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

Authors :
Edens, Chris
Alden, Nisha B.
Danila, Richard N.
Fill, Mary-Margaret A.
Gacek, Paul
Muse, Alison
Parker, Erin
Poissant, Tasha
Ryan, Patricia A.
Smelser, Chad
Tobin-D’Angelo, Melissa
Schrag, Stephanie J.
Source :
PLoS ONE; 5/30/2019, Vol. 14 Issue 5, p1-10, 10p
Publication Year :
2019

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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19326203
Volume :
14
Issue :
5
Database :
Complementary Index
Journal :
PLoS ONE
Publication Type :
Academic Journal
Accession number :
136724657
Full Text :
https://doi.org/10.1371/journal.pone.0217632