Fecal Indicator Research Articles

What is the Difference between Conventional Drinking Water, Potable Reuse Water, and Nonpotable Reuse Water? A Microbiome Perspective.

As water reuse applications expand, there is a need for more comprehensive means to assess water quality. Microbiome analysis could provide the ability to supplement fecal indicators and pathogen profiling toward defining a "healthy" drinking water microbiota while also providing insight into the impact of treatment and distribution. Here, we utilized 16S rRNA gene amplicon sequencing to identify signature features in the composition of microbiota across a wide spectrum of water types (potable conventional, potable reuse, and nonpotable reuse). A clear distinction was found in the composition of microbiota as a function of intended water use (e.g., potable vs nonpotable) across a very broad range of U.S. water systems at both the point of compliance (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.71) and point of use (Betadisper p > 0.01; ANOSIM p < 0.01, r-stat = 0.41). Core and discriminatory analysis further served in identifying distinct differences between potable and nonpotable water microbiomes. Taxa were identified at both the phylum (Desulfobacterota, Patescibacteria, and Myxococcota) and genus (Aeromonas and NS11.12_marine_group) levels that effectively discriminated between potable and nonpotable waters, with the most discriminatory taxa being core/abundant in nonpotable waters (with few exceptions, such as Ralstonia being abundant in potable conventional waters). The approach and findings open the door to the possibility of microbial community signature profiling as a water quality monitoring approach for assessing efficacy of treatments and suitability of water for intended use/reuse application.

A data-driven approach to optimize a sanitary survey for communities in Maputo, Mozambique

ABSTRACT Current approaches to align sanitary surveys to environmental fecal waste indicators have demonstrated limited success, leaving stakeholders focused on fecal waste management with limited and costly tools. We analyzed data from the Maputo Sanitation Project using exploratory factor analysis (EFA) and structural equation modeling (SEM) to enhance the survey's correlation with Escherichia coli concentration data. EFA grouped related survey questions and sampling locations into distinct latent factors. SEM was then used to assess the relationship between the survey latent factors and the mean E. coli concentrations from grouped locations. The results suggested four survey question subgroups: latrine structure, latrine cleanliness, compound/household waste management, and community waste management. In addition, three sampling location subgroups were identified: high-traffic areas (HTAs), food activity locations, and bodily cleaning areas. The largest significant effect size identified suggested that for every 1-unit increase in community waste management, there was a decrease of 1.94 in log10 E. coli per gram of soil in HTAs (p = 0.03), a substantial improvement from the initial 0.50 decrease reported for an expert-weighted metric of all survey questions. These results underscore the importance of community-level waste management and demonstrate the use of a data-driven approach in enhancing environmental health assessments and planning interventions.

Mastering granular activated carbon filtration to remove organic micropollutants, antibiotic resistance and metals for municipal wastewater reuse

GAC filtration of municipal wastewater was optimized and intensified, making its implementation and operation directly after secondary clarification possible and relevant. GAC was first selected based on laboratory tests. Performances on organic micropollutants were linked to the repartition of BET surface between micropores and meso/macropores. At pilot scale, in order to limit the impact of head loss, downflow declogging sequences (DCS) were implemented and upflow filtration tested. 6 to 12 DCS per day led to a 4.7–5.5-fold increase of particles retention capacity between backwashes (cycle duration of 20–120 h), and upflow operations improved head loss evolution profile with only a slight GAC (<15 %) expansion. DCS allows backwash frequency reduction, enabling significant water savings. Both adaptations maintained high organic micropollutants removals compared to a review of 16 GAC studies at pilot or full-scale, results being in the upper range. A specific dose of 2.0–2.5 g GAC/gC was necessary to obtain an average removal of pharmaceuticals and benzotriazole of 80 % at 20 min contact time, which is comparable to PAC and low granulometry GAC. Higher doses are needed for PFAS but >80 % removals are achievable. Particles, TKN, particulate phosphorus and organic matter are well removed by GAC filtration in both configurations. Biological activity is observed through nitrogen transformation in the GAC bed. Heavy metals are greatly removed in GAC filtration, in particular Cd, Cu, Ni and Pb, probably through biosorption onto the biofilm, developed within the GAC bed. For wastewater reuse applications, GAC filtration has an added value through physicochemical quality improvement and fecal contamination indicators removal of 1 log, facilitating the implementation and optimizing the design of a post-disinfection. Antibiotic resistant bacteria and antibiotic resistance genes are also partially retained in GAC filtration. Finally, biological wastewater treatments combined to GAC filtration is a good solution to effectively treat organic micropollutants together with heavy metals and preparing post-disinfection for reuse.

Quantitative fecal pollution assessment with bacterial, viral, and molecular methods in small stream tributaries

Stream water quality can be impacted by a myriad of fecal pollution sources and waste management practices. Identifying origins of fecal contamination can be challenging, especially in high order streams where water samples are influenced by pollution from large drainage areas. Strategic monitoring of tributaries can be an effective strategy to identify conditions that influence local water quality. Water quality is assessed using fecal indicator bacteria (FIB); however, FIB cannot differentiate sources of fecal contamination nor indicate the presence of disease-causing viruses. Under different land use scenarios, three small stream catchments were investigated under ‘wet’ and ‘dry’ conditions (Scenario 1: heavy residential; Scenario 2: rural residential; and Scenario 3: undeveloped/agricultural). To identify fecal pollution trends, host-associated genetic targets HF183/BacR287 (human), Rum2Bac (ruminant), GFD (avian), and DG3 (canine) were analyzed along with FIB (Escherichia coli and enterococci), viral indicators (somatic and F+ coliphage), six general water quality parameters, and local rainfall. Levels of E. coli exceeded single sample maximum limits (235 CFU/100 mL) in 70.7 % of samples, enterococci (70 CFU/100 mL) in 100 % of samples, and somatic coliphage exceeded advisory thresholds (600 PFU/L) in 34.1 % of samples. The detection frequency for the human-associated genetic marker was highest in Scenario 3 (50 % of samples) followed by Scenario 2 (46 %), while the ruminant-associated marker was most prevalent in Scenario 1 (64 %). Due to the high proportion of qPCR-based measurements below the limit of quantification, a Bayesian data analysis approach was applied to investigate links between host-associated genetic marker occurrence with that of rainfall and fecal indicator levels. Multiple trends associated with small stream monitoring were revealed, emphasizing the role of rainfall, the utility of fecal source information to improve water quality management. And furthermore, water quality monitoring with bacterial or viral methodologies can alter the interpretation of fecal pollution sources in impaired waters.

Alternative for HPC22 after repairs in the drinking water distribution system

There is a risk of contamination by (pathogenic) microorganisms from the outside environment into the drinking water during maintenance or pipe breaches in the drinking water distribution system (DWDS) and, consequently, the drinking water distributed to consumers may result in possible detrimental effects on public health. Traditional time-consuming microbiological testing is, therefore, performed to confirm drinking water is not microbially contaminated. This is done by culturing methods of the faecal indicators Escherichia coli, intestinal enterococci and the technical parameters coliform bacteria and heterotrophic plate counts at 22 °C (HPC22). In this study, fast methods (adenosine triphosphate (ATP), flow cytometry, enzyme activity and qPCR) were compared as an alternative for HPC22. Using dilution series and field samples, ATP (ATPtotal-lab and ATPcell-mob) and enzymatic activity (ALP-2) methods proved to be the more reliable and sensitive than flow cytometry and qPCR methods for detecting microbiological contaminations in drinking water. Significant (p < 0.05) and relatively strong correlations (R2 = 0.61–0.76) were obtained between HPC22 and both ATP methods, enzyme activity and qPCR parameters, but relations with flow cytometry were weak (R2 = 0.24 – 0.52). The samples taken after repairs or a calamity from the DWDS showed in general limited variation in the HPC22 count and were in most cases below the guidance level of 1,000 CFU/mL. We recommend that the best performing alternative methods, i.e. ATPtotal-lab and ATPcell-mob and ALP-2, should be included next to HPC22 in additional field studies to further test and compare these methods to be able to decide which fast method can replace HPC22 analysis after maintenance work in the DWDS.

Development and evaluation of a general approach for predicting pathogen decay in surface waters using hierarchical Bayesian modeling

A general approach for predicting indicator and pathogen decay in surface waters was developed using Bayesian hierarchical modeling, a persistence database, and a two-parameter model form. The resulting hierarchical regression describes general persistence behaviors with target-level intercepts and population-level coefficients. Uncertainty factors calculated with the approach suggest fecal indicator bacteria (FIB) and pathogenic bacteria persist similarly in surface waters, but median virus and protozoa persistence metrics may be 2–3 times greater than FIB in similar conditions. The two-parameter model underpinning the approach was used to identify drivers of these differences. Virus decay rates were shown to taper off more quickly than FIB, whereas protozoa were associated with longer initial periods of minimal decay. Despite the low accuracy of the hierarchical model compared to models fit to individual datasets, this approach addresses a critical gap for water management decision-making as site-specific and pathogen-specific persistence data are uncommon in water monitoring practices.

Application of a microbial and pathogen source tracking toolbox to identify infrastructure problems in stormwater drainage networks: a case study.

Water scarcity and increasing urbanization are forcing municipalities to consider alternative water sources, such as stormwater, to fill in water supply gaps or address hydromodification of receiving urban streams. Mounting evidence suggests that stormwater is often contaminated with human feces, even in stormwater drainage systems separate from sanitary sewers. Pinpointing sources of human contamination in drainage networks is challenging given the diverse sources of fecal pollution that can impact these systems and the non-specificity of traditional fecal indicator bacteria (FIB) for identifying these host sources. As such, we used a toolbox approach that encompassed microbial source tracking (MST), FIB monitoring, and bacterial pathogen monitoring to investigate microbial contamination of stormwater in an urban municipality. We demonstrate that human sewage frequently contaminated stormwater (in >50% of routine samples), based on the presence of the human fecal marker HF183, and often exceeded microbial water quality criteria. Arcobacter butzleri, a pathogen of emerging concern, was also detected in >50% of routine samples, with 75% of these pathogen-positive samples also being positive for the human fecal marker HF183, suggesting human municipal sewage as the likely source for this pathogen. MST and FIB were used to track human fecal pollution in the drainage network to the most likely point source of contamination, for which a sewage cross-connection was identified and confirmed using tracer dyes. These results point to the ubiquitous presence of human sewage in stormwater and also provide municipalities with the tools to identify sources of anthropogenic contamination in storm drainage networks.IMPORTANCEWater scarcity, increased urbanization, and population growth are driving municipalities worldwide to consider stormwater as an alternative water source in urban environments. However, many studies suggest that stormwater is relatively poor in terms of microbial water quality, is frequently contaminated with human sewage, and therefore could represent a potential health risk depending on the type of exposure (e.g., irrigation of community gardens). Traditional monitoring of water quality based on fecal bacteria does not provide any information about the sources of fecal pollution contaminating stormwater (i.e., animals/human feces). Herein, we present a case study that uses fecal bacterial monitoring, microbial source tracking, and bacterial pathogen analysis to identify a cross-connection that contributed to human fecal intrusion into an urban stormwater network. This microbial toolbox approach can be useful for municipalities in identifying infrastructure problems in stormwater drainage networks to reduce risks associated with water reuse.

Implications of long-term sample storage on the recovery of viruses from wastewater and biobanking

Wastewater-based monitoring has been widely implemented worldwide for the tracking of SARS-CoV-2 outbreaks and other viral diseases. In many surveillance programmes, unprocessed and processed wastewater samples are often frozen and stored for long periods of time in case the identification and tracing of an emerging health threat becomes necessary. However, extensive sample bioarchives may be difficult to maintain due to limitations in ultra-freezer capacity and associated cost. Furthermore, the stability of viruses in such samples has not been systematically investigated and hence the usefulness of bioarchives is unknown. In this study, we assessed the stability of SARS-CoV-2, influenza viruses, noroviruses and the faecal indicator virus, crAssphage, in raw wastewater and purified nucleic aacid extracts stored at -80 °C for 6–24 months. We found that the isolated viral RNA and DNA showed little signs of degradation in storage over 8–24 months, whereas extensive decay viral and loss of qPCR signal was observed during the storage of raw unprocessed wastewater. The most stable viruses were noroviruses and crAssphage, followed by SARS-CoV-2 and influenza A virus. Based on our findings, we conclude that bioarchives comprised of nucleic acid extracts derived from concentrated wastewater samples may be archived long-term, for at least two years, whereas raw wastewater samples may be discarded after one year.

Longitudinal study on the multifactorial public health risks associated with sewage reclamation

This year-long research analyzed emerging risks in influent, effluent wastewaters and biosolids from six wastewater treatment plants in Spain’s Valencian Region. Specifically, it focused on human enteric and respiratory viruses, bacterial and viral faecal contamination indicators, extended-spectrum beta-lactamases-producing Escherichia coli, and antibiotic-resistance genes. Additionally, particles and microplastics in biosolid and wastewater samples were assessed. Human enteric viruses were prevalent in influent wastewater, with limited post-treatment reduction. Wastewater treatment effectively eliminated respiratory viruses, except for low levels of SARS-CoV-2 in effluent and biosolid samples, suggesting minimal public health risk. Antibiotic resistance genes and microplastics were persistently found in effluent and biosolids, thus indicating treatment inefficiencies and potential environmental dissemination. This multifaced research sheds light on diverse contaminants present after water reclamation, emphasizing the interconnectedness of human, animal, and environmental health in wastewater management. It underscores the need for a One Health approach to address the United Nations Sustainable Development Goals.

The effect of sampling frequency and spatial and temporal variation in the density of fecal indicator bacteria on the assessment of coastal bathing water quality

The time and location of sampling as well as the number of samples per season can influence a reliable assessment of bathing water quality. In this study, we investigated the spatio-temporal variation of fecal indicator bacteria (FIB) density and the effects of FIB variability and sampling frequency on the assessment of a single sample and the annual and final assessment of coastal bathing water quality. Increasing the number of samples from 10 to 20 per bathing season had a significant impact on bathing water quality assessment at sites where water quality fluctuations had previously been observed, resulting in a change in water quality to a lower category in 36 % of annual and 54 % of final assessments, suggesting that the minimum number of samples per season should be increased at such sites. Increasing the number of samples at sites assessed as excellent over a longer period had no impact on water quality assessment.Spatial and temporal variations in FIB density were significant at a considerable number of sites both in the single sample assessment and in the annual and final assessment. Bathing water quality was spatially unrepresentative at a quarter of the sites analyzed and temporally unrepresentative at a fifth, as there was at least one additional point with a lower bathing water quality than the official sampling point or the bathing water quality was lower in the afternoon than in the morning.When revising the current recreational water quality regulations, the impact of sampling frequency of and of spatio-temporal variation of FIB density on the relevance of bathing water quality assessment at sites subjected to pollution needs to be seriously considered.

Impact of wastewater treatment and drought in an Alpine region: a multidisciplinary case study

In the context of global climate change, drought occurrence in streams of alpine origin is a recent phenomenon, whose impact is still poorly investigated. In this study, we adopted a three-disciplinary approach to investigate the response of an Alpine river (NW Italy) to severe drought conditions occurred in the year 2022. We hypothesised that the considerable loss in the water flow could exacerbate wastewater treatment plant (WWTP) discharge effects, lowering dilution capacity of the stream system and then increasing chemical/microbial pollution and altering benthic community characteristics. To assess river response to drought conditions of the considered year, the concentration of the main chemical variables, faecal indicator bacteria, pathogen presence and structural/functional organisation of benthic macroinvertebrates and diatom communities were measured monthly in the reaches located upstream and downstream of a WWTP (January–December 2022). Main environmental variables, such as flow velocity, water depth, and flow regime, were also considered. A multivariate analysis approach was then applied to emphasise correlations between selected variables and flow regime.Comparing upstream and downstream sections over the considered year, a common behaviour of chemical/microbiological parameters was observed, with generally higher concentrations of nutrients and bacterial indicators downstream of the local WWTP. Moreover, a positive correlation between water scarcity and nutrients/bacterial concentrations was revealed. The macroinvertebrate communities responded accordingly, both in terms of density and biological metric shift.Interestingly, differences between the two sections were strictly associated with hydrological conditions, with higher dissimilarities found in low-flow conditions. As the magnitude and duration of drought events are projected to increase in the years to come in different parts of Europe, this work can serve as a first building block and as a hint for future studies aimed at improving our knowledge about the consequences of these events that is pivotal for planning effective management strategies.

The challenge of reducing the fecal indicator bacteria load and preventing spawning during depuration of Perna perna mussels

Perna perna mussels commonly spawn during depuration under water temperatures above 18°C. A previous study conducted under experimental conditions (15L aquariums) has suggested reducing the temperature to decrease the odds of spawning. This study monitored the concentrations of Escherichia coli in mussels during three 48-hour and two 72-hour depuration cycles conducted in a small (600L) commercial depuration unit, under temperatures of 14°C and 17°C. The protocol prevented mussels from spawning, as this behavior was observed only in a few mussels in one out of the four depuration cycles. The reduction of fecal indicator bacteria loads, in turn, was unsatisfactory in all depuration cycles, with at least 67% of the samples from cycles 1, 3, 4, and 5 presenting E. coli concentrations above the end product testing limit (230MPN 100g−1) after 48 hours of depuration. Moreover, none of the sample cycles showed bacterial concentrations below that limit, even after 72 hours of depuration.

Development of a logic regression-based approach for the discovery of host- and niche-informative biomarkers in Escherichia coli and their application for microbial source tracking.

Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the Escherichia coli genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of E. coli transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including emrKY-evgAS, ibsB-(mdtABCD-baeSR), ompC-rcsDB, and yedS-yedR, that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water E. coli isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus-thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts.IMPORTANCEThe presence of microbial contaminants, particularly from fecal sources, within water poses a serious risk to public health. The health and economic burden of waterborne pathogens can be substantial-as such, the ability to detect and identify the sources of fecal contamination in environmental waters is crucial for the control of waterborne diseases. This can be accomplished through microbial source tracking, which involves the use of various laboratory techniques to trace the origins of microbial pollution in the environment. Building on current source tracking methodology, we describe a novel workflow that uses logic regression, a supervised machine learning method, to discover genetic markers in Escherichia coli, a common fecal indicator bacterium, that can be used for source tracking efforts. Importantly, our research provides an example of how the rise in prominence of machine learning algorithms can be applied to improve upon current microbial source tracking methodology.

New Frontiers in Water Distribution System Management and Monitoring: First Development of a Water Safety Plan Based on Heritage Building Information Modeling (HBIM) in Neptune Fountain, Bologna, Italy

The World Health Organization (WHO) recommends the introduction of a water safety plan (WSP) approach on drinking water, in all types of settings. This study represents the first WSP developed on the Neptune Fountain, in Bologna (Italy), based on an interdisciplinary approach, integrating hydraulic and microbiological features, in a Building Information Modeling (BIM). The aim was to develop a dynamic and digital platform to update and share the maintenance program, promoting collaboration among microbiologists, engineers, and municipal staff. Water samples were collected along fountain water distribution systems (WDS) from 2016 to 2021 to monitor water quality through the heterotrophic bacteria at 22 °C and 37 °C, as well as to conduct an Enterococci, Coliform bacteria, Escherichia coli, Pseudomonas aeruginosa, Clostridium perfringens, and Staphylococcus aureus assessment. Simultaneously, hydraulic measures were performed, and advanced geomatics techniques were used to detect the WDS structural components, with a focus on the water treatment system (WTS). The WTS consisted of 10 modules corresponding to specific treatments: descaling, carbon–sand filtration, reverse osmosis, and ultraviolet disinfection. Fecal indicators, heterotrophic bacteria, and P. aeruginosa exceeded the reference limits in most of the modules. Several disinfections and washing treatments, other than changing the maintenance procedure scheduling, were performed, improving the WTS and controlling the contamination. The developed microbiological results, hydraulic measurements, and maintenance procedures were integrated in the BIM model to optimize the data storage, updating procedures and the real-time data sharing. This approach improved the fountain management, operation, and material conservation, ultimately preserving the health of daily visitors.

Spatial distribution of faecal indicator bacteria around Kanyakumari coast, Southernmost point of Mainland India

Coastal and marine ecosystems should be sustained by maintaining the better environmental quality for our well-being. The goal of this study was to assess the water quality on the coastlines of Kanyakumari, the southernmost part of Indian mainland. Distribution and abundance of indicator bacteria and opportunistic pathogens related to fecal contamination and antibiotic resistance of the isolates were studied to observe the influence of anthropogenic pressures on coastal waters. Water samples were collected from July’22 to September‘22 from three different ecosystems: Chinnamuttom harbor, Kovalam coast and Manakudy estuary. At each site physio–chemical parameters were noted. Simple main effects analysis showed that the sites have a statistically significant difference in total viable count and total coliform count (p < 0.05). A total of eight indicator bacteria such as E. coli, Klebsiella sp., Enterococcus sp., Aeromonas sp., Proteus mirabilis, Salmonella typhi, Vibrio cholerae and Vibrio paraheamolyticus were identified. Antibiotic sensitivity test by Kirby-Bauer Disk Diffusion method was performed to identify sensitivity pattern of antibiotics. The isolates were exposed to ten antibiotics. All the isolates were resistant to at least one antibiotic, and penicillin was the predominant. Presence of fecal indicators indisputably reveals that the chosen sites are receiving untreated sewage loaded with fecal matter which might have detrimental effect on coastal waters.

Bacteriological quality and physicochemical analysis of the Kalte River at Wolaita Sodo Town, southern Ethiopia

ObjectiveThe current research aimed to investigate the physicochemical and bacteriological quality status of the Kalte River in Wolaita Sodo Town, southern Ethiopia.MethodsA total of 42 water samples were collected using sterile glass bottles from three different river sites: Damota (upstream), Kera (midstream), and Gututo (downstream). All the water samples were examined for the presence of heterotrophic bacteria, total coliform and fecal coliform using direct plate count method and membrane filtration method. Standard methods suggested by American water works association were used to analysis the physicochemical parameters of the water samples.ResultsThe results revealed that the total heterotrophic bacteria, total coliform, and fecal coliform count ranged from 8.9 to 12.6 × 104 cfu/ml, 7.5–11.3 × 102 cfu/ml and 5.7–9.7 × 104 cfu/ml, respectively. The bacterial count results indicated that the river water crossed the WHO-recommended limit of potable water. Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Salmonella, and Shigella species were the common bacterial pathogens isolated from river water samples. The results of the physicochemical analysis revealed that some of the parameters Biological Oxygen Demand (BOD), Chemical Oxygen Demand (COD), and turbidity exceeded the maximum permissible limits of WHO and other parameters were below the WHO permissible limits.ConclusionTherefore, the presence of bacterial pathogens, fecal coliform indicators, and some physicochemical parameters of the Kalte River exceeding the recommended limits may expose users of the river water to the risk of infection.

Stakeholder Interviews to Inform Best Practice for Public Facing COVID-19 Wastewater Dashboards

Background Wastewater (WW) -based epidemiology is the detection of pathogens from wastewater, typically sewage systems. Its use gained popularity during the COVID-19 pandemic as a rapid and non-invasive way to assess infection prevalence in a population. Public facing dashboards for SARS-CoV-2 were developed in response to the discovery that RNA biomarkers were being shed in faeces before symptoms. However, there is not a standard template or guidance for countries to follow. The aim of this research is to reflect on how currently available dashboards evolved during the pandemic and identify suitable content and rationale from these experiences. Methods Interviews were carried out with implementers and users of dashboards for SARS-CoV-2 WW data across Europe and North America. The interviews addressed commonalities and inconsistencies in displaying epidemiological data of SARS-CoV-2, clinical parameters of COVID-19, data on variants, and data transparency. Results The thematic analysis identified WW dashboard elements that can facilitate standardization, or at least interoperability. These elements emphasise communication among developers under the same organization, open access for identified stakeholders, and data summarized with a time-intensive graphic analysis through normalizing at least by population. Simultaneous communication of clinical surveillance is recommended. More research is needed on flow and faecal indicators for normalization of WW data, and on the analysis and representation of variants. Discussion WW dashboard development between 2020-2023 provided a ‘real-time’ iterative process of data representation, and several recommendations have been identified. Communication of data through dashboards has the potential to support early warning systems for infectious diseases.

Selectively Isolation and Molecular Identification by dnaJ Gene of Legionella pneumophila Found in Various Water Sources in Dhaka, Bangladesh

Abstract BACKGROUND: Legionella spp. are the etiological agents of Legionnaires’ disease, often severe pneumonia. After the first severe outbreak of Legionella spp., it was found widely dispersed in natural water sources and humid environments and has become a concern for these sources’ water quality and safety. The fecal indicators used for water quality assessment do not predict the presence of these pathogens; thus, in the absence of targeted analysis, the risk is unobserved until the emergence of infections. There is no study on the presence of Legionella in unattended water bodies in Bangladesh, such as swimming pools, air-conditioned cooling water, and stagnant circulatory water systems. METHODS: A total of 42 water samples were collected from 12 different sites in Dhaka, Bangladesh. Acid, heat, and chlorine treatment were applied to reduce the load of non-Legionellae in water samples. Chlorine treatment was used to kill unwanted organisms in water samples. After successful pretreatment, samples were cultured on buffered charcoal yeast extract agar (BCYE) media. Optimum pH, concentrations of chlorine, and temperature were set up by extensive trial and error culturing of Legionella on BCYE media to minimize other bacterial growth and maximize Legionella growth. Isolated colonies were confirmed primarily by morphological characteristics on BCYE media. Isolates were then confirmed by polymerase chain reaction and gel electrophoresis techniques. We detected the presence of 16S rDNA for Legionella spp. and the dnaJ gene for Legionella pneumophila species identification. Antibiotic sensitivity tests (minimum inhibitory concentration) were also conducted to see if it was alarming for our community’s health. RESULTS: Most of the Legionella spp. could grow at various temperatures, such as 45°C, 50°C, and 55°C, and they could also survive at the normal levels of chlorination, such as 0.25 mg/L and 0.5 mg/L. We have found that, out of 12 different sites, 4 out of 5 (80%) isolates from cooling tower water, 1 out of 4 (25%) from the swimming pool, and 1 out of 3 (33%) household stagnant water are contaminated with Legionella. However, 3 out of 5 isolates found are L. pneumophila from cooling water sites. Furthermore, strains of Legionella spp. were resistant to many antibiotics, such as ciprofloxacin, azithromycin, and tetracycline. CONCLUSIONS: Serious and fatal Legionella spp. (L. pneumophila) infections may be transmitted because of the widespread presence of these water sources and the large number of users in the community. This threat is worsened by the survival of Legionella under various commonly used antibiotic conditions and further exacerbated by their antibiotic resistance. Health-care professionals may face great challenges due to the lack of studies about its prevalence and treatment procedures.

Faecal contamination in China: Trends, sources, and driving mechanisms

Faecal contamination of surface waters is a global public health and economic burden. Here, we constructed a 30-year dataset to analyse the spatiotemporal trends and driving mechanisms of faecal coliforms (FCs) in China. We found that previous national policies to reduce water pollution have significantly improved the quality of surface water and, correspondingly, faecal contamination. However, the downward trend in FC levels has been more gradual than that for physico-chemical pollutants, and this trend may be exaggerated. Our results show that the driving mechanisms of faecal pollution were seasonal and complex. During the dry season, forests and grasslands were the source landscapes that exacerbated faecal pollution; during the wet season, urbanisation dominated, highlighting China's poorly designed drainage systems. Our projections revealed that faecal contamination will continue to worsen from 2022 to 2035, highlighting the need for pollution control. In the future, faecal indicators should be included in routine monitoring, evaluation, and assessment at the national level. Moreover, coordinated design of forest, grassland, and wetland landscapes is recommended for faecal pollution control at the regional level, whereas stormwater-related source control needs to be further strengthened at the urban level.

Multi-factor normalisation of viral counts from wastewater improves the detection accuracy of viral disease in the community

The detection of viruses (e.g. SARS-CoV-2, norovirus) in wastewater represents an effective way to monitor the prevalence of these pathogens circulating within the community. However, accurate quantification of viral concentrations in wastewater, proportional to human input, is constrained by a range of uncertainties, including (i) dilution within the sewer network, (ii) degradation of viral RNA during wastewater transit, (iii) catchment population and facility use, (iv) efficiency of viral concentration and extraction from wastewater, and (v) inhibition of amplification during the RT-qPCR step. Here, we address these uncertainties by investigating several potential normalisation factors including the concentration of ammonium and orthophosphate. A faecal indicator virus (crAssphage), and the recovery of the process-control viruses (murine norovirus and bacteriophage Phi6), used for quality control during the RT-qPCR step, were also considered. We found that multi-factor normalisation of SARS-CoV-2 RT-qPCR data was optimal using a combination of crAssphage, process-control virus recovery, and concentration efficiency to improve prediction accuracy relative to clinical test data. Using multi-normalised SARS-CoV-2 RT-qPCR data, we found a lasso regression model with random forest modelled residuals lowers the prediction error of positives by 46 %, compared to a single linear regression using raw data. This multi-normalised approach enables more accurate wastewater-based predictions of clinical cases up to five days in advance of clinical data, identifying trends in disease prevalence before clinical testing, and demonstrates the potential to improve viral pathogen detection for a range of currently monitored and emerging diseases.