title: Monitoring changes in spatio-temporal maps of disease.
abstract: The object of statistical surveillance is to detect a change in a process accurately and quickly as new observations keep adding to the observed part of the process. In this paper we discuss methodological issues in developing a rapid response in a spatial surveillance system. Simple exploratory statistical methods together with more sophisticated methods, based on hierarchical space-time models defined at small area level, are considered.
authors.affiliation: Department of Epidemiology and Biostatistics, Norman J. Arnold School of Public Health, University of South Carolina, Columbia, SC 29208, USA. vidal.c@ucles.org.uk
authors.forename: Carmen L
authors.initials: CL
authors.lastname: Vidal Rodeiro
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Lawson
mesh_terms: D001499:Bayes Theorem; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004196:Disease Outbreaks / Q000706:statistics & numerical data*; D008954:Models, Biological; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D018571:Sentinel Surveillance