IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0217632.html
   My bibliography  Save this article

Multistate analysis of prospective Legionnaires’ disease cluster detection using SaTScan, 2011–2015

Author

Listed:
  • Chris Edens
  • Nisha B Alden
  • Richard N Danila
  • Mary-Margaret A Fill
  • Paul Gacek
  • Alison Muse
  • Erin Parker
  • Tasha Poissant
  • Patricia A Ryan
  • Chad Smelser
  • Melissa Tobin-D’Angelo
  • Stephanie J Schrag

Abstract

Detection of clusters of Legionnaires’ disease, a leading waterborne cause of pneumonia, is challenging. Clusters vary in size and scope, are associated with a diverse range of aerosol-producing devices, including exposures such as whirlpool spas and hotel water systems typically associated with travel, and can occur without an easily identified exposure source. Recently, jurisdictions have begun to use SaTScan spatio-temporal analysis software prospectively as part of routine cluster surveillance. We used data collected by the Active Bacterial Core surveillance platform to assess the ability of SaTScan to detect Legionnaires’ disease clusters. We found that SaTScan analysis using traditional surveillance data and geocoded residential addresses was unable to detect many common Legionnaires’ disease cluster types, such as those associated with travel or a prolonged time between cases. Additionally, signals from an analysis designed to simulate a real-time search for clusters did not align with clusters identified by traditional surveillance methods or a retrospective SaTScan analysis. A geospatial analysis platform better tailored to the unique characteristics of Legionnaires’ disease epidemiology would improve cluster detection and decrease time to public health action.

Suggested Citation

  • Chris Edens & Nisha B Alden & Richard N Danila & Mary-Margaret A Fill & Paul Gacek & Alison Muse & Erin Parker & Tasha Poissant & Patricia A Ryan & Chad Smelser & Melissa Tobin-D’Angelo & Stephanie J , 2019. "Multistate analysis of prospective Legionnaires’ disease cluster detection using SaTScan, 2011–2015," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-10, May.
  • Handle: RePEc:plo:pone00:0217632
    DOI: 10.1371/journal.pone.0217632
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0217632
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0217632&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0217632?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
    ---><---

    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:plo:pone00:0217632. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.