BACKGROUND: Dental Unit Water Line (DUWL) deliver water to different handpieces in a dental unit. The water in DUWL circulates in a closed system, where it is taken from a container. The quality of dental water is of considerable importance since patients and dental staff are regularly exposed to water and aerosols generated from dental equipment. Output water from DUWLs may be a potential source of infection for both dental health care personnel and patients.
OBJECTIVE: To assess the microbial contamination in the DUWL among dental clinics in Chennai.
METHODS: An in vitro study was conducted on 60 water samples from 20 dental clinics in Chennai in December 2019. Water samples were collected from three different sources of the Dental unit according to ADA guidelines. The collected samples were assessed for the presence of Aspergillus, Acinetobacter, Pseudomonas aeruginosa, and Legionella by agar plate method. The data were analysed using SPSS software version 20.
RESULTS: Legionella was the most prevalent microorganism with 70% prevalence in a three-way syringe and 50% in scaler and airotor, followed by Pseudomonas aeruginosa and Acinetobacter with 10% prevalence in scaler and airotor and Aspergillus with a prevalence of 10% in the three-way syringe.
CONCLUSIONS: Most of the dental units were contaminated with Aspergillus, Legionella, Pseudomonas aeruginosa and Acinetobacter which pose a serious threat to the patients as well as the dentists.

BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires\' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be prone to errors. We aimed to train a deep learning computer vision model to automatically detect cooling towers that are aerially visible.
METHODS: Between Jan 1 and 31, 2021, we extracted satellite view images of Philadelphia (PN, USA) and New York state (NY, USA) from Google Maps and annotated cooling towers to create training datasets. We augmented training data with synthetic data and model-assisted labelling of additional cities. Using 2051 images containing 7292 cooling towers, we trained a two-stage model using YOLOv5, a model that detects objects in images, and EfficientNet-b5, a model that classifies images. We assessed the primary outcomes of sensitivity and positive predictive value (PPV) of the model against manual labelling on test datasets of 548 images, including from two cities not seen in training (Boston [MA, USA] and Athens [GA, USA]). We compared the search speed of the model with that of manual searching by four epidemiologists.
RESULTS: The model identified visible cooling towers with 95·1% sensitivity (95% CI 94·0-96·1) and a PPV of 90·1% (95% CI 90·0-90·2) in New York City and Philadelphia. In Boston, sensitivity was 91·6% (89·2-93·7) and PPV was 80·8% (80·5-81·2). In Athens, sensitivity was 86·9% (75·8-94·2) and PPV was 85·5% (84·2-86·7). For an area of New York City encompassing 45 blocks (0·26 square miles), the model searched more than 600 times faster (7·6 s; 351 potential cooling towers identified) than did human investigators (mean 83·75 min [SD 29·5]; mean 310·8 cooling towers [42·2]).
CONCLUSIONS: The model could be used to accelerate investigation and source control during outbreaks of Legionnaires\' disease through the identification of cooling towers from aerial imagery, potentially preventing additional disease spread. The model has already been used by public health teams for outbreak investigations and to initialise cooling tower registries, which are considered best practice for preventing and responding to outbreaks of Legionnaires\' disease.
BACKGROUND: None.

Background and Objectives: Legionnaires\' disease (LD) is an acute respiratory disease with increasing annual numbers of reported domestic and global cases. This study aimed to establish foundational data for the prevention and control of LD by investigating the occurrence and infection routes of reported and suspected cases of LD in Gyeonggi Province, Korea, from January 2016 to December 2022, and by and analyzing the risk factors for death. Materials and Methods: A sex-and-age standardization was performed on LD patients and suspected cases reported in Gyeonggi Province. The monthly average number of confirmed cases was visualized using graphs, and a survival analysis was performed using Kaplan-Meier survival curves. The mortality risk ratio was estimated using the Cox proportional hazards model. Results: The incidence of LD in Gyeonggi Province mirrored the national trend, peaking in July with the highest number of confirmed and suspected cases. While there was no significant difference in survival rates by age, the survival rate was higher for suspected cases when analyzed separately. Comparing the death ratio by infection route, nosocomial infections showed the highest death ratio, and intensive care unit (ICU) admission and the presence of coinfections were significantly correlated with mortality. Factors such as nosocomial infection, admission within 1 to 3 days following diagnosis, and the development of complications were factors contributing to a higher risk of death. Conclusions: The general characteristics of patients with LD were similar to those suggested by previous studies. The proportion of community-acquired infections was lower than in previous studies, but the length of hospital stay was similar for survivors and the deceased, and the mortality rate within 30 days after diagnosis was higher for nosocomial infections. In conclusion, nosocomial infection, a period of up to 3 days from admission to diagnosis, and complications were significantly related to the mortality rate of LD.

BACKGROUND: Legionnaires disease (LD) is a rare, life-threatening opportunistic bacterial infection that poses a significant risk to patients with impaired cell-mediated immunity such as solid organ transplant recipients. However, the epidemiologic features, clinical presentation, and outcomes of LD in this population are poorly described.
OBJECTIVE: What are the clinical manifestations, radiologic presentation, risk factors for severity, treatment, and outcome of LD in solid organ transplant recipients?
METHODS: In this 10-year multicenter retrospective cohort study in France, where LD notification is mandatory, patients were identified by hospital discharge databases. Diagnosis of LD relied on positive culture findings from any respiratory sample, positive urinary antigen test (UAT) results, positive specific serologic findings, or a combination thereof. Severe LD was defined as admission to the ICU.
RESULTS: One hundred one patients from 51 transplantation centers were eligible; 64 patients (63.4%) were kidney transplant recipients. Median time between transplantation and LD was 5.6 years (interquartile range, 1.5-12 years). UAT results were positive in 92% of patients (89/97). Among 31 patients with positive culture findings in respiratory samples, Legionella pneumophila serogroup 1 was identified in 90%. Chest CT imaging showed alveolar consolidation in 98% of patients (54 of 57), ground-glass opacity in 63% of patients (36 of 57), macronodules in 21% of patients (12 of 57), and cavitation in 8.8% of patients (5 of 57). Fifty-seven patients (56%) were hospitalized in the ICU. In multivariate analysis, severe LD was associated with negative UAT findings at presentation (P = .047), lymphopenia (P = .014), respiratory symptoms (P = .010), and pleural effusion (P = .039). The 30-day and 12-month mortality rates were 8% (8 of 101) and 20% (19 of 97), respectively. In multivariate analysis, diabetes mellitus was the only factor associated with 12-month mortality (hazard ratio, 3.2; 95% OR, 1.19-8.64; P = .022).
CONCLUSIONS: LD is a late and severe complication occurring in solid organ transplant recipients that may present as pulmonary nodules on which diabetes impacts its long-term prognosis.

BACKGROUND: Severe community-acquired pneumonia (SCAP) is commonly treated with an empiric combination therapy, including a macrolide, or a quinolone and a β-lactam. However, the risk of Legionella pneumonia may lead to a prolonged combination therapy even after negative urinary antigen tests (UAT).
METHODS: We conducted a retrospective cohort study in a French intensive care unit (ICU) over 6 years and included all the patients admitted with documented SCAP. All patients received an empirical combination therapy with a β-lactam plus a macrolide or quinolone, and a Legionella UAT was performed. Macrolide or quinolone were discontinued when the UAT was confirmed negative. We examined the clinical and epidemiological features of SCAP and analysed the independent factors associated with ICU mortality.
RESULTS: Among the 856 patients with documented SCAP, 26 patients had atypical pneumonia: 18 Legionella pneumophila (LP) serogroup 1, 3 Mycoplasma pneumonia (MP), and 5 Chlamydia psittaci (CP). UAT diagnosed 16 (89%) Legionella pneumonia and PCR confirmed the diagnosis for the other atypical pneumonia. No atypical pneumonia was found by culture only. Type of pathogen was not associated with a higher ICU mortality in the multivariate analysis.
CONCLUSIONS: Legionella pneumophila UAT proved to be highly effective in detecting the majority of cases, with only a negligible percentage of patients being missed, but is not sufficient to diagnose atypical pneumonia, and culture did not provide any supplementary information. These results suggest that the discontinuation of macrolides or quinolones may be a safe option when Legionella UAT is negative in countries with a low incidence of Legionella pneumonia.

The guidelines for the requirement of Legionella urinary antigen tests on admission for patients hospitalized with community-acquired pneumonia differ in Japan, the United States, and Europe. We aimed to evaluate the association between the timing of Legionella urinary antigen testing and inhospital mortality in patients with atypical pneumonia.
We identified 654,708 patients with atypical pneumonia from July 2010 to March 2021 using the Japanese national inpatient database. The patients were divided into groups that underwent Legionella urinary antigen tests on the day of admission (test group, n = 229,649) and those that underwent testing after the day of admission or were untested (control group, n = 425,059). A propensity score-stabilized inverse probability of treatment weighting analysis was performed to compare inhospital mortality, length of hospital stay, and total hospitalization costs between the two groups. Odds ratios (ORs) or differences and their 95% confidence intervals (CIs) were calculated using generalized linear models.
The tested group had a significantly lower 30-day inhospital mortality than that of the control group (7.7% vs. 9.0%; OR: 0.83 [95% CIs, 0.81-0.86]). The tested group also had a significantly shorter length of stay (difference, -2.3 [-2.6 to - 2.0] days and total hospitalization costs (-396 [-508 to - 285] US dollars) than that of the control group.
Legionella urinary antigen testing upon admission is associated with better outcomes in patients with atypical pneumonia. Legionella urinary antigen testing performed on the day of admission is recommended for hospitalized patients with atypical pneumonia.

BACKGROUND: Many factors determine empirical antibiotic treatment of community-acquired pneumonia (CAP). We aimed to describe the empirical antibiotic treatment CAP patients with an acute hospital visit and to determine if the current treatment algorithm provided specific and sufficient coverage against Legionella pneumophila, Mycoplasma pneumoniae, and Clamydophila pneumoniae (LMC).
METHODS: A descriptive cross-sectional, multicenter study of all adults with an acute hospital visit in the Region of Southern Denmark between January 2016 and March 2018 was performed. Using medical records, we retrospectively identified the empirical antibiotic treatment and the microbiological etiology for CAP patients. CAP patients who were prescribed antibiotics within 24 h of admission and with an identified bacterial pathogen were included. The prescribed empirical antibiotic treatment and its ability to provide specific and sufficient coverage against LMC pneumonia were determined.
RESULTS: Of the 19,133 patients diagnosed with CAP, 1590 (8.3%) patients were included in this study. Piperacillin-tazobactam and Beta-lactamase sensitive penicillins were the most commonly prescribed empirical treatments, 515 (32%) and 388 (24%), respectively. Our analysis showed that 42 (37%, 95% CI: 28-47%) of 113 patients with LMC pneumonia were prescribed antibiotics with LMC coverage, and 42 (12%, 95% CI: 8-15%) of 364 patients prescribed antibiotics with LMC coverage had LMC pneumonia.
CONCLUSIONS: Piperacillin-tazobactam, a broad-spectrum antibiotic recommended for uncertain infectious focus, was the most frequent CAP treatment and prescribed to every third patient. In addition, the current empirical antibiotic treatment accuracy was low for LMC pneumonia. Therefore, future research should focus on faster diagnostic tools for identifying the infection focus and precise microbiological testing.

UNASSIGNED: The \"LeTriWa study\" on community-acquired cases of Legionnaires\' disease (LD) found that most cases likely acquired their infection at home (AHALD). However, which sources confer the infection is largely unknown. We therefore analyzed the data set from the LeTriWa study to find out if individual sources were associated with AHALD and if specific behavioral habits may increase or lower the risk for AHALD.
UNASSIGNED: During the study we had used two comparison groups: (i) controls matched for age group and hospital (\"controls\"), (ii) household members of cases with AHALD (\"AHALD-HHM\"). We inquired about exposure to water sources, such as showering or wearing dentures, as well as behavioral factors and habits related to oral hygiene. We took standardized household bathroom water and biofilm samples of both cases with AHALD and controls, and in addition from households of cases with AHALD only samples from suspect residential (non-)drinking water sources. We first conducted bivariate analyses for infection sources and behaviors, followed by multivariable analyses.
UNASSIGNED: There were 124 cases with AHALD, 217 controls and 59 AHALD-HHM. In bivariate analyses using controls for comparison, wearing dentures was the only variable significantly positively associated (odds ratio (OR) = 1.7, 95% confidence interval (CI) = 1.1-2.7, p-value = 0.02). Behavioral factors such as showering, letting water run before use and not being alcohol abstinent were significantly negatively associated, smoking was significantly positively associated. In a multivariable analysis, we identified good oral hygiene as a preventive factor for both denture wearers (OR = 0.33, 95% CI = 0.13-0.83, p-value = 0.02) and non-denture wearers (OR = 0.32, 95% CI = 0.10-1.04, p-value = 0.06). Analyses of comparisons with AHALD-HHM showed similar effects but lacked statistical power. We identified Legionella in 16 residential (non-)drinking water sources, one of which was a PCR-positive scratch sample of dentures.
UNASSIGNED: Wearing (inadequately cleaned) dentures or poor oral hygiene might confer an increased risk for AHALD, and oral hygiene may prevent AHALD. The hypothesis that Legionella in oral biofilm or dental plaque may be the cause of cases with AHALD should be examined further. If confirmed this may open new and simple avenues for the prevention of LD.

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.
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.
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.
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.
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.

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.