Epidemiological analysis of Legionnaires' disease in Scotland: a genomic study

Gorzynski, Jamie; Wee, Bryan A.; Llano, Melissa; Alves, Joana; Cameron, Ross; McMenamin, Jim; Smith, Andrew; Lindsay, Diane; Fitzgerald, J. Ross

doi:10.1016/s2666-5247(22)00231-2

Cited by 12 publications

(27 citation statements)

References 28 publications

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“…Phylogenomic analysis has become an important approach to examine pathogen population structure and to investigate the likely origins of L. pneumophila clinical isolates using WGS data (David et al, 2016; Gorzynski et al, 2022; Graham, Doyle, & Jennison, 2014; Qin et al, 2016; Reuter et al, 2013; Wüthrich et al, 2019). A phylogenomic tree was estimated from the non-recombining core-genome SNP alignment to depict the clonal ancestry (Fig.…”

Section: Resultsmentioning

confidence: 99%

High performanceLegionella pneumophilasource attribution using genomics-based machine learning classification

Buultjens

Vandelannoote

Mercoulia

et al. 2023

Preprint

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Fundamental to effective Legionnaires′ disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent,Legionella pneumophila. Genomics has revolutionized pathogen surveillance butL. pneumophilahas a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here we present a powerful machine learning approach that assigns the geographical source of Legionnaires′ disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534L. pneumophilagenome sequences, including 149 genomes linked to 20 previously reported Legionnaires′ disease outbreaks through detailed case investigations. Our classification models were developed in a cross–validation framework using only environmentalL. pneumophilagenomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534–genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance – agreement with epidemiological information. Our multivariate statistical learning approach maximises use of genomic variation data and is thus well-suited for supporting Legionnaires′ disease outbreak investigations.

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Section: Resultsmentioning

confidence: 99%

High performanceLegionella pneumophilasource attribution using genomics-based machine learning classification

Buultjens

Vandelannoote

Mercoulia

et al. 2023

Preprint

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“…Treatment for Legionnaire disease typically involves the use of antibiotics, which are given orally or intravenously depending on the severity of the illness [1] . Commonly used antibiotics for treating Legionnaire disease include azithromycin, levofloxacin, and doxycycline [1] . Supportive care is also an important part of treatment for Legionnaire disease, particularly for individuals with severe illness.…”

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confidence: 99%

“…In severe cases, it can cause confusion and delirium, as well as other neurological symptoms such as seizures. Legionnaire disease may be associated with a low level of sodium in the blood, which can lead to dehydration and other complications [1] .…”

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confidence: 99%

“…Supportive care is also an important part of treatment for Legionnaire disease, particularly for individuals with severe illness. This may include oxygen therapy, fluid replacement, and management of other symptoms such as fever and pain [1] .…”

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confidence: 99%

“…Also, AI algorithms could be used to analyze data on Legionnaire disease outbreaks and predict where future outbreaks are likely to occur, allowing for targeted prevention measures. Further, water management, regular monitoring of water quality, maintenance of appropriate temperatures, and regular cleaning and disinfection of water systems can lower the transmission risk [1] . Also, education and awareness campaigns, implementation of guidelines and best practices for Legionella prevention, disinfection methods, and collaboration between public health authorities, and health care facilities can lower the risk of transmission and progression of disease [1,3,4] .…”

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confidence: 99%

See 2 more Smart Citations

Appraising the statewide escalation of Legionnaire disease in New Jersey and investigation of environmental cause: novel therapies and future recommendations

Ali

Nazir

Ali

et al. 2023

International Journal of Surgery: Global Health

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Legionella

Lindsay,

Ricci

2023

ClinMicroNow

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The family Legionellaceae is composed of a single genus, Legionella , and comprises 66 validly named species and three subspecies. Legionella pneumophila , Legionella micdadei , Legionella bozemanii , and Legionella longbeachae are the most important species from a clinical standpoint, with L. pneumophila causing more than 90% of Legionnaires' disease (LD) globally, apart from Australia and New Zealand, where L. longbeachae predominates. LD is a type of bacterial pneumonia caused by L. pneumophila and other Legionella spp . Identification of Legionella spp . in a clinical laboratory is optimally performed by observation of visual morphology, agglutination methods, and matrix‐assisted laser desorption ionization–time of flight mass spectrometry. Antimicrobial agents regarded as effective for treatment of LD are macrolides, fluoroquinolones, and, rarely, rifampin, all achieving adequate intracellular concentrations.

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Epidemiological analysis of Legionnaires' disease in Scotland: a genomic study

Cited by 12 publications

References 28 publications

High performanceLegionella pneumophilasource attribution using genomics-based machine learning classification

High performanceLegionella pneumophilasource attribution using genomics-based machine learning classification

Appraising the statewide escalation of Legionnaire disease in New Jersey and investigation of environmental cause: novel therapies and future recommendations

Legionella

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