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

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 and Stephanie J Schrag

PLOS ONE, 2019, vol. 14, issue 5, 1-10

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.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0217632

DOI: 10.1371/journal.pone.0217632

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