Monitoring the Health of Populations: Statistical Principles and Methods for Public Health Surveillance
Ron Brookmeyer, Donna F. Stroup
Oxford University Press, USA, 2004 - Medical - 370 pages
Public health faces critical challenges ranging from outbreaks of new and old pathogens to the threat of bioterrorism and the impact of lifestyle and environmental changes on health. Modern tools of health surveillance and sound statistical practices are essential for meeting these challenges and providing accurate warnings about real public health threats without wasting resources on false alarms. Advances in statistical techniques, computing power and the Internet have led to many new approaches to monitoring population health, analyzing the data, and rapidly sharing it.This text explores the critical issues in the statistical analysis and interpretation of public health surveillance data. It covers statistical methods for detecting disease outbreaks and clusters, the use of survey methods, interpreting time trends and geographic patterns, exploratory statistical analysis of surveillance data, and web-based health reporting systems for the rapid detection of public health problems, among other topics. The methodological approaches are illustrated in discussions of several current public health issues, including the HIV/AIDS epidemic, anthrax, health effects of particulate air pollution, and trends in prostate cancer. The methods are broadly applicable to surveillance systems and registries for numerous health conditions, e.g. infectious diseases, chronic diseases, adverse drug reactions.The book provides numerous illustrations, worked examples, and practical information for actually implementing the methods. It will serve as a reference for public health practitioners and as a textbook for courses on disease surveillance taken by students of statistics biostatistics, epidemiology or public health.
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aggregate air pollution American journal analysis applied approach associated assumption bandwidth baseline bias Brookmeyer cancer incidence capture—recapture Centers for Disease clinical cluster sampling cohort confounding contextual Control and Prevention counts covariates defined Diggle Disease Control disease surveillance effects epidemic error estimate example exposure Figure function http://www.cdc.gov identify increase incubation period distribution individual individual-level infection interval journal of Epidemiology kernel linear lung cancer measures methods monitoring Morbidity and Mortality Mortality Weekly Report National NHS Direct nonresponse null hypothesis observed outbreak detection outcome oversampling parameters pattern Poisson Poisson process population prediction interval problem prostate cancer PSA screening public health surveillance random rates region regression relative risk risk factors Royal Statistical Society sample scan statistic SEER Program selection smoothing sources space-time spatial temporal specific spina bifida Statistics in Medicine surveillance system Tango tion United values variables variance variation
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