Outbreak detection and secondary prevention of Legionnaires’ disease: A national approach

Boer, Jeroen W. Den; Verhoef, Linda; Bencini, Max A.; Bruin, Jacob P.; Jansen, Ruud; Yzerman, Ed P. F.

doi:10.1016/j.ijheh.2006.07.002

Cited by 30 publications

(13 citation statements)

References 18 publications

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“…In the Netherlands, a National Legionella Outbreak Detection Programme (NLODP) [10] was installed in 2002, which aimed to shorten response time between diagnosis of patients and source identification, and to improve source investigation and elimination. Together with the implementation of new governmental laws and guidelines to prevent growth of Legionella bacteria in potential sources, it was attempted to diminish the overall impact of Legionnaires’ disease in the Netherlands.…”

Section: Introductionmentioning

confidence: 99%

Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray

Euser

Nagelkerke

Schuren³

et al. 2012

PLoS ONE

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Background Legionella, the causative agent for Legionnaires’ disease, is ubiquitous in both natural and man-made aquatic environments. The distribution of Legionella genotypes within clinical strains is significantly different from that found in environmental strains. Developing novel genotypic methods that offer the ability to distinguish clinical from environmental strains could help to focus on more relevant (virulent) Legionella species in control efforts. Mixed-genome microarray data can be used to perform a comparative-genome analysis of strain collections, and advanced statistical approaches, such as the Random Forest algorithm are available to process these data.MethodsMicroarray analysis was performed on a collection of 222 Legionella pneumophila strains, which included patient-derived strains from notified cases in the Netherlands in the period 2002–2006 and the environmental strains that were collected during the source investigation for those patients within the Dutch National Legionella Outbreak Detection Programme. The Random Forest algorithm combined with a logistic regression model was used to select predictive markers and to construct a predictive model that could discriminate between strains from different origin: clinical or environmental.ResultsFour genetic markers were selected that correctly predicted 96% of the clinical strains and 66% of the environmental strains collected within the Dutch National Legionella Outbreak Detection Programme.ConclusionsThe Random Forest algorithm is well suited for the development of prediction models that use mixed-genome microarray data to discriminate between Legionella strains from different origin. The identification of these predictive genetic markers could offer the possibility to identify virulence factors within the Legionella genome, which in the future may be implemented in the daily practice of controlling Legionella in the public health environment.

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Section: Introductionmentioning

confidence: 99%

Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray

Euser

Nagelkerke

Schuren³

et al. 2012

PLoS ONE

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“…Following a large outbreak of infection in The Netherlands that involved 188 patients with LD [25], a national outbreak detection programme (NODP) was started on 1 August 2002 [26], with the aim of providing a short response time between the diagnosis of LD patients and the inspection and sampling of potential sources of infection. To identify potential sources during the incubation period, medical specialists in infectious disease control at the Regional Public Health Services carry out structured interviews (using a questionnaire) with the patient and/or a contact.…”

Section: Methodsmentioning

confidence: 99%

“…The interviews focus on tracking each patient’s exposure to potential sources of infection. Certain potential sources mentioned specifically in the questionnaire, e.g., swimming pools and saunas, were included on the basis of previous epidemiological and outbreak studies [26].…”

Section: Methodsmentioning

confidence: 99%

Genotypic comparison of clinical Legionella isolates and patient-related environmental isolates in The Netherlands, 2002–2006

Boer

Bruin

Verhoef

et al. 2008

Clinical Microbiology and Infection

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This study investigated the hypothesis that the genotype distribution of Legionella isolates from sporadic patients with Legionnaires' disease differs from that of Legionella strains in the environment. An amplified fragment-length polymorphism (AFLP) assay was used to genotype patient-derived and environmental Legionella isolates. The three Legionella pneumophila genotypes isolated most frequently from human respiratory secretions were AFLP types 004 Lyon, 010 London and 006 Copenhagen. These genotypes were cultured significantly less frequently from environmental samples (50% vs. 4%; p <0.001). The most frequently observed L. pneumophila serogroup 1 genotype among patient-derived isolates was 004 Lyon (32%). This genotype was cultured from only one of 6458 environmental samples. The positive sample contained 1.26 x 10(6) CFU/mL and originated from a whirlpool spa that had not been disinfected and had been maintained at 36 degrees C for several months. Overall, the distribution of genotypes differed significantly among patient and environmental isolates. A possible explanation is that virulent strains may exist in potential environmental sources at undetectable concentrations.

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“…In accordance with the National Legionella Outbreak Detection Programme that was installed in the Netherlands in 2002, an investigation was performed to find the source of infection [11]. During the source investigation, two potential sources were identified: (1) the house of the patient where he had used taps and shower, and (2) the metal processing company where he worked and was exposed to water-based cutting fluids, and a pressure test pump (Figure 1) that uses water to evaluate the quality of the produced industrial iron molds.…”

Section: Case Presentationmentioning

confidence: 99%

Legionnaires’ disease after using an industrial pressure test pump: a case report

et al. 2014

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IntroductionLegionnaires’ disease is an acute pneumonia caused by inhalation or aspiration of aerosols contaminated with Legionella bacteria. The majority (>90%) of Legionnaires’ disease cases are caused by the species Legionella pneumophila, and about 85% more specifically by L. pneumophila serogroup 1 that can be detected by a fast and easy to perform urinary antigen test. Previously reported sources of infection include cooling towers, plumbing systems of hospitals, and whirlpool spas, but for the majority of cases of Legionnaires’ disease the source of infection remains unknown.Case presentationA 52-year-old Caucasian man was admitted to a Dutch hospital with pneumonia, where a culture of the available bronchial lavage was found positive for L. pneumophila serogroup 3, confirming the diagnosis of Legionnaires’ disease. An environmental investigation identified a manually operated pressure test pump at the metal processing company where he worked as the source of infection: the water sample from the pump contained 9·8×103 colony forming units/L L. pneumophila, and sequence-based typing showed the same sequence type (ST93) for both the clinical and environmental strains.ConclusionThis case shows that Legionnaires’ disease can be acquired by exposure to relatively rare sources that are not considered in regular control and prevention measures.

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Outbreak detection and secondary prevention of Legionnaires’ disease: A national approach

Cited by 30 publications

References 18 publications

Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray

Genome Analysis of Legionella pneumophila Strains Using a Mixed-Genome Microarray

Genotypic comparison of clinical Legionella isolates and patient-related environmental isolates in The Netherlands, 2002–2006

Legionnaires’ disease after using an industrial pressure test pump: a case report

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