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. 2021 Nov:202:111649.
doi: 10.1016/j.envres.2021.111649. Epub 2021 Jul 9.

Integrated approach for legionellosis risk analysis in touristic-recreational facilities

Osvalda De Giglio  1 , Christian Napoli  2 , Giusy Diella  3 , Fabrizio Fasano  4 , Marco Lopuzzo  5 , Francesca Apollonio  6 , Marilena D'Ambrosio  7 , Carmen Campanale  8 , Francesco Triggiano  9 , Giuseppina Caggiano  10 , Maria Teresa Montagna  11
Affiliations
Free article

Integrated approach for legionellosis risk analysis in touristic-recreational facilities

Osvalda De Giglio et al. Environ Res. 2021 Nov.
Free article

Abstract

Legionellosis is a severe pneumonia caused by the inhalation of aerosols containing Legionella, Gram-negative bacteria present in the water systems of touristic-recreational facilities. The purpose of this study was to develop a scoring tool to predict the risk of both environmental contamination and Legionnaires' disease cases in such facilities in the Apulia region of southern Italy. We analyzed 47 structural and management parameters/risk factors related to the buildings, water systems, and air conditioning at the facilities. A Poisson regression model was used to compute an overall risk score for each facility with respect to three outcomes: water samples positive for Legionella (risk score range: 7-54), water samples positive for Legionella with an average load exceeding 1000 colony-forming units per liter (CFU/L) (risk score range: 22-179,871), and clinical cases of Legionnaire's disease (risk score range: 6-31). The cut-off values for three outcomes were determined by receiver operating characteristic curves (first outcome, samples positive for Legionella in a touristic-recreational facility: 19; second outcome, samples positive for Legionella in a touristic-recreational facility with an average load exceeding 1000 CFU/L: 2062; third outcome, clinical cases of Legionnaire's disease in a touristic-recreational facility: 22). Above these values, there was a significant probability of observing the outcome. We constructed this predictive model using 70% of a large dataset (18 years of clinical and environmental surveillance) and tested the model on the remaining 30% of the dataset to demonstrate its reliability. Our model enables the assessment of risk for a touristic facility and the creation of a conceptual framework to link the risk analysis with prevention measures.

Keywords: Legionella; Legionellosis; Predictive model; Risk analysis; Tourism.

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