Use of surface water in drinking water production associated with municipal Legionnaires' disease incidence

Waterborne Infectious Diseases Associated with Exposure to Tropical Cyclonic Storms, United States, 1996-2018

In the United States, tropical cyclones cause destructive flooding that can lead to adverse health outcomes. Storm-driven flooding contaminates environmental, recreational, and drinking water sources, but few studies have examined effects on specific infections over time. We used 23 years of exposure and case data to assess the effects of tropical cyclones on 6 waterborne diseases in a conditional quasi-Poisson model. We separately defined storm exposure for windspeed, rainfall, and proximity to the storm track. Exposure to storm-related rainfall was associated with a 48% (95% CI 27%-69%) increase in Shiga toxin-producing Escherichia coli infections 1 week after storms and a 42% (95% CI 22%-62%) in increase Legionnaires' disease 2 weeks after storms. Cryptosporidiosis cases increased 52% (95% CI 42%-62%) during storm weeks but declined over ensuing weeks. Cyclones are a risk to public health that will likely become more serious with climate change and aging water infrastructure systems.

Legionellosis risk-an overview of Legionella spp. habitats in Europe

An increase in the number of reports of legionellosis in the European Union and the European Economic Area have been recorded in recent years. The increase in cases is significant: from 6947 reports in 2015 to 11,298 in 2019. This is alarming as genus Legionella, which comprises a large group of bacteria inhabiting various aquatic systems, poses a serious threat to human health and life, since more than 20 species can cause legionellosis, with L. pneumophila being responsible for the majority of cases. The ability to colonize diverse ecosystems makes the eradication of these microorganisms difficult. A detailed understanding of the Legionella habitat may be helpful in the effective control of this pathogen. This paper provides an overview of Legionella environments in Europe: natural (lakes, groundwater, rivers, compost, soil) and anthropogenic (fountains, air humidifiers, water supply systems), and the role of Legionella spp. in nosocomial infections, which are potentially fatal for children, the elderly and immunocompromised patients.

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.

Wide-scale study of 206 buildings in the Netherlands from 2011 to 2015 to determine the effect of drinking water management plans on the presence of Legionella spp

Previous analysis of the Dutch National Legionella Outbreak Detection Program 2002-2012 has shown that buildings required to maintain a Legionella control plan for their drinking water installation are more likely to test positive for Legionella spp. Than buildings without such a plan (38% versus 22% of samples). To clarify this discrepancy, we analysed the results of mandatory water sample testing conducted as part of risk assessments in 206 buildings in the Netherlands from 2011 to 2015. Of the 6171 samples analysed, 16.2% exceeded the Dutch drinking water standard for Legionella spp. of 100 CFU/litre. In buildings with ≤50 tap points, the average percentage of samples containing ≥100 CFU/litre was 28.2%, and from buildings with >50 tap points, it was 12.2%. Analysis of serial samples (taken every 6 months) from each building showed that 33.2% of all buildings tested positive for at least one sample every 6 months. The overall increase was 4.4% per year. Analysis of Legionella subgroups showed that while the majority of positive samples contained L. non-pneumophila (96.9%), some samples did contain L. pneumophila serogroup 1 (1.0%) and serogroups 2-14 (2.1%). Our data suggest that the Dutch mandatory risk assessment and drinking water management plan is not sufficiently effective in preventing the proliferation of Legionella spp. and may even contribute to proliferation. This analysis should now be expanded to include other areas of the Netherlands in order to understand the geographical differences that we observed in our results, and why smaller buildings appear to be more likely to test positive for Legionella spp.

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.

Occurrence of Legionella spp. in Water-Main Biofilms from Two Drinking Water Distribution Systems

The maintenance of a chlorine or chloramine residual to suppress waterborne pathogens in drinking water distribution systems is common practice in the United States but less common in Europe. In this study, we investigated the occurrence of Bacteria and Legionella spp. in water-main biofilms and tap water from a chloraminated distribution system in the United States and a system in Norway with no residual using real-time quantitative polymerase chain reaction (qPCR). Despite generally higher temperatures and assimilable organic carbon levels in the chloraminated system, total Bacteria and Legionella spp. were significantly lower in water-main biofilms and tap water of that system ( p < 0.05). Legionella spp. were not detected in the biofilms of the chloraminated system (0 of 35 samples) but were frequently detected in biofilms from the no-residual system (10 of 23 samples; maximum concentration = 7.8 × 10⁴ gene copies cm^-2). This investigation suggests water-main biofilms may serve as a source of Legionella for tap water and premise plumbing systems, and residual chloramine may aid in reducing their abundance.

Confirmed and Potential Sources of Legionella Reviewed

Legionella bacteria are ubiquitous in natural matrices and man-made systems. However, it is not always clear if these reservoirs can act as source of infection resulting in cases of Legionnaires' disease. This review provides an overview of reservoirs of Legionella reported in the literature, other than drinking water distribution systems. Levels of evidence were developed to discriminate between potential and confirmed sources of Legionella. A total of 17 systems and matrices could be classified as confirmed sources of Legionella. Many other man-made systems or natural matrices were not classified as a confirmed source, since either no patients were linked to these reservoirs or the supporting evidence was weak. However, these systems or matrices could play an important role in the transmission of infectious Legionella bacteria; they might not yet be considered in source investigations, resulting in an underestimation of their importance. To optimize source investigations it is important to have knowledge about all the (potential) sources of Legionella. Further research is needed to unravel what the contribution is of each confirmed source, and possibly also potential sources, to the LD disease burden.

Using simple agent-based modeling to inform and enhance neighborhood walkability

Background

Pedestrian-friendly neighborhoods with proximal destinations and services encourage walking and decrease car dependence, thereby contributing to more active and healthier communities. Proximity to key destinations and services is an important aspect of the urban design decision making process, particularly in areas adopting a transit-oriented development (TOD) approach to urban planning, whereby densification occurs within walking distance of transit nodes. Modeling destination access within neighborhoods has been limited to circular catchment buffers or more sophisticated network-buffers generated using geoprocessing routines within geographical information systems (GIS). Both circular and network-buffer catchment methods are problematic. Circular catchment models do not account for street networks, thus do not allow exploratory ‘what-if’ scenario modeling; and network-buffering functionality typically exists within proprietary GIS software, which can be costly and requires a high level of expertise to operate.

Methods

This study sought to overcome these limitations by developing an open-source simple agent-based walkable catchment tool that can be used by researchers, urban designers, planners, and policy makers to test scenarios for improving neighborhood walkable catchments. A simplified version of an agent-based model was ported to a vector-based open source GIS web tool using data derived from the Australian Urban Research Infrastructure Network (AURIN). The tool was developed and tested with end-user stakeholder working group input.

Results

The resulting model has proven to be effective and flexible, allowing stakeholders to assess and optimize the walkability of neighborhood catchments around actual or potential nodes of interest (e.g., schools, public transport stops). Users can derive a range of metrics to compare different scenarios modeled. These include: catchment area versus circular buffer ratios; mean number of streets crossed; and modeling of different walking speeds and wait time at intersections.

Conclusions

The tool has the capacity to influence planning and public health advocacy and practice, and by using open-access source software, it is available for use locally and internationally. There is also scope to extend this version of the tool from a simple to a complex model, which includes agents (i.e., simulated pedestrians) ‘learning’ and incorporating other environmental attributes that enhance walkability (e.g., residential density, mixed land use, traffic volume).