On-line Monitoring of Public Health Surveillance Data

Peter Diggle; Leo Knorr-Held; Barry Rowlingson; Ting Li Su; Peter Hawtin; Trevor N. Bryant

doi:10.1093/acprof:oso/9780195146493.003.0009

On-line Monitoring of Public Health Surveillance Data

Peter Diggle, Leo Knorr-Held, Barry Rowlingson, Ting Li Su, Peter Hawtin, Trevor N. Bryant

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

1 Citation (Scopus)

Abstract

The Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics (AEGISS) 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. This chapter uses the AEGISS project to discuss the methodologic issues in developing a rapidresponse, spatial surveillance system. It considers 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.

Original language	English
Title of host publication	Monitoring the Health of Populations : Statistical Principles and Methods for Public Health Surveillance
ISBN (Electronic)	9780199864928
DOIs	https://doi.org/10.1093/acprof:oso/9780195146493.003.0009
Publication status	Published - 1 Sept 2009
Externally published	Yes

Keywords

AEGISS
Data collection
Public health monitoring
Surveillance system
United Kingdom

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1093/acprof:oso/9780195146493.003.0009

Cite this

@inbook{74be23f7a3724977b0490b67cc772295,

title = "On-line Monitoring of Public Health Surveillance Data",

abstract = "The Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics (AEGISS) 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. This chapter uses the AEGISS project to discuss the methodologic issues in developing a rapidresponse, spatial surveillance system. It considers 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.",

keywords = "AEGISS, Data collection, Public health monitoring, Surveillance system, United Kingdom",

author = "Peter Diggle and Leo Knorr-Held and Barry Rowlingson and Su, \{Ting Li\} and Peter Hawtin and Bryant, \{Trevor N.\}",

year = "2009",

month = sep,

day = "1",

doi = "10.1093/acprof:oso/9780195146493.003.0009",

language = "English",

isbn = "9780195146493",

booktitle = "Monitoring the Health of Populations : Statistical Principles and Methods for Public Health Surveillance",

}

TY - CHAP

T1 - On-line Monitoring of Public Health Surveillance Data

AU - Diggle, Peter

AU - Knorr-Held, Leo

AU - Rowlingson, Barry

AU - Su, Ting Li

AU - Hawtin, Peter

AU - Bryant, Trevor N.

PY - 2009/9/1

Y1 - 2009/9/1

N2 - The Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics (AEGISS) 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. This chapter uses the AEGISS project to discuss the methodologic issues in developing a rapidresponse, spatial surveillance system. It considers 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.

AB - The Ascertainment and Enhancement of Gastrointestinal Infection Surveillance and Statistics (AEGISS) 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. This chapter uses the AEGISS project to discuss the methodologic issues in developing a rapidresponse, spatial surveillance system. It considers 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.

KW - AEGISS

KW - Data collection

KW - Public health monitoring

KW - Surveillance system

KW - United Kingdom

U2 - 10.1093/acprof:oso/9780195146493.003.0009

DO - 10.1093/acprof:oso/9780195146493.003.0009

M3 - Chapter

SN - 9780195146493

BT - Monitoring the Health of Populations : Statistical Principles and Methods for Public Health Surveillance

ER -

On-line Monitoring of Public Health Surveillance Data

Abstract

Keywords

UN SDGs

Access to Document

Fingerprint

Cite this