A statistical algorithm for the early detection of outbreaks of infectious disease

C. P. Farrington, Nicholas Andrews, A. D. Beale, M. A. Catchpole

Research output: Contribution to journalArticlepeer-review

210 Citations (Scopus)

Abstract

Outbreaks of infectious diseases must be detected early for effective control measures to be introduced. When dealing with large amounts of data, automated procedures can usefully supplement traditional surveillance methods, provided that the wide variety of patterns and frequencies of infections are taken into account. This paper describes a robust system developed to process weekly reports of infections received at the Communicable Disease Surveillance Centre. A simple regression algorithm is used to calculate suitable thresholds. Organisms exceeding their threshold are then flagged for further investigation.

Original languageEnglish
Pages (from-to)547-563
Number of pages17
JournalJournal of the Royal Statistical Society. Series A: Statistics in Society
Volume159
Issue number3
DOIs
Publication statusPublished - 1996

Keywords

  • Clustering
  • Dispersion
  • Epidemiology
  • Exceedance
  • Glim
  • Outbreak
  • Regression
  • Reweighting
  • Seasonality
  • Threshold
  • Trend

Fingerprint

Dive into the research topics of 'A statistical algorithm for the early detection of outbreaks of infectious disease'. Together they form a unique fingerprint.

Cite this