LEADER 05368nam 2200673Ia 450 001 9911020015403321 005 20200520144314.0 010 $a9786610238538 010 $a9781280238536 010 $a1280238534 010 $a9780470092507 010 $a0470092505 010 $a9780470092491 010 $a0470092491 035 $a(CKB)1000000000356543 035 $a(EBL)239466 035 $a(OCoLC)475950826 035 $a(SSID)ssj0000249354 035 $a(PQKBManifestationID)11194276 035 $a(PQKBTitleCode)TC0000249354 035 $a(PQKBWorkID)10205340 035 $a(PQKB)10988902 035 $a(MiAaPQ)EBC239466 035 $a(Perlego)2775706 035 $a(EXLCZ)991000000000356543 100 $a20050329d2005 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aSpatial and syndromic surveillance for public health /$fedited by Andrew B. Lawson, Ken Kleinman 210 $aChichester, West Sussex, England ;$aHoboken, NJ $cJ. Wiley & Sons$dc2005 215 $a1 online resource (285 p.) 300 $aDescription based upon print version of record. 311 08$a9780470092484 311 08$a0470092483 320 $aIncludes bibliographical references (p. [245] - 266) and index. 327 $aSpatial and Syndromic Surveillance for Public Health; Contents; Preface; List of Contributors; 1 Introduction: Spatial and syndromic surveillance for public health; 1.1 What is public health surveillance?; 1.1.1 Spatial surveillance; 1.1.2 Syndromic surveillance; 1.2 The increased importance of public health surveillance; 1.3 Geographic information, cluster detection and spatial surveillance; 1.4 Surveillance and screening; 1.5 Overview of process control and mapping; 1.5.1 Process control methodology; 1.5.2 The analysis of maps and surveillance; 1.6 The purpose of this book 327 $a1.6.1 Statistical surveillance and methodological development in a public health context1.6.2 The statistician's role in surveillance; 1.7 The contents of this book; Part I Introduction to Temporal Surveillance; 2 Overview of temporal surveillance; 2.1 Introduction; 2.1.1 Surveillance systems; 2.1.2 Surveillance attributes; 2.1.3 Early detection of unusual health events; 2.2 Statistical methods; 2.2.1 Historical limits method; 2.2.2 Process control charts; 2.2.3 Time-series analysis; 2.3 Conclusion; 3 Optimal surveillance; 3.1 Introduction 327 $a3.2 Optimality for a fixed sample and for on-line surveillance3.3 Specification of the statistical surveillance problem; 3.4 Evaluations of systems for surveillance; 3.4.1 Measures for a fixed sample situation adopted for surveillance; 3.4.2 False alarms; 3.4.3 Delay of the alarm; 3.4.4 Predictive value; 3.5 Optimality criteria; 3.5.1 Minimal expected delay; 3.5.2 Minimax optimality; 3.5.3 Average run length; 3.6 Optimality of some standard methods; 3.6.1 The likelihood ratio method; 3.6.2 The Shewhart method; 3.6.3 The CUSUM method; 3.6.4 Moving average and window-based methods 327 $a3.6.5 Exponentially weighted moving average methods3.7 Special aspects of optimality for surveillance of public health; 3.7.1 Gradual changes during outbreaks of diseases; 3.7.2 Change between unknown incidences; 3.7.3 Spatial and other multivariate surveillance; 3.8 Concluding remarks; Acknowledgment; Part II Basic Methods for Spatial and Syndromic Surveillance; 4 Spatial and spatio-temporal disease analysis; 4.1 Introduction; 4.2 Disease mapping and map reconstruction; 4.3 Disease map restoration; 4.3.1 Simple statistical representations; 4.3.2 Basic models 327 $a4.3.3 A simple overdispersion model4.3.4 Advanced Bayesian models; 4.4 Residuals and goodness of fit; 4.5 Spatio-temporal analysis; 4.6 Surveillance issues; 5 Generalized linear models and generalized linear mixed models for small-area surveillance; 5.1 Introduction; 5.2 Surveillance using small-area modeling; 5.2.1 Example; 5.2.2 Using the model results; 5.3 Alternate model formulations; 5.3.1 Fixed effects logistic regression; 5.3.2 Poisson regression models; 5.4 Practical variations; 5.5 Data; 5.5.1 Developing and defining syndromes; 5.6 Evaluation 327 $a5.6.1 Fixed and random effects monthly models 330 $aFollowing the events of 9/11 and in the current world climate, there is increasing concern of the impact of potential bioterrorism attacks. Spatial surveillance systems are used to detect changes in public health data, and alert us to possible outbreaks of disease, either from natural resources or from bioterrorism attacks. Statistical methods play a key role in spatial surveillance, as they are used to identify changes in data, and build models of that data in order to make predictions about future activity. This book is the first to provide an overview of all the current key methods in spa 606 $aPublic health surveillance 606 $aEpidemiology 615 0$aPublic health surveillance. 615 0$aEpidemiology. 676 $a614.4 701 $aLawson$b Andrew$g(Andrew B.)$0149118 701 $aKleinman$b Ken$0732796 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911020015403321 996 $aSpatial and syndromic surveillance for public health$94416116 997 $aUNINA