Information systems are central to the development of effective comprehensive approaches aimed at the prevention, detection, mitigation, and management of human and animal infectious disease outbreaks. Infectious disease informatics (IDI) is a subfield of biomedical informatics concerned with the development of methodologies and technologies needed for collecting, sharing, reporting, analyzing, and visualizing infectious disease data and for providing data-driven decision-making support for infectious disease prevention, detection, mitigation, and management. The growth and 
vitality of IDI are central to our national security. Biosurveillance is an important partner of IDI applications and focuses primarily on the early  detection of new outbreaks of infectious diseases and on the early identification of elevated or new diseases’ risks. 
IDI and biosurveillance research directly benefits public health and animal health agencies in their multiple activities in fighting and managing infectious diseases. IDI and biosurveillance research provides quantitative methods and computational tools that are instrumental in the decision
making process carried out by government agencies with responsibilities in infectious diseases within national and international contexts. IDI also has important applications in law enforcement and national security concerning, among other issues, the prevention of and timely response to the deliberate release of biological agents. As a result of the increasing threats to our national security, a large amount of animal and public health infectious disease data are being collected by various laboratories, health care providers, and government agencies at local, state, national, and international levels. In fact, many agencies charged with collecting these data have developed information 
access, analysis, and reporting systems of varying degrees of sophistication.  
Researchers from a wide range of backgrounds including but not limited to epidemiology, statistics, applied mathematics, computer science and machine learning/data mining, have contributed to the development of technologies that facilitate real-time data collection and access. They have also developed algorithms needed to analyze or mine the collected data.  
This book on IDI and biosurveillance compiles a high-quality collection of academic work in various sub-areas of IDI and biosurveillance to provide an integrated and timely view of the current state-of-the-art. It also identifies technical and policy challenges and opportunities with the goal of promoting 
cross-disciplinary research that takes advantage of novel methodology  and lessons learned from innovative applications. This book fills a systemic gap in the literature by emphasizing informatics-driven perspectives (e.g.,  information system design, data standards, computational aspects of bio
surveillance algorithms, and system evaluation) rather than just statistical modeling and analytical work. Finally, this book attempts to reach policy makers and practitioners through the clear and effective communication of recent research findings in the context of case studies in IDI and bio
surveillance, providing “hands-on” in-depth opportunities to practitioners to increase their understanding of value, applicability, and limitations of technical solutions.