Effect of disinfectant residuals on infection risks from Legionella pneumophila released by biofilms grown under simulated premise plumbing conditions

Building plumbing influences the microdiversity and community assembly of the drinking water microbiome

Building plumbing microbial communities can significantly influence water quality at the point of use, particularly during periods of stagnation. Thus, a fine-scale understanding of factors governing community membership and structure, as well as environmental and ecological factors shaping building plumbing microbial communities is critical. In this study, we utilized full-length 16S ribosomal RNA (rRNA) gene sequencing to investigate the microdiversity and spatial-temporal dynamics of microbial communities in institutional and residential building plumbing systems. Bacterial operational taxonomic units (OTUs) within institutional buildings exhibited much lower microdiversity relative to the same OTUs in residential buildings. Higher microdiversity was associated with higher persistence and relative abundance of OTUs. Interestingly, amplicon sequencing variants within the same OTUs exhibited habitat preferences based on the building type while also demonstrating varying temporal turnover patterns. Dispersal limitation disproportionately governed community assembly in institutional buildings, whereas heterogeneous selection was the dominant ecological mechanism shaping the microbial community in residential buildings. Dispersal limitation in institutional buildings is consistent with larger building sizes and greater periods of water stagnation. Interestingly, the inability to explain the extent of heterogeneous selection-driven community assembly in residential locations using measured water chemistry may suggest a disproportionately large effect of fine-scale variation in plumbing characteristics on community assembly in residential locations.

Occurrence, predictive models and potential health risk assessment of viable but non-culturable (VBNC) pathogens in drinking water

Viable but non-culturable (VBNC) pathogens are prevalent in drinking water systems and can resuscitate under favorable conditions, thereby posing significant public health risks. This study investigated the occurrence of VBNC Escherichia coli and Pseudomonas aeruginosa in source water, tap water, and potable water in eastern China, using propidium monoazide-quantitative PCR and culture-based methods. Multiple linear regression (MLR) and artificial neural network (ANN) models were developed based on conventional water quality indicators to predict VBNC pathogen concentrations. The results indicated that drinking water treatment plants effectively reduced VBNC pathogens by 1-3 log units, however, concentrations ranging from 100 to 102 CFU/100 mL remained in tap and potable water, with detection rates between 83.33% and 100%. Furthermore, potable water contained a higher concentration of VBNC pathogens than tap water, suggesting a potential risk of microbial leakage from water dispensers. The constructed ANN models outperformed than MLR models, with R values greater than 0.8, indicating a strong correlation between measured values and model predictions for VBNC pathogens. ANN models also demonstrated superior accuracy than MLR models in predicting VBNC pathogens across different type of drinking water, achieving accuracies of 88.89% for Escherichia coli and 77.78% for Pseudomonas aeruginosa. The QMRA revealed that annual infection risks and disease burdens from VBNC pathogens in potable water were greater than those in tap water, with both exceeding acceptable safety thresholds. This study emphasizes that the risks posed by VBNC pathogens deserve attention and model predictions provide critical evidence for health risk identification.

Development of a machine learning model to support low cost real-time Legionella monitoring in premise plumbing systems

Legionella pneumophila (L. pneumophila) is a pathogenic bacterium primarily known for causing Legionnaires' Disease which is known for high mortality rates, particularly in the elderly. With caseloads continuing to increase, further research is needed to improve our understanding of optimized sampling schema and safe limits of L. pneumophila, in part to target improved treatment options and realistic population-level risk modeling. Particularly in healthcare and other high-risk locations these become crucial and time sensitive needs. Therefore, we conceptualized this research as a means of incorporating easily measured physiochemical water quality parameters and generalization of the unique ecology of building water systems to build a computational model that can allow for more rapid and accurate decision making. This research uses the specific machine learning (ML) method called statistical learning theory to incorporate concentration of host cells, such as native amoeba, and physiochemical water quality parameters to estimate the probability of observing ranges of Legionella gene copy concentrations. Using data from previously published research on Legionella prevalence in a large building, our ML method trains the model on the relative impacts of physiochemical parameters on likely amoeba host cell occurrences. The model is expanded to estimate host cell concentrations using correlations and regressions operated through LASSO algorithms. After categorization variables from these results are then used to inform a logistic regression to provide an estimate of the probability of Legionella gene copy concentration ranges. In summary, conventional results generated by logistic regression and multiple linear regression quantified the associations among ecological conditions in the water and ability to predict a likely range of Legionella concentration in a management focused way. Further, two ML methods, PCA and LASSO, demonstrated feasibility in accurate real-time monitoring of Legionella through physiochemical indicators as evidenced with good accuracy of predictions based for validation results. Furthermore results demonstrate the vital need to account for the impact of water quality on building on host cells, and via their quantified water microbial ecology, not just Legionella concentrations.

Applications of Quantitative Microbial Risk Assessment to Respiratory Pathogens and Implications for Uptake in Policy: A State-of-the-Science Review

BACKGROUND

Respiratory tract infections are major contributors to the global disease burden. Quantitative microbial risk assessment (QMRA) holds potential as a rapidly deployable framework to understand respiratory pathogen transmission and inform policy on infection control.

OBJECTIVES

The goal of this paper was to evaluate, motivate, and inform further development of the use of QMRA as a rapid tool to understand the transmission of respiratory pathogens and improve the evidence base for infection control policies.

METHODS

We conducted a literature review to identify peer-reviewed studies of complete QMRA frameworks on aerosol inhalation or contact transmission of respiratory pathogens. From each of the identified studies, we extracted and summarized information on the applied exposure model approaches, dose-response models, and parameter values, including risk characterization. Finally, we reviewed linkages between model outcomes and policy.

RESULTS

We identified 93 studies conducted in 16 different countries with complete QMRA frameworks for diverse respiratory pathogens, including SARS-CoV-2, Legionella spp., Staphylococcus aureus, influenza, and Bacillus anthracis. Six distinct exposure models were identified across diverse and complex transmission pathways. In 57 studies, exposure model frameworks were informed by their ability to model the efficacy of potential interventions. Among interventions, masking, ventilation, social distancing, and other environmental source controls were commonly assessed. Pathogen concentration, aerosol concentration, and partitioning coefficient were influential exposure parameters as identified by sensitivity analysis. Most (84%, n = 78 ) studies presented policy-relevant content including a) determining disease burden to call for policy intervention, b) determining risk-based threshold values for regulations, c) informing intervention and control strategies, and d) making recommendations and suggestions for QMRA application in policy.

CONCLUSIONS

We identified needs to further the development of QMRA frameworks for respiratory pathogens that prioritize appropriate aerosol exposure modeling approaches, consider trade-offs between model validity and complexity, and incorporate research that strengthens confidence in QMRA results. https://doi.org/10.1289/EHP12695.

Quantitative Microbial Risk Assessment Framework Incorporating Water Ages with Legionella pneumophila Growth Rates

Water age in drinking water systems is often used as a proxy for water quality but is rarely used as a direct input in assessing microbial risk. This study directly linked water ages in a premise plumbing system to concentrations of Legionella pneumophila via a growth model. In turn, the L. pneumophila concentrations were used for a quantitative microbial risk assessment to calculate the associated probabilities of infection (Pinf) and clinically severe illness (Pcsi) due to showering. Risk reductions achieved by purging devices, which reduce water age, were also quantified. The median annual Pinf exceeded the commonly used 1 in 10,000 (10-4) risk benchmark in all scenarios, but the median annual Pcsi was always 1-3 orders of magnitude below 10-4. The median annual Pcsi was lower in homes with two occupants (4.7 × 10-7) than with one occupant (7.5 × 10-7) due to more frequent use of water fixtures, which reduced water ages. The median annual Pcsi for homes with one occupant was reduced by 39-43% with scheduled purging 1-2 times per day. Smart purging devices, which purge only after a certain period of nonuse, maintained these lower annual Pcsi values while reducing additional water consumption by 45-62%.

Impact of fixture purging on water age and excess water usage, considering stochastic water demands

Higher water ages are linked with water quality decline as chlorine dissipates, temperatures become more favorable for microbial growth, and metals and organic matter leach from the pipes. Water fixtures with automated purging devices can limit water age in premise plumbing systems, but also increase water use. To develop purging strategies that lower age while also minimizing water use, the stochastic nature of water demands must be considered. In this research, a hydraulic plumbing network model, with stochastic demands at fixtures, was used to compare water age and water use for five purging conditions: purging at regular intervals, "smart" purging (considering the time of last use), purging with different volumes of water, purging at different fixtures, and the purging with different levels of home occupancy. Higher purging frequency and volume resulted in lower water ages, but higher water use. Purging greatly reduced the variability in water ages, avoiding extreme ages entirely. Water age was minimized by scheduling the purging around occupancy behavior, such as before the occupants wake up or return from work. Scheduled purging used more water than smart purging. Purging after 12 h of nonuse used only 55% of the additional water required for purging every 12 h. Purging after 24 h of nonuse at the kitchen tap and shower used only 38% of the additional water required for purging every 24 h, while maintaining lower water ages and removing the variability in water ages. While larger purging volumes had a greater impact on water age, there were diminishing returns. Purging has a larger impact on low-occupancy homes because fixtures have less frequent use. Overall, this research provides a methodology to compare purging strategies that minimize both water age and water use. While the numerical results presented here are only valid for the specific layout and usage habits, they provide insights and trends applicable to other cases.

Hidden risks: Simulated leakage of domestic sewage to secondary water supply systems poses serious microbiological risks

There are continuous reports about the pollution of the secondary water supply systems (SWSSs), among which domestic sewage leakage is the most serious. In this study, a pilot experiment lasting 70 days was conducted to explore the changes in physicochemical water quality and the microbial profiles in SWSSs polluted by different doses of domestic sewage through qPCR and high-throughput sequencing methods. The results showed that when domestic sewage entered the simulated water storage tank, a large amount of organic matter brought by domestic sewage quickly consumed chlorine disinfectants. High pollution levels (pollution index ≥ 1/1000) were accompanied by significant increases in turbidity and ammonia nitrogen concentration (p < 0.05) and by abnormal changes in sensory properties. Although different microbial community structures were found only at high pollution levels, qPCR results showed that the abundance of the bacterial 16S rRNA gene and some pathogenic gene markers in the polluted tank increased with the pollution level, and the specific gene marker of pathogens could be detected even at imperceptible pollution levels. In particular, the high detection frequency and abundance of Escherichia coli and Enterococcus faecails in polluted tank water samples demonstrated that they can be used for early warning. Moreover, it seems that the microorganisms that came with the domestic sewage lost their cultivability soon after entering SWSSs but could recover their activities during stagnation. In addition, the biofilm biomass in the polluted tank with high pollution levels increased faster at the initial stage, while after a longer contact time, it tended to remain at the same level as the control tank. This study emphasized the high microbial risk introduced by sewage water leakage even at imperceptible levels and could provide scientific suggestions for early warning and prevention of pollution to SWSSs.

Flushing Temporarily Improves Microbiological Water Quality for Buildings Supplied with Chloraminated Surface Water but Has Little Effect for Groundwater Supplies

Microbial communities in premise plumbing systems were investigated after more than 2 months of long-term stagnation, during a subsequent flushing event, and during post-flush stagnation. Water samples were collected from showers in buildings supplied with chlorinated groundwater, untreated groundwater, and chloraminated surface water. The building supplied with chlorinated groundwater generally had the lowest bacterial concentrations across all sites (ranging from below quantification limit to 5.2 log copies/L). For buildings supplied with untreated groundwater, bacterial concentrations (5.0 to 7.6 log copies/L) and microbial community diversity index (ACE) values were consistent throughout sampling. Nontuberculous mycobacteria (NTM) and Legionella pneumophila were not detected in any groundwater-supplied buildings. Total bacteria, Legionella spp., and NTM were abundant in the surface water-supplied buildings following long-term stagnation (up to 7.6, 6.2, and 7.6 log copies/L, respectively). Flushing decreased these concentrations by ∼1 to >4 log units and reduced microbial community diversity, but the communities largely recovered within a week of post-flush stagnation. The results suggest that buildings supplied with disinfected surface water are more likely than buildings supplied with treated or untreated groundwater to experience deleterious changes in microbiological water quality during stagnation and that the water quality improvements from flushing with chloraminated water, while substantial, are short-lived.

Impact of prolonged hotel closures during the COVID-19 pandemic on Legionella infection risks

In general, it is accepted that water stagnation and lack or poor maintenance in buildings are risk factors for Legionella growth. Then, in theory, the prolonged hotel closures due to the COVID-19 pandemic may have increased the risk of Legionella infections. However, there are very few field studies comparing the level of Legionella colonization in buildings before the pandemic and the new situation created after the lockdown. The objective of this study was to analyze these differences in a group of hotels that experienced prolonged closures in 2020 due to the COVID-19 pandemic. We have studied the Legionella spp. results, analyzed by standard culture, from the domestic water distribution systems of 73 hotels that experienced closures (from 1 to >4 months) during 2020, immediately after the reopening. The results were compared with those obtained in similar samplings of 2019. For the comparative analysis, we divided the hotels in two groups: Group A that have suffered closures for ≤3 months and Group B that remained closed for more than 3 months, both in relation to the opening period of 2019. In the Group B (36 sites), the frequency of positive samples in the hot water system increased from 6.7% in 2019 to 14.0% in 2020 (p < 0.05). In the Group A (37 sites), no significant differences were observed. No statistically significant differences were observed in terms of positive sites (defined as hotels with at least 1 positive sample), Legionella spp. concentrations and prevalence of Legionella pneumophila sg1 between the samplings of the two periods studied. The results suggest that hotels that suffered the longest prolonged closures (> 3 months) could have carried a higher risk of exposure to Legionella in the domestic hot water system. These findings highlight the importance of adequate preopening cleaning and disinfection procedures for hotel water systems, and the convenience of considering the most effective disinfection methods especially for hot water systems and after prolonged closure periods.

Spatiotemporal distribution of opportunistic pathogens and microbial community in centralized rural drinking water: One year survey in China

Centralized water supply in rural areas, supported by small waterworks (small-central mode) and by municipal water treatment plants (urban-extension mode), is an important guarantee to implement the Rural Revitalization Strategy Plan (2018-2022) in China. Opportunistic pathogens (OPs) could not be evaluated by the national drinking water sanitation standards in China (GB 5749-2022), posing potential microbial risks in rural drinking water. In this study, the spatiotemporal distribution of OPs, microbial community and the associated functional composition under two central water supply modes were investigated by molecular approaches. The results indicated that OPs were widely presented in the rural drinking water regardless of water supply modes, and were more abundant than those in the urban tap water. The insufficient residual chlorine and higher turbidity triggered more microbial proliferation, posing a seasonal variation of OPs gene copy numbers and bacterial community compositions. In warm seasons of summer and autumn, the gene copies of E. coli, M. avium, Pseudomonas spp. and the amoeba host Acanthamoeba spp. achieved up to 4.92, 3.94, 6.75 and 3.74 log₁₀ (gene copies/mL), respectively. Potential functional prediction indicated higher relative abundance of pathogenic genes and infectious risks associated with the rural drinking water under small-central water supply mode. This one-year survey of the spatiotemporal distribution of OPs and microbial community provided scientific insights into microbial safety of rural drinking water, prompting attention on small-central water supply mode against OPs risks.

Shower water contributes viable nontuberculous mycobacteria to indoor air

Nontuberculous mycobacteria (NTM) are frequently present in municipal drinking water and building plumbing, and some are believed to cause respiratory tract infections through inhalation of NTM-containing aerosols generated during showering. However, the present understanding of NTM transfer from water to air is insufficient to develop NTM risk mitigation strategies. This study aimed to characterize the contribution of shower water to the abundance of viable NTM in indoor air. Shower water and indoor air samples were collected, and 16S rRNA and rpoB genes were sequenced. The sequencing results showed that running the shower impacted the bacterial community structure and NTM species composition in indoor air by transferring certain bacteria from water to air. A mass balance model combined with NTM quantification results revealed that on average 1/132 and 1/254 of NTM cells in water were transferred to air during 1 hour of showering using a rain and massage showerhead, respectively. A large fraction of the bacteria transferred from water to air were membrane-damaged, i.e. they had compromised membranes based on analysis by live/dead staining and flow cytometry. However, the damaged NTM in air were recoverable as shown by growth in a culture medium mimicking the respiratory secretions of people with cystic fibrosis, implying a potential infection risk by NTM introduced to indoor air during shower running. Among the recovered NTM, Mycobacterium mucogenicum was the dominant species as determined by rpoB gene sequencing. Overall, this study lays the groundwork for future pathogen risk management and public health protection in the built environment.

Chlorine decay and disinfection by-products formation during chlorination of biofilms formed with simulated drinking water containing corrosion inhibitors

Corrosion inhibitors used to reduce pipe corrosion can alter the physical structure and biochemical components of the biofilm in premise plumbing systems. We studied the effects of corrosion inhibitors on chlorine decay and associated disinfection by-products (DBPs) formation by biofilms grown with simulated drinking water amended with silicate, phosphate, and the phosphate blends. Experiments were conducted with either intact biofilms or biofilm materials dispersed in solution during sonication (referred to as biomass). While there was no significant difference in chlorine decay among biomass from different biofilms, biomass from the phosphate blend biofilm showed the lowest trihalomethane (THMs) and haloacetic acids (HAAs) formation. The chlorine decay rate constants from the biofilm experiment were ranked as: phosphate blends > phosphate ≈ groundwater (GW) > silicate. The kinetics of chlorine decay and formation of DBPs were successfully described by pseudo-first-order kinetics. These fitting parameters were used to predict the DBPs formation in a realistic premise plumbing system. The results showed that biofilm-derived THMs and HAAs increased with increasing chlorine concentration, while THMs and HAAs first increased and then stabilized to a maximum with increasing biofilm total organic carbon (TOC) concentration. In general, the biofilms grown with phosphate-based corrosion inhibitors resulted in lower DBPs formation yield but higher bacterial release, which could potentially increase the risk of user exposure to opportunistic pathogens in drinking water. The silicate biofilms showed the largest yield coefficient of DBPs formation but had the least biomass and lower bacterial release.

Causes, Factors, and Control Measures of Opportunistic Premise Plumbing Pathogens—A Critical Review

This review critically analyses the chemical and physical parameters that influence the occurrence of opportunistic pathogens in the drinking water distribution system, specifically in premise plumbing. A comprehensive literature review reveals significant impacts of water age, disinfectant residual (type and concentration), temperature, pH, and pipe materials. Evidence suggests that there is substantial interplay between these parameters; however, the dynamics of such relationships is yet to be elucidated. There is a correlation between premise plumbing system characteristics, including those featuring water and energy conservation measures, and increased water quality issues and public health concerns. Other interconnected issues exacerbated by high water age, such as disinfectant decay and reduced corrosion control efficiency, deserve closer attention. Some common features and trends in the occurrence of opportunistic pathogens have been identified through a thorough analysis of the available literature. It is proposed that the efforts to reduce or eliminate their incidence might best focus on these common features.

Opportunistic Premise Plumbing Pathogens. A Potential Health Risk in Water Mist Systems Used as a Cooling Intervention

Water mist systems (WMS) are used for evaporative cooling in public areas. The health risks associated with their colonization by opportunistic premise plumbing pathogens (OPPPs) is not well understood. To advance the understanding of the potential health risk of OPPPs in WMS, biofilm, water and bioaerosol samples (n = 90) from ten (10) WMS in Australia were collected and analyzed by culture and polymerase chain reaction (PCR) methods to detect the occurrence of five representative OPPPs: Legionella pneumophila, Pseudomonas aeruginosa, Mycobacterium avium, Naegleria fowleri and Acanthamoeba. P. aeruginosa (44%, n = 90) occurred more frequently in samples, followed by L. pneumophila serogroup (Sg) 2–14 (18%, n = 90) and L. pneumophila Sg 1 (6%, n = 90). A negative correlation between OPPP occurrence and residual free chlorine was observed except with Acanthamoeba, rs (30) = 0.067, p > 0.05. All detected OPPPs were positively correlated with total dissolved solids (TDS) except with Acanthamoeba. Biofilms contained higher concentrations of L. pneumophila Sg 2–14 (1000–3000 CFU/mL) than water samples (0–100 CFU/mL). This study suggests that WMS can be colonized by OPPPs and are a potential health risk if OPPP contaminated aerosols get released into ambient atmospheres.