IDEAS home Printed from https://ideas.repec.org/a/taf/uiiexx/v46y2014i8p790-797.html
   My bibliography  Save this article

The use of a CUSUM residual chart to monitor respiratory syndromic data

Author

Listed:
  • Huifen Chen
  • Chaosian Huang

Abstract

This article reports a surveillance mechanism that can be used to monitor syndromic data on respiratory syndrome. The data used for illustration are the daily counts of respiratory-syndrome visits sampled from the National Health Insurance Research Database in Taiwan. The population size is 160 000. A regression model with an autoregressive-integrated-moving-average error term is fitted to the data and then CUmulative SUM (CUSUM) residual charts are plotted to detect aberrations in the frequency of visits to a walk in clinic. Day-of-the-week, seasonal, and holiday effects are considered in the regression model. It is shown that a CUSUM residual chart can be used to detect abnormal increases in daily counts of respiratory-syndrome visits.

Suggested Citation

  • Huifen Chen & Chaosian Huang, 2014. "The use of a CUSUM residual chart to monitor respiratory syndromic data," IISE Transactions, Taylor & Francis Journals, vol. 46(8), pages 790-797, August.
    • Handle: RePEc:taf:uiiexx:v:46:y:2014:i:8:p:790-797
    DOI: 10.1080/0740817X.2012.761369
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/0740817X.2012.761369
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0740817X.2012.761369?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Giorgio Bagarella & Mauro Maistrello & Maddalena Minoja & Olivia Leoni & Francesco Bortolan & Danilo Cereda & Giovanni Corrao, 2022. "Early Detection of SARS-CoV-2 Epidemic Waves: Lessons from the Syndromic Surveillance in Lombardy, Italy," IJERPH, MDPI, vol. 19(19), pages 1-10, September.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:taf:uiiexx:v:46:y:2014:i:8:p:790-797. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/uiie .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.