Legionellosis is a respiratory infection caused by Legionella sp. that is found in water and soil. Infection may cause pneumonia (Legionnaires’ Disease) and a milder form (Pontiac Fever). Legionella colonizes water systems and results in exposure by inhalation of aerosolized bacteria. The incubation period ranges from 2 to 14 days. Precipitation and humidity may be associated with increased risk. We used Medicare records from 1999 to 2020 to identify hospitalizations for legionellosis. Precipitation, temperature, and relative humidity were obtained from the PRISM Climate Group for the zip code of residence. We used a time-stratified bi-directional case-crossover design with lags of 20 days. Data were analyzed using conditional logistic regression and distributed lag non-linear models. A total of 37 883 hospitalizations were identified. Precipitation and relative humidity at lags 8 through 13 days were associated with an increased risk of legionellosis. The strongest association was precipitation at day 10 lag (OR = 1.08, 95% CI = 1.05–1.11 per 1 cm). Over 20 days, 3 cm of precipitation increased the odds of legionellosis over four times. The association was strongest in the Northeast and Midwest and during summer and fall. Precipitation and humidity were associated with hospitalization among Medicare recipients for legionellosis at lags consistent with the incubation period for infection.

Legionellosis is a disease caused by the bacterium Legionella that most commonly presents as Legionnaires’ disease (LD), a severe form of pneumonia. From 2015 to 2019, an average of 438 LD cases per year were reported in Canada. However, it is believed that the actual number of cases is much higher, since LD may be underdiagnosed and underreported. The purpose of this study was to develop an estimate of the true incidence of illnesses, hospitalizations, and deaths associated with LD in Canada. Values were derived using a stochastic model, based on Canadian surveillance data from 2015 to 2019, which were scaled up to account for underdiagnosis and underreporting. Overall, there were an estimated 1,113 (90% CrI: 737–1,730) illnesses, 1,008 (90% CrI: 271–2,244) hospitalizations, and 34 (90% CrI: 4–86) deaths due to domestically acquired waterborne LD annually in Canada from 2015 to 2019. It was further estimated that only 36% of illnesses and 39% of hospitalizations and deaths were captured in surveillance, and that 22% of illnesses were caused by Legionella serogroups and species other than Legionella pneumophila serogroup 1 (non-Lp1). This study highlights the true burden and areas for improvement in Canada’s surveillance and detection of LD.

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.

The evidence for the incubation period of Legionnaires’ disease is based on data from a small number of outbreaks. An incubation period of 2–10 days is commonly used for the definition and investigation of cases. In the German LeTriWa study, we collaborated with public health departments to identify evidence-based sources of exposure among cases of Legionnaires’ disease within 1–14 days before symptom onset. For each individual, we assigned weights to the numbered days of exposure before symptom onset, giving the highest weight to exposure days of cases with only one possible day of exposure. We then calculated an incubation period distribution where the median was 5 days and the mode was 6 days. The cumulative distribution reached 89% by the 10th day before symptom onset. One case-patient with immunosuppression had a single day of exposure to the likely infection source only 1 day before symptom onset. Overall, our results support the 2- to 10-day incubation period used in case definition, investigation, and surveillance of cases with Legionnaires’ disease.

In the event of a Legionnaires' disease outbreak, rapid location and control of the source of bacteria are crucial for outbreak management and regulation. In this paper, we describe an enhancement of the traditional wind rose for epidemiological use; shifting the focus of measurement from relative frequency of the winds speeds and directions to the relative volume of air carried, whilst also incorporating probability distributions of disease incubation periods to refine identification of the important wind directions during a cases window of exposure, i.e. from which direction contaminated aerosols most likely originated. The probability-weighted wind rose offers a potential improvement over the traditional wind rose by weighting the importance of wind measurements through incorporation of probability of exposure given an individual's time of symptom onset (obtained through knowledge of the incubation period), and by instead focusing on the volume of carrying air which offers better insight into the most probable direction of the source. This then provides a probabilistic distribution of which direction the wind was blowing around the time of infection. We discuss how the probability-weighted wind rose can be implemented during a Legionnaires' disease outbreak, and how outbreak control teams might use it as supportive evidence to identify the most likely direction of the contaminated source from the presumed site of exposure. In addition, this paper discusses how minor adjustments can be made to the method allowing the probability-weighted wind rose to be applied to other non-communicable airborne diseases, providing the disease's probability distribution for the incubation period distribution is well known.

Hypoxemic patients often desaturate further with movement and transport. While inhaled epoprostenol does not improve mortality, improving oxygenation allows for transport of severely hypoxemic patients to tertiary care centers with a related improvement in mortality rates. Extracorporeal membrane oxygenation (ECMO) use is increasing in frequency for patients with refractory hypoxemia, and with increasing regionalization of care, safe transport of hypoxemic patients only becomes more important. In this series, four cases are presented of young patients with severe hypoxemic respiratory failure from Legionnaires’ disease transported on inhaled epoprostenol to ECMO centers for consideration of cannulation. With continued climate changes, Legionella and other pathogens are likely to be a continued threat. As such, optimizing oxygenation to allow for transport should continue to be a priority for critical care transport (CCT) services.

The incident command system (ICS) provides a common structure to control and coordinate an emergency response, regardless of scale or predicted impact. The lessons learned from the application of an ICS for large infectious disease outbreaks are documented. However, there is scant evidence on the application of an ICS to manage a local multiagency response to a disease cluster with environmental health risks. The Sydney Local Health District Public Health Unit (PHU) in New South Wales, Australia, was notified of 5 cases of Legionnaires’ disease during 2 weeks in May 2016. This unusual incident triggered a multiagency investigation involving an ICS with staff from the PHU, 3 local councils, and the state health department to help prevent any further public health risk. The early and judicious use of ICS enabled a timely and effective response by supporting clear communication lines between the incident controller and field staff. The field team was key in preventing any ongoing public health risk through inspection, sampling, testing, and management of water systems identified to be at-risk for transmission of legionella. Good working relationships between partner agencies and trust in the technical proficiency of environmental health staff aided in the effective management of the response. (Disaster Med Public Health Preparedness. 2018;12:539–542)

A legionellosis outbreak at an industrial site was investigated to identify and control the source. Cases were identified from disease notifications, workplace illness records, and from clinicians. Cases were interviewed for symptoms and risk factors and tested for legionellosis. Implicated environmental sources were sampled and tested for legionella. We identified six cases with Legionnaires’ disease and seven with Pontiac fever; all had been exposed to aerosols from the cooling towers on the site. Nine cases had evidence of infection with either Legionella pneumophila serogroup (sg) 1 or Legionella longbeachae sg1; these organisms were also isolated from the cooling towers. There was 100% DNA sequence homology between cooling tower and clinical isolates of L. pneumophila sg1 using sequence-based typing analysis; no clinical L. longbeachae isolates were available to compare with environmental isolates. Routine monitoring of the towers prior to the outbreak failed to detect any legionella. Data from this outbreak indicate that L. pneumophila sg1 transmission occurred from the cooling towers; in addition, L. longbeachae transmission was suggested but remains unproven. L. longbeachae detection in cooling towers has not been previously reported in association with legionellosis outbreaks. Waterborne transmission should not be discounted in investigations for the source of L. longbeachae infection.

This study determined the occurrence of legionellae in private houses for which there were no available data on aquatic environments other than the water supply system. From June 2013 to November 2014, we collected 138 water and 90 swab samples from aquatic environments in 19 houses. Legionella DNA was detected via a loop-mediated isothermal amplification assay in 66 (47·8%) water and 17 (18·9%) swab samples. High Legionella DNA detection rates were observed in water samples from washing machines and aquariums. Legionella spp. was isolated from 9 (6·5%) water and 3 (3·3%) swab samples. Legionella pneumophila SG 1 was detected from the outlet water of a bathtub spout and a bath sponge. Use of amoebic co-culture effectively increased legionellae and Legionella DNA detection rates from all sample types. A logistic regression analysis revealed that the heterotrophic plate count was significantly related to Legionella contamination. Our findings indicate that there is a risk of legionellosis from exposure to Legionella spp. in a variety of aquatic environments in residential houses. Control measures for legionellae in houses should include frequent cleaning and disinfecting to reduce heterotrophic bacteria in water and, where possible, preventing aerosolization from aquatic environments.

There is a paucity of information on the risk from potable water in non-passenger merchant vessels (NPMVs) particularly with regard to Legionella and other bacteria. This retrospective study examined water samples from 550 NPMVs docked in eight UK ports. A total of 1027 samples from 412 NPMVs were examined for total aerobic colony counts (ACC), coliforms, Escherichia coli and enterococci; 41% of samples yielded ACC above the action level (>1 × 103 c.f.u./ml) and 4·5% contained actionable levels (>1 c.f.u./100 ml) of faecal indicator bacteria. Eight hundred and three samples from 360 NPMVs were cultured specifically for Legionella and 58% of vessels proved positive for these organisms with 27% of samples showing levels greater than the UK upper action limit of 1 × 103 c.f.u./l. Cabin showers (49%) and hospital shower (45%) were frequently positive. A subset of 106 samples was analysed by quantitative polymerase chain reaction for Legionella and identified a further 11 Legionella-positive NPMVs, returning a negative predictive value of 100%. There was no correlation between NPMV age or size and any microbial parameters (P > 0·05). Legionella pneumophila serogroup 1 was isolated from 46% of NPMVs and sequence-based typing of 17 isolates revealed four sequence types (STs) previously associated with human disease. These data raise significant concerns regarding the management of microbial and Legionella risks on board NPMVs and suggest that better guidance and compliance are required to improve control.

Legionnaires’ disease (LD) is a globally distributed systemic infectious disease. The burden of LD in many regions is still unclear, especially in Asian countries including China. A survey of Legionella infection using real-time PCR and nested sequence-based typing (SBT) was performed in two hospitals in Shanghai, China. A total of 265 bronchoalveolar lavage fluid (BALF) specimens were collected from hospital A between January 2012 and December 2013, and 359 sputum specimens were collected from hospital B throughout 2012. A total of 71 specimens were positive for Legionella according to real-time PCR focusing on the 5S rRNA gene. Seventy of these specimens were identified as Legionella pneumophila as a result of real-time PCR amplification of the dotA gene. Results of nested SBT revealed high genetic polymorphism in these L. pneumophila and ST1 was the predominant sequence type. These data revealed that the burden of LD in China is much greater than that recognized previously, and real-time PCR may be a suitable monitoring technology for LD in large sample surveys in regions lacking the economic and technical resources to perform other methods, such as urinary antigen tests and culture methods.

In June 2014 Public Health England confirmed a case of Legionnaires' disease (LD) in a neonate following birth at home in a hired birthing pool incorporating a heater and a recirculation pump which had been filled in advance of labour. The case triggered a public health investigation and a microbiological survey of an additional ten heated birthing pools hired or recently hired to the general public across England. The birthing pool used by the parent of the confirmed case was identified as the source of the neonate's infection following detection of Legionella pneumophila ST48 in both patient and environmental samples. Legionella species were detected by quantitative polymerase chain reaction but not culture in a further three pools together with other opportunistic pathogens identified by culture and matrix-assisted laser desorption ionization–time of flight (MALDI–ToF) mass spectrometry. A Patient Safety Alert from NHS England and Public Health England was issued stating that heated birthing pools filled in advance of labour should not be used for home births. This recommendation remains in place. This investigation in conjunction with other recent reports has highlighted a lack of awareness regarding the microbiological safety of heated birthing pools and their potential to be a source of LD and other opportunistic infections. Furthermore, the investigation raised important considerations with regards to microbiological sampling and testing in such incidents. Public health authorities and clinicians should consider LD in the differential diagnosis of severe respiratory infection in neonates within 14 days of a water birth.

An unusually long-lasting community-acquired outbreak of Legionnaires’ disease (LD) occurred in the inhabitants of a town in northern Italy from 2005 to 2008. Overall, 43 cases were diagnosed including five deaths. Hundreds of water samples were collected for Legionella isolation but only two clinical samples were obtained. Clinical strains were ST23 as were environmental isolates detected in most Legionella-positive patients' homes and those from a public fountain. Although no Legionella was found in the municipal water mains, a continuous chlorination was applied in 2008. This action resulted in a halving of cases, although incidence remained tenfold higher than the Italian average incidence until the end of 2013, when it dropped to the expected rate. Retrospective analyses of prevalent wind direction suggested that a hidden cooling tower could have been the main cause of this uncommon outbreak, highlighting the importance of implementation of cooling tower registers in supporting LD investigations.

During two legionellosis outbreak investigations, one at a geriatric centre and the other in high-rise housing for seniors, it was observed that additional cases of legionellosis occurred in nearby smaller residential settings. This apparent geographical cluster of legionellosis occurred in the same general area of a community water storage tank. No potential airborne sources in or near the area could be identified, but a community water system storage tank that was centrally located among case residences spurred an investigation of water-quality factors in the identified investigation area. Conditions conducive for Legionella growth, particularly low chlorine residuals, were found. The rate of legionellosis among residents aged ⩾50 years in the investigation areas (61·0 and 64·1/100 000) was eight times higher than in the rest of the service area (9·0/100 000) and almost 20 times higher than the statewide annual average incidence rate (3·2/100 000). A water mains flushing programme in the area was launched by the water utility, and water samples taken before and during flushing found L. pneumophila.

Legionella pneumophila is the main pathogen responsible for outbreaks of Legionnaires' disease, which can be related to contaminated water supplies such as cooling towers or water pipes. We combined conventional molecular methods and whole genome sequence (WGS) analysis to investigate an outbreak of L. pneumophila in a large Australian hospital. Typing of these isolates using sequence-based typing and virulence gene profiling, was unable to discriminate between outbreak and non-outbreak isolates. WGS analysis was performed on isolates during the outbreak, as well as on unlinked isolates from the Public Health Microbiology reference collection. The more powerful resolution provided by analysis of whole genome sequences allowed outbreak isolates to be distinguished from isolates that were temporally and spatially unassociated with the outbreak, demonstrating that this technology can be used in real-time to investigate L. pneumophila outbreaks.

We investigated a mixed outbreak of Legionnaires' disease (LD) and Pontiac fever (PF) at a military base to identify the outbreak's environmental source as well as known legionellosis risk factors. Base workers with possible legionellosis were interviewed and, if consenting, underwent testing for legionellosis. A retrospective cohort study collected information on occupants of the buildings closest to the outbreak source. We identified 29 confirmed and probable LD and 38 PF cases. All cases were exposed to airborne pathogens from a cooling tower. Occupants of the building closest to the cooling tower were 6·9 [95% confidence interval (CI) 2·2–22·0] and 5·5 (95% CI 2·1–14·5) times more likely to develop LD and PF, respectively, than occupants of the next closest building. Thorough preventive measures and aggressive responses to outbreaks, including searching for PF cases in mixed legionellosis outbreaks, are essential for legionellosis control.

During August and September 2010 an unexpected high number of domestic cases of Legionnaires' disease (LD) were reported in The Netherlands. To examine this increase, patient characteristics and results of source finding and environmental sampling during the summer peak were compared to other domestic cases in 2008–2011. This analysis did not provide an explanation for the rise in cases. A similar increase in LD cases in 2006 was shown to be associated with warm and wet weather conditions, using an extended Poisson regression model with adjustment for long-term trends. This model was optimized with the new data from 2008 to 2011. The increase in 2010 was very accurately described by a model, which included temperature in the preceding 4 weeks, and precipitation in the preceding 2 weeks. These results confirm the strong association of LD incidence with weather conditions, but it remains unclear which environmental sources contributed to the 2010 summer increase.

This study evaluated the spatio-temporal variation of Legionella spp. in New Zealand using notification and laboratory surveillance data from 1979 to 2009 and analysed the epidemiological trends. To achieve this we focused on changing incidence rates and occurrence of different species over this time. We also examined whether demographic characteristics such as ethnicity may be related to incidence. The annual incidence rate for laboratory-proven cases was 2·5/100 000 and 1·4/100 000 for notified cases. Incidence was highest in the European population and showed large geographical variations between 21 District Health Boards. An important finding of this study is that the predominant Legionella species causing disease in New Zealand differs from that found in other developed countries, with about 30–50% of cases due to L. longbeachae and a similar percentage due to L. pneumophila for any given year. The environmental risk exposure was identified in 420 (52%) cases, of which 58% were attributed to contact with compost; travel was much less significant as a risk factor (6·5%). This suggests that legionellosis has a distinctive epidemiological pattern in New Zealand.

Sporadic community-acquired legionellosis (SCAL) can be acquired through contaminated aerosols from residential potable water. Electricity-dependent hot-water tanks are widely used in the province of Quebec (Canada) and have been shown to be frequently contaminated with Legionella spp. We prospectively investigated the homes of culture-proven SCAL patients from Quebec in order to establish the proportion of patients whose domestic potable hot-water system was contaminated with the same Legionella isolate that caused their pneumonia. Water samples were collected in each patient's home. Environmental and clinical isolates were compared using pulsed-field gel electrophoresis. Thirty-six patients were enrolled into the study. Legionella was recovered in 12/36 (33%) homes. The residential and clinical isolates were found to be microbiologically related in 5/36 (14%) patients. Contaminated electricity-heated domestic hot-water systems contribute to the acquisition of SCAL. The proportion is similar to previous reports, but may be underestimated.

The aim was to analyse variation in incidence of sporadic Legionnaires' disease in a geographical information system in three time periods (1990–2005) by the application of a grid model and to assess the model's validity by analysing variation according to grid position. Coordinates of the addresses at time of disease of 606 confirmed cases with Legionnaires' disease were obtained. The incidence was calculated in cells of 10×10 km in 25 different grids superimposed on a map of Denmark. A 95% and 99% threshold was applied to identify cells with excess incidence representing potential clusters. Four cells had excess incidence in all three time periods. The analysis in 25 different grid positions indicated a low risk of overlooking cells with excess incidence in a random grid. The coefficient of variation ranged from 0·08 to 0·11 independent of the threshold. By application of a random grid model we demonstrated that it was possible to detect small areas with excess incidence that were not detected in the present surveillance system.