Under the Weather: Legionellosis and Meteorological Factors

The Presence of Legionella in Water Used for Car Washing: Implications for Public Health

Although today all of the aspects of Legionella are better understood than in the past, in many countries the interest is still mainly focused on healthcare and tourism facilities. Other at-risk areas are less explored, such as those where workers are often in contact with water during their activities. In reality, any water system capable of producing aerosols can be considered a potential source of Legionella transmission, including car washes, where a large number of users work and flow through annually. From January to May 2022, 120 samples were carried out in 30 car washes located in Messina (Italy): 60 samples of water and 60 of aerosols. The aim of this investigation was to evaluate the risk of legionellosis in car washing workers exposed to potentially contaminated aerosols. To increase the probability of finding Legionella, the sample collections were organized on different days of the week. Of the total samples taken, 10 (8.3%) were positive for Legionella: seven (11.7%) water (range 100-1000 CFU) and three (5%) aerosol (range 10-150 CFU) samples. Detected serogroups were L. pneumophila sgr 1, 7, 10 and Legionella gormanii. Given the results obtained, preventative measures should be implemented in such facilities in order to protect the health of users and car wash operators.

Impacts of weather and air pollution on Legionnaires' disease in Switzerland: A national case-crossover study

BACKGROUND

The number of reported cases of Legionnaires' disease (LD) has risen markedly in Switzerland (6.5/100,000 inhabitants in 2021) and abroad over the last decade. Legionella, the causative agent of LD, are ubiquitous in the environment. Therefore, environmental changes can affect the incidence of LD, for example by increasing bacterial concentrations in the environment or by facilitating transmission.

OBJECTIVES

The aim of this study is to understand the environmental determinants, in particular weather conditions, for the regional and seasonal distribution of LD in Switzerland.

METHODS

We conducted a series of analyses based on the Swiss LD notification data from 2017 to 2021. First, we used a descriptive and hotspot analysis to map LD cases and identify regional clusters. Second, we applied an ecological model to identify environmental determinants on case frequency at the district level. Third, we applied a case-crossover design using distributed lag non-linear models to identify short-term associations between seven weather variables and LD occurrence. Lastly, we performed a sensitivity analysis for the case-crossover design including NO2 levels available for the year 2019.

RESULTS

Canton Ticino in southern Switzerland was identified as a hotspot in the cluster analysis, with a standardised notification rate of 14.3 cases/100,000 inhabitants (CI: 12.6, 16.0). The strongest association with LD frequency in the ecological model was found for large-scale factors such as weather and air pollution. The case-crossover study confirmed the strong association of elevated daily mean temperature (OR 2.83; CI: 1.70, 4.70) and mean daily vapour pressure (OR: 1.52, CI: 1.15, 2.01) 6-14 days before LD occurrence.

DISCUSSION

Our analyses showed an influence of weather with a specific temporal pattern before the onset of LD, which may provide insights into the effect mechanism. The relationship between air pollution and LD and the interplay with weather should be further investigated.

Legionellosis on the rise: A scoping review of sporadic, community-acquired incidence in the United States

Over the past two decades, the incidence of legionellosis has been steadily increasing in the United States though there is noclear explanation for the main factors driving the increase. While legionellosis is the leading cause of waterborne outbreaks in the US, most cases are sporadic and acquired in community settings where the environmental source is never identified. This scoping review aimed to summarise the drivers of infections in the USA and determine the magnitude of impact each potential driver may have. A total of 1,738 titles were screened, and 18 articles were identified that met the inclusion criteria. Strong evidence was found for precipitation as a major driver, and both temperature and relative humidity were found to be moderate drivers of incidence. Increased testing and improved diagnostic methods were classified as moderate drivers, and the ageing U.S. population was a minor driver of increasing incidence. Racial and socioeconomic inequities and water and housing infrastructure were found to be potential factors explaining the increasing incidence though they were largely understudied in the context of non-outbreak cases. Understanding the complex relationships between environmental, infrastructure, and population factors driving legionellosis incidence is important to optimise mitigation strategies and public policy.

Associations of household factors, hot water temperature, and chlorine residual with Legionella occurrence in single-family homes in New Jersey

Only 4 % of reported Legionnaires' disease (LD) cases are outbreak-associated and the remaining 96 % are sporadic, for which no known source of Legionella is identified. Although outbreaks of LD are linked to cooling towers, decorative fountains, spas and hot tubs, and other sources, the drivers of sporadic LD are less known. Residential premise plumbing is likely an important source of aerosol exposure and there are unique features of premise plumbing which could lead to proliferation of Legionella. A sampling study of Legionella in single-family homes was undertaken in NJ from 2020 to 2021 which included a household characteristic survey and collection of hot water temperature and chlorine residual during sampling. A total of 94 homeowners residing in owner-occupied, single-family units with individual hot water systems were recruited to participate through two mechanisms (1) Legionnaire's disease case-patients and (2) non-case volunteers from each NJ county. Among the 94 single-family homes sampled, 15 % had least one sample positive for Legionella by culture and 57 % had at least one sample with detection of Legionella DNA markers by PCR. Chlorine residual, hot water temperature, and season were independently associated with increased detection of Legionella in home water samples. There was limited or inconsistent evidence of the role of household characteristic factors in Legionella detection. This study identified season, insufficient chlorine residual and hot water temperature as risk factors for Legionella detection in single-family homes. Findings from this work can promote additional partnership between public health and water utilities in improving chlorine residuals in residential communities and educating homeowners on best practices for home water management.

Legionella monitoring results by water quality characteristics in a large public water system

Legionella, the causative agent of Legionnaires' disease, is an emerging concern for water utilities. Passaic Valley Water Commission (PVWC) is a public drinking water supplier, which provides treated surface water to approximately 800,000 customers in New Jersey. To evaluate the occurrence of Legionella in the PVWC distribution system, swab, first draw, and flushed cold water samples were collected from total coliform sites (n = 58) during a summer and winter sampling event. Endpoint PCR detection methods were combined with culture for Legionella detection. Among 58 total coliform sites during the summer, 17.2% (10/58) of first draw samples were positive for 16S and mip Legionella DNA markers and 15.5% (9/58) in flushed samples. Across both summer and winter sampling, a total of four out of 58 sites had low-level culture detection of Legionella spp. (0.5-1.6 CFU/mL) among first draw samples. Only one site had both a first and flush draw detection (8.5 CFU/mL and 1.1 CFU/mL) for an estimated culture detection frequency of 0% in the summer and 1.7% in the winter among flushed draw samples. No L. pneumophila was detected by culture. Legionella DNA detection was significantly greater in the summer than in the winter, and detection was greater in samples collected from areas treated with phosphate. No statistical difference was found between first draw and flush sample detection. Total organic carbon, copper, and nitrate were significantly associated with Legionella DNA detection.

Temporal trends in legionellosis national notification data and the effect of COVID-19, Switzerland, 2000-2020

The notification rate of legionellosis in Switzerland and other European countries has markedly increased over the last 20 years. Here, we investigated the Swiss notification data on legionellosis from 2000 to 2020 in regards of overall time trend, content and data quality. We further explored the impact of the COVID-19 pandemic on the reported case numbers using an interrupted time series approach. Between 2000 and 2020, 5980 cases were included in our analysis. The annual crude notification rate for legionellosis cases increased from 1.1/100,000 population (CI: 0.9-1.4) in 2000 to 5.6/100,000 population (CI: 5.1-6.1) in 2020. In recent years, the summer peaks have been more pronounced and some shifted earlier in the year. The highest notification rate was recorded in 2018 with 6.7/100,000 population (CI: 6.2-7.3). The hospitalisation rate for notified cases remained high across all study years (89.9%), while the case fatality rate slightly decreased (from 7.7% to 3.6%). COVID-19 containment measures, such as travel restrictions and/or related behavioural changes, are associated with a temporary decline in cases of 35%. Overall, the quality of the notification data was good. Clinical data were more susceptible to interferences than data from laboratory reporting, which could be observed most clearly in the decline of clinical reports by 4.3 percentage points in 2020. As the case classification for Legionnaires' disease includes pneumonia symptoms, this decline could lead to an underestimation of Legionnaires' disease cases, yet the continuous reporting though the diagnostic laboratories suggested a robust surveillance system for legionellosis in Switzerland.

Meteorological conditions and Legionnaires' disease sporadic cases-a systematic review

A number of studies suggest that meteorological conditions are related to the risk of Legionnaires' disease (LD) but the findings are not consistent. A systematic review was conducted to investigate the association of weather with sporadic LD and highlight the key meteorological conditions related to this outcome. PubMed, EMBASE, The Cochrane Library and OpenGrey were searched on 26-27 March 2020 without date, language or location restrictions. Key words included "legionellosis", "legionnaires' disease", combined with "meteorological conditions", "weather", "temperature", "humidity", "rain", "ultraviolet rays", "wind speed", etc. Studies were excluded if they did not examine the exposure of interest, the outcome of interest and their association or if they only reported LD outbreak cases. The study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and it was registered in PROSPERO (#CRD42020168869). There were 811 articles, of which 17 were included in the review. The studies investigated different meteorological variables and most of them examined the combined effect of several variables. The most commonly examined factors were precipitation and temperature, followed by relative humidity. The studies suggested that increased precipitation, temperature and relative humidity were positively associated with the incidence of LD. There was limited evidence that higher wind speed, pressure, visibility, UV radiation and longer sunshine duration were inversely linked with the occurrence of LD. A period of increased but not very high temperatures, followed by a period of increased precipitation, favour the occurrence of LD. Increased awareness of the association of temperature and precipitation and LD occurrence among clinicians and public health professionals can improve differential diagnosis for cases of sporadic community-acquired pneumonia and at the same time contribute to improving LD surveillance.

A review of legionnaires' disease and public water systems - Scientific considerations, uncertainties and recommendations

Legionella is an opportunistic premise plumbing pathogen and causative agent of a severe pneumonia called Legionnaires' Disease (LD). Cases of LD have been on the rise in the U.S. and globally. Although Legionella was first identified 45 years ago, it remains an 'emerging pathogen." Legionella is part of the normal ecology of a public water system and is frequently detected in regulatory-compliant drinking water. Drinking water utilities, regulators and public health alike are increasingly required to have a productive understanding of the evolving issues and complex discussions of the contribution of the public water utility to Legionella exposure and LD risk. This review provides a brief overview of scientific considerations important for understanding this complex topic, a review of findings from investigations of public water and LD, including data gaps, and recommendations for professionals interested in investigating public water utilities. Although the current literature is inconclusive in identifying a public water utility as a sole source of an LD outbreak, the evidence is clear that minimizing growth of Legionella in public water utilities through proper maintenance and sustained disinfectant residuals, throughout all sections of the water utility, will lead to a less conducive environment for growth of the bacteria in the system and the buildings they serve.

Increased risk of Legionella pneumonia as community-acquired pneumonia after heavy rainfall in 2018 in west Japan

INTRODUCTION

Japan experienced a heavy rainfall event from June 28 to July 8, 2018, and many casualties were caused by both heavy rainfall and flooding. Few studies have investigated patients' characteristics and the causative pathogens of community-acquired pneumonia before and after heavy rainfall events. The aim of the present study was to evaluate the causative pathogens and clinical characteristics of hospitalized patients with community-acquired pneumonia before and after the heavy rainfall event using prospective cohort data.

METHODS

The study was divided into two periods: July to November 2013-2017 (before heavy rainfall) and July to November 2018 (after heavy rainfall). The patients' clinical characteristics and causative pathogens before and after the heavy rainfall were investigated. Regarding the causative pathogens, adjustments were made for precipitation and seasonal patterns.

RESULTS

There were no significant differences in the number and clinical characteristics of patients before and after heavy rainfall. However, the frequency of Legionella pneumonia was significantly higher after than before the heavy rainfall event (8.9% vs 3.0%, P = 0.02) and remained significant after adjusting for precipitation and season. Three of 7 Legionella pneumonia patients engaged in reconstruction work and 2 Legionella pneumonia patients had soil exposure.

CONCLUSIONS

An increased risk of Legionella pneumonia after not only rainfall and serious flooding, but also following recovery work or soil exposure should be considered.

Relationship of meteorological factors and air pollutants with medical care utilization for gastroesophageal reflux disease in urban area

BACKGROUND

Gastroesophageal reflux disease (GERD) is a highly prevalent disease of the upper gastrointestinal tract, and it is associated with environmental and lifestyle habits. Due to an increasing interest in the environment, several groups are studying the effects of meteorological factors and air pollutants (MFAPs) on disease development.

AIM

To identify MFAPs effect on GERD-related medical utilization.

METHODS

Data on GERD-related medical utilization from 2002 to 2017 were obtained from the National Health Insurance Service of Korea, while those on MFAPs were obtained from eight metropolitan areas and merged. In total, 20071900 instances of GERD-related medical utilizations were identified, and 200000 MFAPs were randomly selected from the eight metropolitan areas. Data were analyzed using a multivariable generalized additive Poisson regression model to control for time trends, seasonality, and day of the week.

RESULTS

Five MFAPs were selected for the prediction model. GERD-related medical utilization increased with the levels of particulate matter with a diameter ≤ 2.5 μm (PM_2.5) and carbon monoxide (CO). S-shaped and inverted U-shaped changes were observed in average temperature and air pollutants, respectively. The time lag of each variable was significant around nine days after exposure.

CONCLUSION

Using five MFAPs, the final model significantly predicted GERD-related medical utilization. In particular, PM_2.5 and CO were identified as risk or aggravating factors for GERD.

Legionnaires' Disease on the Rise in Switzerland: A Denominator-Based Analysis of National Diagnostic Data, 2007-2016

The risk of falling ill with Legionnaires' disease (LD) is suggested to increase, but the global burden of disease is unknown due to a lack of appropriate diagnosis and surveillance systems. In Switzerland, the number of LD cases, captured by the National Notification System for Infectious Diseases, has more than doubled since 2008. This study aims to investigate this increase, contextualizing disease surveillance data with denominator data, which is not routinely available, i.e., the number of tests performed for Legionella spp. We collected the testing data for Legionella spp. of 14 Swiss diagnostic laboratories and calculated the positivity, defined as the proportion of the number of positive tests to the number of tests performed. The number of positive tests increased proportionally to the number of tests performed; hence, the positivity remained stable. However, the cause of the increase in test volume is unclear and has a large impact on the interpretation of the positivity curve. Further, the test outcome was found to be dependent on regional determinants, and the diagnostic method applied. The lack of understanding if and at which stage LD is considered in current case management of pneumonia patients limits the interpretation of observed heterogeneities in incidence or underestimation of LD in Switzerland. The absence of (or non-adherence to) existing guidelines and the heterogeneity in diagnostic testing hampers the comparison of data in the Swiss public health context. Therefore, diagnostic procedures should be harmonised across Switzerland and adherence to national LD management guidelines supported.

Optimising the case-crossover design for use in shared exposure settings

With a case-crossover design, a case's exposure during a risk period is compared to the case's exposures at referent periods. The selection of referents for this self-controlled design is determined by the referent selection strategy (RSS). Previous research mainly focused on systematic bias associated with the RSS. We additionally focused on how RSS determines the number of referents per risk, sensitivity to overdispersion and time-varying confounding.

We illustrated the consequences of different RSS using a simulation study informed by data on meteorological variables and Legionnaires’ disease. By randomising the events and exposure time series, we explored statistical power associated with time-stratified and fixed bidirectional RSS and their susceptibility to systematic bias and confounding bias. In addition, we investigated how a high number of events on the same date (e.g. outbreaks) affected coefficient estimation. As illustrated by our work, referent selection alone can be insufficient to control for a time-varying confounding bias. In contrast to systematic bias, confounding bias can be hard to detect. We studied potential solutions: varying the model parameters and link-function, outlier-removal and aggregating the input-data over smaller areas. Our simulation study offers a framework for researchers looking to detect and to avoid bias in case-crossover studies.

Short-term associations between Legionnaires' disease incidence and meteorological variables in Belgium, 2011-2019

The number of reported cases with Legionnaires' disease (LD) is increasing in Belgium. Previous studies have investigated the associations between LD incidence and meteorological factors, but the Belgian data remained unexplored. We investigated data collected between 2011 and 2019. Daily exposure data on temperature, relative humidity, precipitation and wind speed was obtained from the Royal Meteorological Institute for 29 weather stations. Case data were collected from the national reference centre and through mandatory notification. Daily case and exposure data were aggregated by province. We conducted a time-stratified case-crossover study. The 'at risk' period was defined as 10 to 2 days prior to disease onset. The corresponding days in the other study years were selected as referents. We fitted separate conditional Poisson models for each day in the 'at risk' period and a distributed lag non-linear model (DLNM) which fitted all data in one model. LD incidence showed a yearly peak in August and September. A total of 614 cases were included. Given seasonality, a sequence of precipitation, followed by high relative humidity and low wind speed showed a statistically significant association with the number of cases 6 to 4 days later. We discussed the advantages of DLNM in this context.

Prediction of Precipitation Based on Recurrent Neural Networks in Jingdezhen, Jiangxi Province, China

Precipitation is a critical input for hydrologic simulation and prediction, and is widely used for agriculture, water resources management, and prediction of flood and drought, among other activities. Traditional precipitation prediction researches often established one or more probability models of historical data based on the statistical prediction methods and machine learning techniques. However, few studies have been attempted deep learning methods such as the state-of-the-art for Recurrent Neural Networks (RNNs) networks in meteorological sequence time series predictions. We deployed Long Short-Term Memory (LSTM) network models for predicting the precipitation based on meteorological data from 2008 to 2018 in Jingdezhen City. After identifying the correlation between meteorological variables and the precipitation, nine significant input variables were selected to construct the LSTM model. Then, the selected meteorological variables were refined by the relative importance of input variables to reconstruct the LSTM model. Finally, the LSTM model with final selected input variables is used to predict the precipitation and the performance is compared with other classical statistical algorithms and the machine learning algorithms. The experimental results show that the LSTM is suitable for precipitation prediction. The RNN models, combined with meteorological variables, could predict the precipitation accurately in Jingdezhen City and provide sufficient time to prepare strategies against potential related disasters.

The all-intracellular order Legionellales is unexpectedly diverse, globally distributed and lowly abundant

Legionellales is an order of the Gammaproteobacteria, only composed of host-adapted, intracellular bacteria, including the accidental human pathogens Legionella pneumophila and Coxiella burnetii. Although the diversity in terms of lifestyle is large across the order, only a few genera have been sequenced, owing to the difficulty to grow intracellular bacteria in pure culture. In particular, we know little about their global distribution and abundance.

Here, we analyze 16/18S rDNA amplicons both from tens of thousands of published studies and from two separate sampling campaigns in and around ponds and in a silver mine. We demonstrate that the diversity of the order is much larger than previously thought, with over 450 uncultured genera. We show that Legionellales are found in about half of the samples from freshwater, soil and marine environments and quasi-ubiquitous in man-made environments. Their abundance is low, typically 0.1%, with few samples up to 1%. Most Legionellales OTUs are globally distributed, while many do not belong to a previously identified species.

This study sheds a new light on the ubiquity and diversity of one major group of host-adapted bacteria. It also emphasizes the need to use metagenomics to better understand the role of host-adapted bacteria in all environments.

The unprecedented 2014 Legionnaires' disease outbreak in Portugal: atmospheric driving mechanisms

A large outbreak of Legionnaires' disease occurred in November 2014 nearby Lisbon, Portugal. This epidemic infected 377 individuals by the Legionella pneumophila bacteria, resulting in 14 deaths. The primary source of transmission was contaminated aerosolized water which, when inhaled, lead to atypical pneumonia. The unseasonably warm temperatures during October 2014 may have played a role in the proliferation of Legionella species in cooling tower systems. The episode was further exacerbated by high relative humidity and a thermal inversion which limited the bacterial dispersion. Here, we analyze if the Legionella outbreak event occurred during a situation of extreme potential recirculation and/or stagnation characteristics. In order to achieve this goal, the Allwine and Whiteman approach was applied for a hindcast simulation covering the affected area during a near 20-year long period (1989-2007) and then for an independent period covering the 2014 event (15 October to 13 November 2014). The results regarding the average daily critical transport indices for the 1989-2007 period clearly indicate that the airshed is prone to stagnation as these events have a dominant presence through most of the study period (42%), relatively to the occurrence of recirculation (18%) and ventilation (17%) events. However, the year of 2014 represents an exceptional year when compared to the 1989-2007 period, with 53 and 33% of the days being classified as under stagnation and recirculation conditions, respectively.

Weather-Dependent Risk for Legionnaires' Disease, United States

Using the Nationwide Inpatient Sample and US weather data, we estimated the probability of community-acquired pneumonia (CAP) being diagnosed as Legionnaires’ disease (LD). LD risk increases when weather is warm and humid. With warm weather, we found a dose-response relationship between relative humidity and the odds for LD. When the mean temperature was 60°–80°F with high humidity (>80.0%), the odds for CAP being diagnosed with LD were 3.1 times higher than with lower levels of humidity (<50.0%). Thus, in some regions (e.g., the Southwest), LD is rarely the cause of hospitalizations. In other regions and seasons (e.g., the mid-Atlantic in summer), LD is much more common. Thus, suspicion for LD should increase when weather is warm and humid. However, when weather is cold, dry, or extremely hot, empirically treating all CAP patients for LD might contribute to excessive antimicrobial drug use at a population level.

Environmental sources of community-acquired legionnaires' disease: A review

BACKGROUND

Most Legionnaires' disease in the US and abroad is community-acquired and believed to be sporadic, or non-outbreak associated. Most patients are exposed to numerous water sources, thus making it difficult to focus environmental investigations. Identifying known sources of sporadic community-acquired Legionnaires' disease will inform future sporadic Legionnaires' disease investigations as well as highlight directions for research. The objective is to summarize and rank sporadic Legionnaires' disease sources based on the level of linkage between the environmental source and cases.

METHODS

A PubMed search was conducted using the search terms legion* and (origins or source or transmission) and (sporadic or community-acquired). Studies of nosocomial and/or outbreak-associated disease were excluded from this review. Definite, probable, possible and suspect ranks were assigned to sources based on evidence of linkage to sporadic Legionnaires' disease.

RESULTS

The search yielded 196 articles and 47 articles were included in the final review after application of exclusion criteria. A total of 28 sources were identified. Of these, eight were assigned definite rank including residential potable water and car air-conditioner water leakage. Probable rank was assigned to five sources including solar-heated potable water and soil. Possible rank was assigned to nine sources including residential potable water and cooling towers. Suspect rank was assigned to 20 sources including large building water systems and cooling towers.

CONCLUSION

Residential potable water, large building water systems and car travel appear to contribute to a substantial proportion of sporadic Legionnaires' disease. Cooling towers are also a potentially significant source; however, definitive linkage to sporadic cases proves difficult. The sources of sporadic Legionnaires' disease cannot be definitively identified for most cases.

Analysis of population-level determinants of legionellosis: spatial and geovisual methods for enhancing classification of high-risk areas

Background

Although the incidence of legionellosis throughout North America and Europe continues to increase, public health investigations have not been able to identify a common exposure in most cases. Over 80% of cases are sporadic with no known source. To better understand the role of the macro-environment in legionellosis risk, a retrospective ecological study assessed associations between population-level measures of demographic, socioeconomic, and environmental factors and high-risk areas.

Methods

Geographic variability and clustering of legionellosis was explored in our study setting using the following methods: unadjusted and standardized incidence rate and SaTScan™ cluster detection methods using default scanning window of 1 and 50% as well as a reliability score methodology. Methods for classification of “high-risk” census tracts (areas roughly equivalent to a neighborhood with average population of 4000) for each of the spatial methods are presented. Univariate and multivariate logistic regression analyses were used to estimate associations with sociodemographic factors: population ≥ 65 years of age, non-white race, Hispanic ethnicity, poverty, less than or some high school education; housing factors: housing vacant, renter-occupied, and built pre-1950 and pre-1970; and whether drinking water is groundwater or surface water source.

Results

Census tracts with high percentages of poverty, Hispanic population, and non-white population were more likely to be classified as high-risk for legionellosis versus a low-risk census tract. Vacant housing, renter-occupied housing, and homes built pre-1970 were also important positively associated risk factors. Drinking water source was not found to be associated with legionellosis incidence.

Discussion

Census tract level demographic, socioeconomic, and environmental characteristics are important risk factors of legionellosis and add to our understanding of the macro-environment for legionellosis occurrence. Our findings can be used by public health professionals to target disease prevention communication to vulnerable populations. Future studies are needed to explore the exact mechanisms by which these risk factors may influence legionellosis clustering.