Legionnaires' Disease Outbreaks and Cooling Towers, New York City, New York, USA

Assessment of monitoring approaches to control Legionella pneumophila within a complex cooling tower system

Precise and rapid methods are needed to improve monitoring approaches of L. pneumophila (Lp) in cooling towers (CTs) to allow timely operational adjustments and prevent outbreaks. The performance of liquid culture (ASTM D8429-21) and an online qPCR device were first compared to conventional filter plate culture (ISO 11731-2017), qPCR and semi-automated qPCR at three spiked concentrations of Lp (serogroup 1) validated by flow cytometry (total/viable cell count). The most accurate was qPCR, followed by liquid culture, online and semi-automated qPCR, and lastly, by a significant margin, filter plate culture. An industrial CT system was monitored using liquid and direct plate culture by the facility, qPCR and online qPCR. Direct plate and liquid culture results agreed at regulatory sampling point, supporting the use of the faster liquid culture for monitoring culturable Lp. During initial operation, qPCR and online qPCR results were within one log of culture at the primary pump before deviating after first cleaning. Other points revealed high spatial variability of Lp. The secondary pumps and chiller had the most positivity and highest concentrations by both qPCR and liquid culture compared to the basin and infeed tank. Altogether, this suggests that results from monthly compliance sampling at a single location with plate culture are not representative of Lp risks in this CT due to the high temporal and spatial variability. The primary pump, rather than the CT basin, should be designated for sampling, as it is representative of the health risk. An annual multi point survey of the system should be conducted to identify and target Lp hot spots. Generally, a combination of liquid culture for compliance and frequent qPCR for process control provides a more agile and robust monitoring scheme than plate culture alone, enabling early treatment adjustments, due to lower limit of detection (LOD) and turnover time.

Effects of antimicrobials over sessile and planktonic microbiota associated with an industrial cooling water system

The bacterial community from a cooling water system was investigated through culture-dependent and independent strategies, and the responses of planktonic and sessile bacteria (grown in glass slides and stainless-steel coupons) to antimicrobials of industrial and clinical use were assessed. The morphotypes with higher biofilm-forming potential were Pseudoxanthomonas sp., Rheinheimera sp., Aeromonas sp. and Staphylococcus sp., and the first also exhibited lower susceptibility to all antibiotics and biocides tested. 16S rRNA high throughput sequencing indicated that Pseudomonadota (77.1% on average, sd 11.1%), Bacteroidota (8.4, sd 5.7%), and Planctomycetota (3.0, sd 1.3%) were the most abundant phyla. KEGG orthologs associated with antibiotics and biocide resistance were abundant in all samples. Although the minimum inhibitory and bactericidal concentrations were generally higher for biofilms, morphotypes in planktonic form also showed high levels of resistance, which could be associated with biofilm cells passing into the planktonic phase. Overall, monochloramine was the most effective biocide.

Correlation between bacterial microbiome and Legionella species in water from public bath facilities by 16S rRNA gene amplicon sequencing

Public bath facilities are a major source of Legionella infections in Japan. In this study, we performed 16S rRNA gene amplicon sequencing to characterize the bacterial community in bath and shower water from public bath facilities, along with chemical parameters, and investigated the effect of the bacterial microbiome on the presence of Legionella species. Although no significant difference in bacterial community richness was observed between bath and shower water samples, there was a remarkable difference in the bacterial community structure between them. Distance-based redundancy analysis revealed that several factors (free residual chlorine, pH, and conductivity) were correlated with the bacterial community in bath water. The most abundant bacterial genera in the samples were Pseudomonas (13.7%) in bath water and Phreatobacter (13.6%) in shower water, as indicated by the taxonomic composition, and the dominant bacteria differed between these environmental samples. Legionella pneumophila was the most frequently detected Legionella species, with additional 15 other Legionella species detected in water samples. In Legionella-positive water samples, several unassigned and uncultured bacteria were enriched together. In addition, the co-occurrence network showed that Legionella was strongly interconnected with two uncultured bacteria. Corynebacterium and Sphingomonas negatively correlated with Legionella species. The present study reveals the ecology of Legionella species, especially their interactions with other bacteria that are poorly understood to date.

IMPORTANCE

Public bath facilities are major sources of sporadic cases and outbreaks of Legionella infections. Recently, 16S rRNA gene amplicon sequencing has been used to analyze bacterial characteristics in various water samples from both artificial and natural environments, with a particular focus on Legionella bacterial species. However, the relationship between the bacterial community and Legionella species in the water from public bath facilities remains unclear. In terms of hygiene management, it is important to reduce the growth of Legionella species by disinfecting the water in public bath facilities. Our findings contribute to the establishment of appropriate hygiene management practices and provide a basis for understanding the potential health effects of using bath and shower water available in public bath facilities.

Water quality and microecosystem of water tanks in karst mountainous area, Southwest China

Karst mountainous areas in Southwest China, the world's largest bare karst area, are faced with growing water shortages. Rainwater harvesting plays an important role in alleviating water shortage. However, there remains a substantial gap in the research regarding the water quality of tanks. Water samples were seasonally collected from ten tanks to investigate the physicochemical properties, microbial communities, and their key influencing factors. The result showed that pH, turbidity, chroma, DOC, and CODMn exceeded drinking water guidelines. The alkaline pH value and the deterioration of sensory properties was the main feature of tank water, from which the over-standard rate of the uncleaned water tanks was higher. Moreover, principal component analyses suggested that tank water quality was influenced by human activities, catchment areas, and material cycling processes within the tanks, of which in-tank microbial activities were the most important driving factors in water quality variation. Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Verrucomicrobia were the predominant bacterial phyla in water tanks. Acinetobacter, Cyanobium-PCC-6307, CL500-29-marine-group, Candidatus-Aquiluna, and Exiguobacterium were the most abundant genera. The bacterial communities were significantly affected by the management practices. Higher relative abundance of Cyanobacteria and lower relative abundance of Proteobacteria was detected in the uncleaned tanks, which was a sign of tank water quality deterioration. The microbial community structure was closely related to the environmental factors. There was evidence that the water quality was affected by the existence of a microecosystem dominated by photosynthetic microorganisms in the water tanks. In addition, Acinetobacter, Enterobacter, Pseudomonas, and Legionella identified as the potential opportunistic pathogenic genera were frequently detected but the relative abundances except Acinetobacter were low in the tanks. Overall, our findings indicated that management style influences water quality and bacterial communities of tank water.

Clustering of SARS-CoV-2 in Households in New York City: A Building-Level Analysis, March-December 2020

OBJECTIVES

To identify the proportion of coronavirus disease 2019 (COVID-19) cases that occurred within households or buildings in New York City (NYC) beginning in March 2020 during the first stay-at-home order to determine transmission attributable to these settings and inform targeted prevention strategies.

DESIGN

The residential addresses of cases were geocoded (converting descriptive addresses to latitude and longitude coordinates) and used to identify clusters of cases residing in unique buildings based on building identification number (BIN), a unique building identifier. Household clusters were defined as 2 or more cases within 2 weeks of onset or diagnosis date in the same BIN with the same unit number, last name, or in a single-family home. Building clusters were defined as 3 or more cases with onset date or diagnosis date within 2 weeks in the same BIN who do not reside in the same household.

SETTING

NYC from March to December 2020.

PARTICIPANTS

NYC residents with a positive SARS-CoV-2 nucleic acid amplification or antigen test result with a specimen collected during March 1, 2020, to December 31, 2020.

MAIN OUTCOME MEASURE

The proportion of NYC COVID-19 cases in a household or building cluster.

RESULTS

The BIN analysis identified 65 343 building and household clusters: 17 139 (26%) building clusters and 48 204 (74%) household clusters. A substantial proportion of NYC COVID-19 cases (43%) were potentially attributable to household transmission in the first 9 months of the pandemic.

CONCLUSIONS

Geocoded address matching assisted in identifying COVID-19 household clusters. Close contact transmission within a household or building cluster was found in 43% of noncongregate cases with a valid residential NYC address. The BIN analysis should be utilized to identify disease clustering for improved surveillance.

Heterotrophic Plate Count Can Predict the Presence of Legionella spp. in Cooling Towers

Legionella pneumophila (Lp) colonizes aquatic environments and is a potential pathogen to humans, causing outbreaks of Legionnaire’s disease. It is mainly associated with contaminated cooling towers (CTs). Several regulations, including Spanish legislation (Sl), have introduced the analysis of heterotrophic plate count (HPC) bacteria and Legionella spp. (Lsp) in management plans to prevent and control Legionella outbreaks from CTs. The 2003 Sl for CTs (RD 865/2003) considered that concentrations of HPC bacteria ≤10,000 cfu/mL and of Lsp ≤100 cfu/L are safe; therefore, no action is required, whereas management actions should be implemented above these standards. We have investigated to what extent the proposed standard for HPC bacteria is useful to predict the presence of Lsp in cooling waters. For this, we analyzed Lsp and HPC concentrations, water temperature, and the levels of chlorine in 1376 water samples from 17 CTs. The results showed that in the 1138 water samples negative for Legionella spp. (LN), the HPC geometric mean was significantly lower (83 cfu/mL, p < 0.05) than in the positive Lsp. samples (135 cfu/mL). Of the 238 (17.3%) LP samples, 88.4% (210/238) were associated with values of HPC ≤10,000 cfu/mL and most of them showed HPC concentrations ≤100 (53.7%). In addition, a relatively low percentage of LP (28/238, 11.6%) samples were associated with HPC bacteria concentrations >10,000 cfu/mL, indicating that this standard does not predict the colonization risk for Legionella in the CTs studied. The present study has demonstrated that a threshold concentration ≤100 cfu/mL of HPC bacteria could better predict the higher concentration of Legionella in CTs, which will aid in preventing possible outbreaks.

Predicting Legionella contamination in cooling towers and evaporative condensers from microbiological and physicochemical parameters

BACKGROUND

Inhalation of Legionella-containing aerosols generated by cooling towers (CT) and evaporative condensers (EC) where water risk management is not performed correctly has been linked to a high percentage of community outbreaks of Legionnaires' disease (LD). Likewise, microbiological and physicochemical characteristics of the water in these facilities have been associated with this bacterium. The main aim of this study was to assess the risk of Legionella colonization in CT and EC based on the data for microbiological and physicochemical water quality provided by the Environmental Health Department and Laboratory of the City Council of L'Hospitalet de Llobregat (Barcelona, Spain).

METHODS

Legionella was analysed in 789 samples collected from 127 CT and EC in 46 companies in Catalonia from 2002 to 2019. A two-step logistic regression analysis was carried out to assess the risk of colonization by Legionella in the studied facilities according to the microbiological (aerobic heterotrophic bacteria) and physicochemical (pH, alkalinity, hardness, turbidity, conductivity, total iron and Langelier Index) water parameters. The optimal cut-off points for the water parameters predictive of Legionella contamination were defined as the values on the receiver operating characteristic (ROC) curve where sensitivity and specificity were jointly maximized.

RESULTS

Legionella was isolated in 8.49% of the 789 analysed samples, 22.39% of which were heavily contaminated (with counts higher than 1.0 × 10⁴ CFU/l). L. pneumophila was isolated in 82.09% of the samples, with 41.82% belonging to serogroup 1. Logistic regression analysis revealed that aerobic heterotrophic bacteria concentrations ≥6.90 × 10² CFU/ml [Odds ratios (OR) (95% CI) = 3.56 (1.39-9.43), p = 0.01], a pH ≥ 8.70 [OR (95% CI) = 3.60 (1.34-10.09), p = 0.01], and water hardness ≥5.72 × 10² mg/l [OR (95% CI) = 6.30 (2.34-18.56), p < 0.001] were each independently associated with a higher risk of CT and EC colonization by Legionella.

CONCLUSIONS

The present study shows the importance of risk assessment for improving the control measures aimed at preventing or reducing Legionella populations in CT and EC, thus minimizing potential dangers for public health.

Genome analysis of Legionella pneumophila ST23 from various countries reveals highly similar strains

ST23 isolated in Italy are analysed by cgMLST and SNP approaches and they are also compared with ST23 from other countries. They are found to be phylogenetically related independently on year, town, or country of isolation.

Legionella pneumophila serogroup 1 (Lp1) sequence type (ST) 23 is one of the most commonly detected STs in Italy where it currently causes all investigated outbreaks. ST23 has caused both epidemic and sporadic cases between 1995 and 2018 and was analysed at genomic level and compared with ST23 isolated in other countries to determine possible similarities and differences. A core genome multi-locus sequence typing (cgMLST), based on a previously described set of 1,521 core genes, and single-nucleotide polymorphisms (SNPs) approaches were applied to an ST23 collection including genomes from Italy, France, Denmark and Scotland. DNAs were automatically extracted, libraries prepared using NextEra library kit and MiSeq sequencing performed. Overall, 63 among clinical and environmental Italian Lp1 isolates and a further seven and 11 ST23 from Denmark and Scotland, respectively, were sequenced, and pangenome analysed. Both cgMLST and SNPs analyses showed very few loci and SNP variations in ST23 genomes. All the ST23 causing outbreaks and sporadic cases in Italy and elsewhere, were phylogenetically related independent of year, town or country of isolation. Distances among the ST23s were further shortened when SNPs due to horizontal gene transfers were removed. The Lp1 ST23 isolated in Italy have kept their monophyletic origin, but they are phylogenetically close also to ST23 from other countries. The ST23 are quite widespread in Italy, and a thorough epidemiological investigation is compelled to determine sources of infection when this ST is identified in both LD sporadic cases and outbreaks.

Evaporative misters for urban cooling and comfort: effectiveness and motivations for use

Thermal comfort is an important determinant of quality of life and economic vitality in cities. Strategies to improve thermal comfort may become a more critical part of urban sustainability efforts with projections of continued urban growth and climate change. A case study was performed in the hot, dry summertime climate of Tempe, Arizona to quantify the influence of evaporative misters on the thermal environment in outdoor restaurants and to understand business managers' motivations to use misters. Microclimate measurements (air temperature (T_a), wind speed, relative humidity, globe temperature) were taken at five restaurants midday within four exposures: misted sun, misted shade, sun only, and shade only. We assessed T_a, mean radiant temperature (MRT), universal thermal climate index (UTCI), and physiological equivalent temperature (PET) between these four conditions within each location. Misters improved thermal comfort across all days, sites, and exposure conditions. MRT was on average 7.6 °C lower in misted locations, which significantly lowered average PET (- 6.5 °C) and UTCI (- 4.4 °C) (p < 0.05). Thermal comfort was most improved using mist in combination with shade. Under such conditions, PET and UTCI were reduced by 15.5 °C and 9.7 °C (p < 0.05), respectively. Business managers identified customer comfort and increased seating capacity as the principal factors for mister use. Esthetics of misters further encouraged use, while cost and environmental concerns were perceived to be less important. While this case study demonstrates value in outdoor misting in a hot, dry climate, additional work is needed to more fully evaluate tradeoffs between cost, water use, and comfort with continuing urban growth.

Risk assessment and disease burden of legionella presence in cooling towers of Iran's central hospitals

Regular monitoring and measurement of Legionella in tower water and preventive measures against contamination are particularly important in hospitals. This study aimed at risk assessment and disease burden because of legionella presence in cooling towers of Iran's central hospitals. Then its correlation with temperature, pH, turbidity, residual chlorine, and EC was investigated by the Pearson test. The health risk and burden of diseases caused by Legionella exposure were determined using QMRA and DALY models. Statistical analysis and modeling were performed in MATLAB₂₀₁₈. Of the total samples, 30-43% was infected with Legionella. The mean concentrations in hospital A and B were 5-102.5 ± 10 and 5-89.7 ± 0.7 CFU/L, respectively. Among environmental factors, turbidity and pH were the most effective factors in increasing and decreasing Legionella concentration, respectively. According to the QMRA model, the risks of Legionella infections and annual mortality in both hospitals were 0.2-0.3, 0-0.19, 2-2.9 × 10^-5, and 0-0.7 × 10^-5, respectively, which was higher than the acceptable risk range for Legionella (10-4-10-7). However, the trend of its change was negatively correlated with time (R_B = - 0.77). According to the results, the concentration of Legionella and the exposure risk in both hospitals were higher than the permissible range, which is necessary to decrease to 0.1 current concentrations.

Next generation sequencing approaches to evaluate water and wastewater quality

The emergence of next generation sequencing (NGS) is revolutionizing the potential to address complex microbiological challenges in the water industry. NGS technologies can provide holistic insight into microbial communities and their functional capacities in water and wastewater systems, thus eliminating the need to develop a new assay for each target organism or gene. However, several barriers have hampered wide-scale adoption of NGS by the water industry, including cost, need for specialized expertise and equipment, challenges with data analysis and interpretation, lack of standardized methods, and the rapid pace of development of new technologies. In this critical review, we provide an overview of the current state of the science of NGS technologies as they apply to water, wastewater, and recycled water. In addition, a systematic literature review was conducted in which we identified over 600 peer-reviewed journal articles on this topic and summarized their contributions to six key areas relevant to the water and wastewater fields: taxonomic classification and pathogen detection, functional and catabolic gene characterization, antimicrobial resistance (AMR) profiling, bacterial toxicity characterization, Cyanobacteria and harmful algal bloom identification, and virus characterization. For each application, we have presented key trends, noteworthy advancements, and proposed future directions. Finally, key needs to advance NGS technologies for broader application in water and wastewater fields are assessed.

Pathogenicity and Virulence of Legionella: Intracellular replication and host response

Bacteria of the genus Legionella are natural pathogens of amoebae that can cause a severe pneumonia in humans called Legionnaires’ Disease. Human disease results from inhalation of Legionella-contaminated aerosols and subsequent bacterial replication within alveolar macrophages. Legionella pathogenicity in humans has resulted from extensive co-evolution with diverse genera of amoebae. To replicate intracellularly, Legionella generates a replication-permissive compartment called the Legionella-containing vacuole (LCV) through the concerted action of hundreds of Dot/Icm-translocated effector proteins. In this review, we present a collective overview of Legionella pathogenicity including infection mechanisms, secretion systems, and translocated effector function. We also discuss innate and adaptive immune responses to L. pneumophila, the implications of Legionella genome diversity and future avenues for the field.

Evaluation of Legiolert™ for the Detection of Legionella pneumophila and Comparison with Spread-Plate Culture and qPCR Methods

Legionella pneumophila, the organism responsible for Legionnaires' disease, a potentially lethal pneumonia, is an opportunistic bacterium spread via inhalation of contaminated, aerosolized water. The detection and control of L. pneumophila is crucial to reduce the risk it poses to human health. L. pneumophila is generally detected and quantified by the plating method, ISO 11731:2017 and by qPCR. ISO 11731 is based on the filtration of the water sample through a membrane, which is placed on selective agar medium, and after colony growth, presumptive Legionella are then confirmed by subculturing, serology, or PCR. Quantitative Polymerase Chain Reaction (qPCR) is based on the amplification of a DNA sequence specific to L. pneumophila, usually within the mip gene. The objective of this study was to compare these methods to a new, liquid culture method based on the Most Probable Number (MPN) technique, Legiolert™/Quanti-Tray® with data obtained with ISO 11731 and a viability quantitative qPCR (v-qPCR), for quantification of L. pneumophila in potable and non-potable waters. Data showed that the Legiolert method revealed concentrations of L. pneumophila greater than ISO 11731 and generally similar results to those of v-qPCR. The Legiolert method was highly specific and easy to use, representing a significant advancement in the quantification of L. pneumophila from potable and non-potable waters.

Multi-Scale Airborne Infectious Disease Transmission

Airborne disease transmission is central to many scientific disciplines including agriculture, veterinary biosafety, medicine, and public health. Legal and regulatory standards are in place to prevent agricultural, nosocomial, and community airborne disease transmission. However, the overall importance of the airborne pathway is underappreciated, e.g.,, US National Library of Medicine's Medical Subjects Headings (MESH) thesaurus lacks an airborne disease transmission indexing term. This has practical consequences as airborne precautions to control epidemic disease spread may not be taken when airborne transmission is important, but unrecognized. Publishing clearer practical methodological guidelines for surveillance studies and disease outbreak evaluations could help address this situation.To inform future work, this paper highlights selected, well-established airborne transmission events - largely cases replicated in multiple, independently conducted scientific studies. Methodologies include field experiments, modeling, epidemiology studies, disease outbreak investigations and mitigation studies. Collectively, this literature demonstrates that airborne viruses, bacteria, and fungal pathogens have the capability to cause disease in plants, animals, and humans over multiple distances - from near range (< 5 m) to continental (> 500 km) in scale. The plausibility and implications of undetected airborne disease transmission are discussed, including the notable underreporting of disease burden for several airborne transmitted diseases.

Water Sampling Module for Collecting and Concentrating Legionella pneumophila from Low-to-Medium Contaminated Environment

The detection of water contamination with Legionella pneumophila is of critical importance to manufacturers of water processing equipment and public health entities dealing with water networks and distribution systems. Detection methods based on polymerase chain reaction or biosensor technologies require preconcentration steps to achieve attractive sensitivity levels. Preconcentration must also be included in protocols of automated collection of water samples by systems designed for quasi-continuous monitoring of remotely located water reservoirs for the presence of L. pneumophila. We designed and characterized a water sampling module for filtration and backwashing intended for analysis of low-to-medium contaminated water, typically with L. pneumophila bacteria not exceeding 50 colony-forming units per milliliter. The concentration factors of 10× and 21× were achieved with 0.22 and 0.45 µm filters, respectively, for samples of bacteria prepared in clean saline solutions. However, a 5× concentration factor was achieved with 0.45 µm filters for a heavily contaminated or turbid water typical of some industrial water samples.

Unravelling the importance of the eukaryotic and bacterial communities and their relationship with Legionella spp. ecology in cooling towers: a complex network

BACKGROUND

Cooling towers are a major source of large community-associated outbreaks of Legionnaires' disease, a severe pneumonia. This disease is contracted when inhaling aerosols that are contaminated with bacteria from the genus Legionella, most importantly Legionella pneumophila. How cooling towers support the growth of this bacterium is still not well understood. As Legionella species are intracellular parasites of protozoa, it is assumed that protozoan community in cooling towers play an important role in Legionella ecology and outbreaks. However, the exact mechanism of how the eukaryotic community contributes to Legionella ecology is still unclear. Therefore, we used 18S rRNA gene amplicon sequencing to characterize the eukaryotic communities of 18 different cooling towers. The data from the eukaryotic community was then analysed with the bacterial community of the same towers in order to understand how each community could affect Legionella spp. ecology in cooling towers.

RESULTS

We identified several microbial groups in the cooling tower ecosystem associated with Legionella spp. that suggest the presence of a microbial loop in these systems. Dissolved organic carbon was shown to be a major factor in shaping the eukaryotic community and may be an important factor for Legionella ecology. Network analysis, based on co-occurrence, revealed that Legionella was correlated with a number of different organisms. Out of these, the bacterial genus Brevundimonas and the ciliate class Oligohymenophorea were shown, through in vitro experiments, to stimulate the growth of L. pneumophila through direct and indirect mechanisms.

CONCLUSION

Our results suggest that Legionella ecology depends on the host community, including ciliates and on several groups of organisms that contribute to its survival and growth in the cooling tower ecosystem. These findings further support the idea that some cooling tower microbiomes may promote the survival and growth of Legionella better than others. Video Abstract.

A Snapshot of the Prevalence and Molecular Diversity of Legionella pneumophila in the Water Systems of Israeli Hotels

Exposure to Legionella spp. contaminated aerosols in hotel settings confers risk for travel-associated Legionnaire’s disease (TALD). In this study, we investigated the prevalence of Legionella contamination and its molecular diversity in hotels and resorts across Israel. The study was comprised of a convenience sample of water systems from 168 hotels and resorts countrywide, routinely inspected between March 2015 and February 2017. Isolation and quantitation of Legionella were performed in a water laboratory using the ISO 11731 method. The distribution of Legionella isolates was analyzed according to geography and source. The genetic diversity of a subset of isolates was analyzed by sequence-based typing (SBT) at the National Reference Laboratory for Legionella and compared to the national database. Out of 2830 samples tested, 470 (17%) obtained from 102 different premises (60% of hotels) were positive for Legionella spp. In 230 samples (49% of all positive, 8% of total samples), accounting for 37% of hotels, Legionella spp. counts exceeded the regulatory threshold of 1000 CFU/L. The most frequently contaminated water sources were cooling towers (38%), followed by faucets, hot tubs, water lines, and storage tanks (14–17% each). Furthermore, 32% and 17% of samples obtained from cooling towers and hot tubs, respectively, exceeded the regulatory thresholds. SBT was performed on 78 strains and revealed 27 different sequence types (STs), including two novel STs. The most prevalent STs found were ST1 (26%), ST87 (10%), ST93 (6%), and ST461 and ST1516 (5% each). Several L. pneumophila STs were found to be limited to certain geographical regions. This is the first study to investigate the prevalence and diversity of Legionella in hotels and resorts in Israel during non-outbreak environmental inspections. These findings will inform risk assessment, surveillance, and control measures of TALD.

Epidemiologic Survey of Legionella Urine Antigen Testing Within a Large Wisconsin-Based Health Care System

Purpose

Legionella pneumophila pneumonia is a life-threatening, environmentally acquired infection identifiable via Legionella urine antigen tests (LUAT). We aimed to identify cumulative incidence, demographic distribution, and undetected disease outbreaks of Legionella pneumonia via positive LUAT in a single eastern Wisconsin health system, with a focus on urban Milwaukee County.

Methods

A multilevel descriptive ecologic study was conducted utilizing electronic medical record data from a large integrated health care system of patients who underwent LUAT from 2013 to 2017. A random sample inclusive of all positive tests was reviewed to investigate geodemographic differences among patients testing positive versus negative. Statistical comparisons used chi-squared or 2-sample t-tests; stepwise regression followed by binary logistic regression was used for multivariable analysis. Positive cases identified by LUAT were mapped to locate hotspots; positive cases versus total tests performed also were mapped by zip code.

Results

Of all LUAT performed (n=21,599), 0.68% were positive. Among those in the random sample (n=11,652), positive cases by LUAT were more prevalent in the June-November time period (86.2%) and younger patients (59.4 vs 67.7 years) and were disproportionately male (70.3% vs 29.7%) (P<0.0001 for each). Cumulative incidence was higher among nonwhite race/ethnicity (1.91% vs 1.01%, P<0.0001) but did not remain significant on multivariable analysis. Overall, 5507 tests were performed in Milwaukee County zip codes, yielding 82 positive cases by LUAT (60.7% of all positive cases in the random sample). A potential small 2016 outbreak was identified.

Conclusions

Cumulative incidence of a positive LUAT was less than 1%. LUAT testing, if done in real time by cooperative health systems, may complement public health detection of Legionella pneumonia outbreaks.

Impact of temperature on Legionella pneumophila, its protozoan host cells, and the microbial diversity of the biofilm community of a pilot cooling tower

Legionella pneumophila is a waterborne bacterium known for causing Legionnaires' Disease, a severe pneumonia. Cooling towers are a major source of outbreaks, since they provide ideal conditions for L. pneumophila growth and produce aerosols. In such systems, L. pneumophila typically grow inside protozoan hosts. Several abiotic factors such as water temperature, pipe material and disinfection regime affect the colonization of cooling towers by L. pneumophila. The local physical and biological factors promoting the growth of L. pneumophila in water systems and its spatial distribution are not well understood. Therefore, we built a lab-scale cooling tower to study the dynamics of L. pneumophila colonization in relationship to the resident microbiota and spatial distribution. The pilot was filled with water from an operating cooling tower harboring low levels of L. pneumophila. It was seeded with Vermamoeba vermiformis, a natural host of L. pneumophila, and then inoculated with L. pneumophila. After 92 days of operation, the pilot was disassembled, the water was collected, and biofilm was extracted from the pipes. The microbiome was studied using 16S rRNA and 18S rRNA genes amplicon sequencing. The communities of the water and of the biofilm were highly dissimilar. The relative abundance of Legionella in water samples reached up to 11% whereas abundance in the biofilm was extremely low (≤0.5%). In contrast, the host cells were mainly present in the biofilm. This suggests that L. pneumophila grows in host cells associated with biofilm and is then released back into the water following host cell lysis. In addition, water temperature shaped the bacterial and eukaryotic community of the biofilm, indicating that different parts of the systems may have different effects on Legionella growth.

Multistate analysis of prospective Legionnaires' disease cluster detection using SaTScan, 2011-2015

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.

Analysis of Genetic Characterization and Clonality of Legionella pneumophila Isolated from Cooling Towers in Japan

We investigated the genetic characteristics of 161 Legionella pneumophila strains isolated over a period of 10 years from cooling towers in Japan. Minimum spanning tree analysis based on the sequence-based typing (SBT) of them identified three clonal complexes (CCs); CC1 (105/161, 65.2%), CC2 (22 /161, 13.7%), and CC3 (20/161, 12.4%). CC1 was formed by serogroup (SG) 1 and SG7, whereas CC2 was mainly formed by SG1. All of the CC3 isolates except two strains were SG13. The major sequence types (STs) in CC1 and CC2 were ST1 (88/105, 83.8%) and ST154 (15/22, 68.2%), respectively. These STs are known as typical types of L. pneumophila SG1 in Japanese cooling tower. Additionally, we identified 15 strains of ST2603 as the major type in CC3. This ST has not been reported in Japanese cooling tower. Whole genome sequencing (WGS) analysis of the representative strains in the three CCs, which were isolated from various cooling towers over the 10 years, elucidated high clonal population of L. pneumophila in Japanese cooling tower. Moreover, it revealed that the strains of CC2 are phylogenetically distant compared to those of CC1 and CC3, and belonged to L. pneumophila subsp. fraseri.

Simulation of Legionnaires' disease prospective spatiotemporal cluster detection, Allegheny County, Pennsylvania, USA

Legionnaires' disease (LD) incidence in the USA has quadrupled since 2000. Health departments must detect LD outbreaks quickly to identify and remediate sources. We tested the performance of a system to prospectively detect simulated LD outbreaks in Allegheny County, Pennsylvania, USA. We generated three simulated LD outbreaks based on published outbreaks. After verifying no significant clusters existed in surveillance data during 2014-2016, we embedded simulated outbreak-associated cases into 2016, assigning simulated residences and report dates. We mimicked daily analyses in 2016 using the prospective space-time permutation scan statistic to detect clusters of ⩽30 and ⩽180 days using 365-day and 730-day baseline periods, respectively. We used recurrence interval (RI) thresholds of ⩾20, ⩾100 and ⩾365 days to define significant signals. We calculated sensitivity, specificity and positive and negative predictive values for daily analyses, separately for each embedded outbreak. Two large, simulated cooling tower-associated outbreaks were detected. As the RI threshold was increased, sensitivity and negative predictive value decreased, while positive predictive value and specificity increased. A small, simulated potable water-associated outbreak was not detected. Use of a RI threshold of ⩾100 days minimised time-to-detection while maximizing positive predictive value. Health departments should consider using this system to detect community-acquired LD outbreaks.