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Provides a coherent and comprehensive account of the theory and practice of real-time human disease outbreak detection, explicitly recognizing the revolution in practices of infection control and public health surveillance. Reviews the current mathematical, statistical, and computer science systems for early detection of disease outbreaks Provides extensive coverage of existing surveillance data Discusses experimental methods for data measurement and evaluation Addresses engineering and practical implementation of effective early detection systems Includes real case studies
Presents basic and advanced methods with a focus on demonstrated added value for a broad class of public health surveillance problems.
Following the attacks of September 11, 2001 and the anthrax letters, the ability to detect biological threats as quickly as possible became a top priority. In 2003 the Department of Homeland Security (DHS) introduced the BioWatch program-a federal monitoring system intended to speed detection of specific biological agents that could be released in aerosolized form during a biological attack. The present volume evaluates the costs and merits of both the current BioWatch program and the plans for a new generation of BioWatch devices. BioWatch and Public Health Surveillance also examines infectious disease surveillance through hospitals and public health agencies in the United States, and considers whether BioWatch and traditional infectious disease surveillance are redundant or complementary.
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
After the September 11, 2001, terrorist attacks and subsequent anthrax mailings, the U.S. government prioritized a biosurveillance strategy aimed at detecting, monitoring, and characterizing national security health threats in human and animal populations, food, water, agriculture, and the environment. However, gaps and challenges in biosurveillance efforts and integration of biosurveillance activities remain. September 8-9, 2011, the IOM held a workshop to explore the information-sharing and collaboration processes needed for the nation's integrated biosurveillance strategy.
This book is a source of information on practical and innovative approaches to biosecurity surveillance. It explains the foundation and concepts behind surveillance design, with examples of methods and tools created to deal with surveillance challenges. With supporting case studies and including current directions in research, it covers evidence-based approaches to surveillance, statistics, detectability, single and multi-species detection, risk assessment, diagnostics, data-basing, modelling of invasion and spread, optimisation, and future climate challenges.
This book on Infectious Disease Informatics (IDI) and biosurveillance is intended to provide an integrated view of the current state of the art, identify technical and policy challenges and opportunities, and promote cross-disciplinary research that takes advantage of novel methodology and what we have learned from innovative applications. This book also fills a systemic gap in the literature by emphasizing informatics driven perspectives (e.g., information system design, data standards, computational aspects of biosurveillance algorithms, and system evaluation). 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 biosurveillance, providing “hands-on” in-depth opportunities to practitioners to increase their understanding of value, applicability, and limitations of technical solutions. This book collects the state of the art research and modern perspectives of distinguished individuals and research groups on cutting-edge IDI technical and policy research and its application in biosurveillance. The contributed chapters are grouped into three units. Unit I provides an overview of recent biosurveillance research while highlighting the relevant legal and policy structures in the context of IDI and biosurveillance ongoing activities. It also identifies IDI data sources while addressing information collection, sharing, and dissemination issues as well as ethical considerations. Unit II contains survey chapters on the types of surveillance methods used to analyze IDI data in the context of public health and bioterrorism. Specific computational techniques covered include: text mining, time series analysis, multiple data streams methods, ensembles of surveillance methods, spatial analysis and visualization, social network analysis, and agent-based simulation. Unit III examines IT and decision support for public health event response and bio-defense. Practical lessons learned in developing public health and biosurveillance systems, technology adoption, and syndromic surveillance for large events are discussed. The goal of this book is to provide an understandable interdisciplinary IDI and biosurveillance reference either used as a standalone textbook or reference for students, researchers, and practitioners in public health, veterinary medicine, biostatistics, information systems, computer science, and public administration and policy.
For many years, concerns about bioterrorism and emerging infectious diseases have drawn attention to the need for strong surveillance systems. Experts are working to develop new and better ways to detect these biological threats as quickly as possible. One effort in this area is the Department of Homeland Security's BioWatch program. To evaluate the effectiveness of the BioWatch program, the Institute of Medicine (IOM) and National Research Council (NRC) convened the Committee on Effectiveness of National Biosurveillance Systems: BioWatch and the Public Health System. This interim report contains no findings and recommendations, but outlines the committee's initial progress.
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
Bioterrorism is not a new threat, but in an increasingly interconnected world, the potential for catastrophic outcomes is greater today than ever. The medical and public health communities are establishing biosurveillance systems designed to proactively monitor populations for possible disease outbreaks as a first line of defense. The ideal biosurveillance system should identify trends not visible to individual physicians and clinicians in near-real time. Many of these systems use statistical algorithms to look for anomalies and to trigger epidemiologic investigation, quantification, localization and outbreak management. This book discusses the design and evaluation of statistical methods for effective biosurveillance for readers with minimal statistical training. Weaving public health and statistics together, it presents basic and more advanced methods, with a focus on empirically demonstrating added value. Although the emphasis is on epidemiologic and syndromic surveillance, the statistical methods can be applied to a broad class of public health surveillance problems.