related algorithms needed for the efficient operation of large-scale realtime information query and monitoring/surveillance systems such as the NIDII, (2) developing and evaluating a set of novel spatio-temporal data analysis and online surveillance techniques which can be used in both IDI and other applications needing similar capabilities (e.g., crime analysis), and (3) developing a comprehensive user evaluation and technology adoption framework and conducting a detailed user evaluation and organizational impact study of the developed IDI system and related technologies.
The proposed work will have the following major broader impacts: (a) The research team will develop a working infectious disease information system across jurisdictions and disease types, providing an integrated data sharing, access, analysis, visualization, and surveillance environment for researchers, public health officials, and law enforcement and national security officials who need to assess risk of and respond to biological terror attacks. (b) The work will bring together previously disparate research and practitioner communities to conduct IDI research of significant practical relevance. In addition, it will foster cross-fertilization between law enforce and national security research and IDI.
Project Title: ITR-(NHS)-(DMC): A National Center of Excellence for Infectious Disease Informatics Project PI: Hsinchun Chen, Prof., University of Arizona, Tucson, Arizona, U.S.A. Grant Number: NSF Information Technology Research, #IIS-0428241 Reporting Period: Final Report BioPortal Outcomes Report for General Public How can we best monitor, investigate, and respond to infectious disease outbreaks in order to keep the general public in the U.S. and around the globe safe? This question has been at the center of our project to investigate the role "information systems" – that is, information technology and data, and the interactions that people have with them – should play in helping the public health officials to develop an effective approach to preventing, detecting, and managing infectious disease outbreaks. Disease outbreaks can pose critical threats to public health, national security, and economic stability. Examples of past threats include, for example, the influenza pandemic in the early 20th century and the SARS outbreak in the early 21st. Present dangers include, for example, newly antibiotic-resistant strains of various human diseases, and stubborn outbreaks of livestock diseases such as foot-and-mouth. Given the ease with which people and goods travel around the world, infectious diseases can spread quickly, whether they are naturally occurring or are from a bioterrorist attack, and public health and biosecurity remain a top priority of the governments at all levels. . There are many challenges to successfully answering the question posed above. In this project, we worked with public health officials in Arizona, California, New York, Kansas, Taiwan, and Beijing, China, and: - Developed and evaluated the kind of large-scale system that would be needed to allow all kinds of public-health organizations to share their data in real time; - Experimented with new mathematical models and statistical techniques, and made discoveries about new ways for public-health personnel to detect disease outbreaks, such as "hotspot" analysis to detect where diseases emerge or are particularly active, and "predictive modeling" that helps us estimate how a disease will spread; - Created tools for "visualization" (a way to use pictures to represent complex data), and "alerting" (a way to automatically send out meaningful messages very quickly); - Conducted studies with real public-health organizations and people to tell us if our information systems were easy to learn, had the data and tools important to them, and were useful. - Investigated the role that "social networks" (the relationships people have with each other) play in disease outbreaks.
