12,000

We have over 12,000 students, from over 100 countries, within one of the safest campuses in the UK

93%

93% of Lancaster students go into work or further study within six months of graduating

Home > Research > Publications & Outputs > On-line monitoring of public health surveillanc...
View graph of relations

« Back

On-line monitoring of public health surveillance data.

Research output: Contribution in Book/Report/ProceedingsChapter

Published

Publication date2004
Host publicationMonitoring the health of populations : statistical principles and methods for public health surveillance
EditorsRon Brookmeyer, Donna F. Stroup
Place of publicationOxford
PublisherOxford University Press
Pages233-266
Number of pages34
ISBN (Print)0195146492
Original languageEnglish

Abstract

The Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics (AGEISS) project aims to use spatial statistical methods to identify anomalies in the space-time distribution of nonspecific, gastrointestinal infections in the United Kingdom, using the Southampton area in southern England as a test case. Health-care providers are asked to report incident cases daily. Regionwide incident data are then sent electronically to Lancaster, where a statistical analysis of the space-time distribution of incident cases is updated. The results are then posted to a Web site with tabular, graphical and map-based summaries of the analysis. Here we use the AEGISS project to discuss the methodological issues in developing a rapid-response, spatial surveillance system. We consider simple, exploratory statistical methods together with more sophisticated methods, based on hierarchical space-time stochastic process models defined either at individual or small-area levels. The chapter is a report of work in progress. Currently, the Web-based AEGISS reporting system uses only simple summaries of the incident data, but its ultimate aim is to display the results of formal predictive inference in a hierarchical model of space-time variation in disease risk.