Developments in general and syndromic surveillance for small area health data

Andrew Lawson; Allan Clark; Carmen Vidal-Rodeiro

doi:10.1080/0266476042000270568

Developments in general and syndromic surveillance for small area health data

Andrew Lawson, Allan Clark, Carmen Vidal-Rodeiro

Research output: Contribution to journal › Article

10 Citations (Scopus)

Abstract

In this paper we examine a range of issues related to the analysis of health surveillance data when it is spatially-referenced. The importance of considering alarm functions derived from likelihood or Bayesian models is stressed. In addition, we focus on some new developments in predictive distribution residuals in the analysis.

Original language	English
Pages (from-to)	963-978
Number of pages	16
Journal	Journal of Applied Statistics
Volume	31
Issue number	8
DOIs	https://doi.org/10.1080/0266476042000270568
Publication status	Published - 2004

Access to Document

10.1080/0266476042000270568

Cite this

@article{32734a26d6af40268b16094390d81841,

title = "Developments in general and syndromic surveillance for small area health data",

abstract = "In this paper we examine a range of issues related to the analysis of health surveillance data when it is spatially-referenced. The importance of considering alarm functions derived from likelihood or Bayesian models is stressed. In addition, we focus on some new developments in predictive distribution residuals in the analysis.",

author = "Andrew Lawson and Allan Clark and Carmen Vidal-Rodeiro",

year = "2004",

doi = "10.1080/0266476042000270568",

language = "English",

volume = "31",

pages = "963--978",

journal = "Journal of Applied Statistics",

issn = "1360-0532",

publisher = "Taylor and Francis",

number = "8",

}

TY - JOUR

T1 - Developments in general and syndromic surveillance for small area health data

AU - Lawson, Andrew

AU - Clark, Allan

AU - Vidal-Rodeiro, Carmen

PY - 2004

Y1 - 2004

N2 - In this paper we examine a range of issues related to the analysis of health surveillance data when it is spatially-referenced. The importance of considering alarm functions derived from likelihood or Bayesian models is stressed. In addition, we focus on some new developments in predictive distribution residuals in the analysis.

AB - In this paper we examine a range of issues related to the analysis of health surveillance data when it is spatially-referenced. The importance of considering alarm functions derived from likelihood or Bayesian models is stressed. In addition, we focus on some new developments in predictive distribution residuals in the analysis.

U2 - 10.1080/0266476042000270568

DO - 10.1080/0266476042000270568

M3 - Article

SN - 1360-0532

VL - 31

SP - 963

EP - 978

JO - Journal of Applied Statistics

JF - Journal of Applied Statistics

IS - 8

ER -