The relationship between meteorological variables and sporadic cases of Legionnaires' disease in residents of England and Wales

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.

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.

The effect of seasonal and extreme floods on hospitalizations for Legionnaires' disease in the United States, 2000-2011

BACKGROUND

An increasing severity of extreme storms and more intense seasonal flooding are projected consequences of climate change in the United States. In addition to the immediate destruction caused by storm surges and catastrophic flooding, these events may also increase the risk of infectious disease transmission. We aimed to determine the association between extreme and seasonal floods and hospitalizations for Legionnaires' disease in 25 US states during 2000-2011.

METHODS

We used a nonparametric bootstrap approach to examine the association between Legionnaires' disease hospitalizations and extreme floods, defined by multiple hydrometeorological variables. We also assessed the effect of extreme flooding associated with named cyclonic storms on hospitalizations in a generalized linear mixed model (GLMM) framework. To quantify the effect of seasonal floods, we used multi-model inference to identify the most highly weighted flood-indicator variables and evaluated their effects on hospitalizations in a GLMM.

RESULTS

We found a 32% increase in monthly hospitalizations at sites that experienced cyclonic storms, compared to sites in months without storms. Hospitalizations in months with extreme precipitation were in the 89^th percentile of the bootstrapped distribution of monthly hospitalizations. Soil moisture and precipitation were the most highly weighted variables identified by multi-model inference and were included in the final model. A 1-standard deviation (SD) increase in average monthly soil moisture was associated with a 49% increase in hospitalizations; in the same model, a 1-SD increase in precipitation was associated with a 26% increase in hospitalizations.

CONCLUSIONS

This analysis is the first to examine the effects of flooding on hospitalizations for Legionnaires' disease in the United States using a range of flood-indicator variables and flood definitions. We found evidence that extreme and seasonal flooding is associated with increased hospitalizations; further research is required to mechanistically establish whether floodwaters contaminated with Legionella bacteria drive transmission.

The association between sporadic Legionnaires' disease and weather and environmental factors, Minnesota, 2011-2018

From 2011 through 2018, there was a notable increase in sporadic Legionnaires' disease in the state of Minnesota. Sporadic cases are those not associated with a documented outbreak. Outbreak-related cases are typically associated with a common identified contaminated water system; sporadic cases typically do not have a common source that has been identified. Because of this, it is hypothesised that weather and environmental factors can be used as predictors of sporadic Legionnaires' disease. An ecological design was used with case report surveillance data from the state of Minnesota during 2011 through 2018. Over this 8-year period, there were 374 confirmed Legionnaires' disease cases included in the analysis. Precipitation, temperature and relative humidity (RH) data were collected from weather stations across the state. A Poisson regression analysis examined the risk of Legionnaires' disease associated with precipitation, temperature, RH, land-use and age. A lagged average 14-day precipitation had the strongest association with Legionnaires' disease (RR 2.5, CI 2.1-2.9), when accounting for temperature, RH, land-use and age. Temperature, RH and land-use also had statistically significant associations to Legionnaires' disease, but with smaller risk ratios. This study adds to the body of evidence that weather and environmental factors play an important role in the risk of sporadic Legionnaires' disease. This is an area that can be used to target additional research and prevention strategies.

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.

Legionella and legionellosis in touristic-recreational facilities: Influence of climate factors and geostatistical analysis in Southern Italy (2001-2017)

Legionella is the causative agent of Legionnaires' disease, a flu-like illness normally acquired following inhalation or aspiration of contaminated water aerosols. Our recent studies revealed that climatic parameters can increase the number of reported cases of community-acquired Legionnaires' disease. Here, we evaluated the presence of Legionella in water networks and the distribution of Legionnaires' disease cases associated with touristic-recreational facilities in the Apulia region (southern Italy) during the period 2001-2017 using geostatistical and climatic analyses. Geostatistical analysis data revealed that the area with the highest concentration of Legionella in water systems also had the greatest number of cases of Legionnaires' disease associated with touristic-recreational facilities. Climatic analysis showed that higher daily temperature excursion (difference between maximum and minimum temperature) on the day of sampling was more often associated with Legionella-positive samples than Legionella-negative samples. In addition, our data highlighted an increased risk of Legionnaires' disease with increases in precipitation and average temperature and with decreases in daily temperature excursion (difference between maximum and minimum temperature over the course of 24 h in the days of incubation period of disease) and minimum temperature. Healthcare professionals should be aware of this phenomenon and be particularly vigilant for cases of community-acquired pneumonia during such climatic conditions and among the tourist population. The innovative geo-statistical approach used in this study could be applied in other contexts when evaluating the effects of climatic conditions on the incidence of Legionella infections.

Association Between Sporadic Legionellosis and River Systems in Connecticut

Background

There has been a dramatic increase in the incidence of sporadic legionnaires' disease in Connecticut since 1999, but the exact reasons for this are unknown. Therefore, there is a growing need to understand the drivers of legionnaires' disease in the community. In this study, we explored the relationship between the natural environment and the spatial and temporal distribution of legionellosis cases in Connecticut.

Methods

We used spatial models and time series methods to evaluate factors associated with the increase and clustering of legionellosis in Connecticut. Stream flow, proximity to rivers, and residence in regional watersheds were explored as novel predictors of disease, while controlling for testing intensity and correlates of urbanization.

Results

In Connecticut, legionellosis incidence exhibited a strong pattern of spatial clustering. Proximity to several rivers and residence in the corresponding watersheds were associated with increased incidence of the disease. Elevated rainfall and stream flow rate were associated with increases in incidence 2 weeks later.

Conclusions

We identified a novel relationship between the natural aquatic environment and the spatial distribution of sporadic cases of legionellosis. These results suggest that natural environmental reservoirs may have a greater influence on the spatial distribution of sporadic legionellosis cases than previously thought.

Short-term effects of atmospheric pressure, temperature, and rainfall on notification rate of community-acquired Legionnaires' disease in four European countries

Legionnaires' disease (LD) is caused by the inhalation of aerosols containing Legionella, a Gram-negative bacteria. Previous national- or regional-level studies have suggested an impact of climate on LD incidence. The objective of this study was to investigate the effect of temperature, rainfall, and atmospheric pressure on short-term variations in LD notification rate. EU/EEA Member States report their LD surveillance data to the European Centre for Disease Prevention and Control. Community-acquired LD cases reported by Denmark, Germany, Italy, and The Netherlands with onset date in 2007-2012 were aggregated by onset week and region of residence. Weather variables were extracted from the European Climate Assessment & Dataset project. We fitted Poisson regression models to estimate the association between meteorological variables and the weekly number of community-acquired LD cases. Temperature, rainfall and atmospheric pressure were all associated with LD risk with higher risk associated with simultaneous increase in temperature and rainfall. Temperatures >20 °C were not associated with a higher risk for LD. LD cases occurring during wintertime may be associated with sources less influenced by meteorological conditions.

Compost and Legionella longbeachae: an emerging infection?

Human disease caused by Legionella species is dominated by Legionella pneumophila, the main causative agent in cases of Legionnaires’ disease. However, other species are known to cause infection, for example, Legionella longbeachae causes an equivalent number of cases of disease as L. pneumophila in Australia and New Zealand. Infection with L. longbeachae is commonly associated with exposure to composts and potting soils, and cases of infection with this organism have been increasing in Europe over the past ten years. The increase in incidence may be linked to factors such as increased awareness of clinical presentation, or due to changing formulation of growing media, although it should be noted that the presence of Legionella species in growing media does not correlate with the number of cases currently seen. This is likely due to the variables associated with infection, for example, host factors such as smoking or underlying health conditions, or difference in growing media storage or climate, especially warm humid conditions, which may affect survival and growth of these organisms in the growing media environment. There are numerous unknowns in this area and collaboration between growing media manufacturers and researchers, as well as more awareness among diagnosing clinicians, laboratory staff and the general public is necessary to reduce risk. More research is needed before definitive conclusions can be drawn: L. pneumophila research currently dominates the field and it is likely that the overreliance on diagnostic techniques such as the urinary antigen test, which is specific for L. pneumophila Sg 1, is detrimental to the diagnosis of L. longbeachae infection.