Hostname: page-component-78c5997874-dh8gc Total loading time: 0 Render date: 2024-11-10T10:09:55.890Z Has data issue: false hasContentIssue false
  • English
  • Français

Understanding the distribution of positive Legionella samples in healthcare-premise water systems: Using statistical analysis to determine a distribution for Legionella and to support sample size recommendations

Published online by Cambridge University Press:  08 October 2020

Dylan J. Nagy ,
David M. Dziewulski Open the ORCID record for David M. Dziewulski [Opens in a new window] ,
Neculai Codru  and
Ursula L. Lauper
Dylan J. Nagy
Affiliation:
New York State Department of Health, Bureau of Water Supply Protection, Albany, New York School of Public Health, University at Albany, SUNY, Rensselaer, New York
David M. Dziewulski*
Affiliation:
New York State Department of Health, Bureau of Water Supply Protection, Albany, New York School of Public Health, University at Albany, SUNY, Rensselaer, New York
Neculai Codru
Affiliation:
New York State Department of Health, Bureau of Water Supply Protection, Albany, New York
Ursula L. Lauper
Affiliation:
New York State Department of Health, Bureau of Water Supply Protection, Albany, New York
*
Author for correspondence: David M. Dziewulski, E-mail: david.dziewulski@health.ny.gov
Get access Rights & Permissions [Opens in a new window]

Abstract

Objective:

To significantly fit a statistical distribution to the proportion of positive Legionella samples in a series of water samples from multiple facility-premise water systems.

Design:

Statistical fit test.

Setting:

A hospital and associated long-term care facility (LTCF) in New York State, as well as temporal and culture data from a deidentified hospital site supplied by one of the vendor laboratories.

Methods:

Culture samples (n = 1,393) were segmented into 139 test cycles with roughly 10 samples in each. The proportion of positive samples was standardized to 25 total samples per test to give a distribution of discrete values. These values were analyzed for fit with the following discrete distributions: Poisson, negative binomial, geometric, and zero-inflated Poisson.

Results:

The zero-inflated Poisson distribution fitted to the copper–silver ionization (CSI)-treated and untreated test cycles indicates that 88% of the expected positive proportions should occur by the 30% cutoff (rounded up to 8 positive samples among 25 total samples), similar to the 93% expectation for just CSI-treated test cycles. The other treatment in these data (chlorine dioxide) was not effective in treating Legionella in the sampled buildings, and if there is an underlying distribution to these specific test cycles, it is not the zero-inflated Poisson distribution.

Conclusions:

In a well-maintained or well-treated premise water distribution system, ~30% or lower proportion of positive Legionella samples should occur. Anything above that cutoff is either very unlikely or not expected at all and indicates a problem in the water system.

Type
Original Article
Information
Infection Control & Hospital Epidemiology , Volume 42 , Issue 1 , January 2021 , pp. 63 - 68
Check for updates
Copyright
© 2020 by The Society for Healthcare Epidemiology of America. All rights reserved.

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Soda, E, Barskey, A, Shah, P et al. Vital signs: health care–associated Legionnaires’ disease surveillance data from 20 states and a large metropolitan area—United States, 2015. Morbid Mortal Wkly Rep 2017;66:584–589.CrossRefGoogle Scholar
Legionnaires’ disease is on the rise in the United States. Centers for Disease Control and Prevention website. https://www.cdc.gov/legionella/qa-media.html. Published December 31, 2018. Accessed August 7, 2020.Google Scholar
Garrison, L, Kunz, J, Cooley, L, et al. Vital signs: deficiencies in environmental control identified in outbreaks of Legionnaires’ disease—North America, 2000–2014. Am J Transplant 2016;16:3049–3058.CrossRefGoogle Scholar
Dziewulski, D, Ingles, E, Codru, N, Strepelis, J, Schoonmaker-Bopp, D. Use of copper–silver ionization for the control of Legionellae in alkaline environments at healthcare facilities. Am J Infect Control 2015;43:971–976.CrossRefGoogle Scholar
Freije, M. Legionellae Control in Health Care Facilities: A Guide for Minimizing Risk. Seattle: HC Information Resources; 1996.Google Scholar
Best, M, Yu, V, Stout, J, Gortz, A, Muder, R, Taylor, F. Legionellaceae in the hospital water supply. Lancet 1983;2:307–310.CrossRefGoogle ScholarPubMed
Stout, J, Muder, R, Mietzner, S, et al. Role of environmental surveillance in determining the risk of hospital-acquired legionellosis: a national surveillance study with clinical correlations. Infect Control Hospital Epidemiol 2007;28:818–824.CrossRefGoogle ScholarPubMed
Lin, Y, Stout, J, Yu, V. Prevention of hospital-acquired legionellosis. Curr Opin Infect Dis 2011;24:350–356.CrossRefGoogle ScholarPubMed
10 NYCRR Part 4, Protection against Legionella. New York State Codes, Rules and Regulations website. https://regs.health.ny.gov/content/part-4-protection-against-legionella. Published 2016. Accessed March 28, 2019.Google Scholar
Spagnolo, A, Cristina, M, Casini, B, Perdelli, F. Legionella pneumophila in healthcare facilities. Med Microbiol 2013;24:70–80.Google Scholar
Pipes, W, Christian, R. A sampling model for coliforms in water distribution systems. In: Annual Conference for American Water Works Association; 1978.Google Scholar
El-Sharrawi, A. Some goodness-of-fit methods for the poisson plus added zeros distribution. Am Soc Microbiol 1985;49:1304–1306.Google Scholar
Christian, R, Pipes, W. Frequency distribution of coliforms in water distribution systems. Appl Env Microbiol 1983;45:603–609.CrossRefGoogle ScholarPubMed
Allen, J, Myatt, T, MacIntosh, D, et al. Assessing risk of health careeacquired Legionnaires’ disease from environmental sampling: the limits of using a strict percent positivity approach. Am J Infect Control 2012;40:917–921.CrossRefGoogle ScholarPubMed
Pierre, D, Stout, J, Yu, V. Editorial commentary: risk assessment and prediction for health care-associated Legionnaires’ disease: percent distal site positivity as a cut-point. Am J Infect Control 2014;42:1248–2150.CrossRefGoogle ScholarPubMed
Supplementary material: File

Nagy et al. Supplementary Materials

Nagy et al. Supplementary Materials 1

Download Nagy et al. Supplementary Materials(File)
File 13.5 KB
Supplementary material: File

Nagy et al. Supplementary Materials

Nagy et al. Supplementary Materials 2

Download Nagy et al. Supplementary Materials(File)
File 2.2 MB