You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
A Statistical Algorithm for the Early Detection of Outbreaks of Infectious Disease
C. P. Farrington, N. J. Andrews, A. D. Beale and M. A. Catchpole
Journal of the Royal Statistical Society. Series A (Statistics in Society)
Vol. 159, No. 3 (1996), pp. 547-563
Stable URL: http://www.jstor.org/stable/2983331
Page Count: 17
You can always find the topics here!Topics: Disease outbreaks, Infectious diseases, Surveillance, Salmonella, False positive errors, Infections, Time series, Binomials, Statistical median, Public health
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
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.
Journal of the Royal Statistical Society. Series A (Statistics in Society) © 1996 Royal Statistical Society