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

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

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    254 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

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