As evidenced by the anthrax attacks in 2001, the SARS outbreak in 2003, and the H1N1 influenza pandemic in 2009, a pathogen does not recognize geographic or national boundaries, often leading to devastating consequences. Automated biosurveillance systems have emerged as key solutions for mitigating current and future health-related events. Focusing on this promising public health innovation, Biosurveillance: Methods and Case Studies discusses how these systems churn through vast amounts of health-related data to support epidemiologists and public health officials in the early identification, situation awareness, and response management of natural and man-made health-related events.



The book follows a natural sequence from theory to application. The initial chapters build a foundation while subsequent chapters present more applied case studies from around the world, including China, the United States, Denmark, and the Asia-Pacific region. The contributors share candid, first-hand insights on lessons learned and unresolved issues that will help chart the future of biosurveillance.



As this book illustrates, biosurveillance operates in a complex, multidimensional problem space that incorporates varied data. Capturing the progress of modern-day pioneers who are walking in John Snow's footsteps, this volume shows how contemporary information technology can be applied to the age-old challenge of combating the spread of disease and illness.