Effect of rainfall on Giardia and crypto

Opportunistic Pathogens in Drinking Water Distribution Systems-A Review

In contrast to "frank" pathogens, like Salmonella entrocolitica, Shigella dysenteriae, and Vibrio cholerae, that always have a probability of disease, "opportunistic" pathogens are organisms that cause an infectious disease in a host with a weakened immune system and rarely in a healthy host. Historically, drinking water treatment has focused on control of frank pathogens, particularly those from human or animal sources (like Giardia lamblia, Cryptosporidium parvum, or Hepatitis A virus), but in recent years outbreaks from drinking water have increasingly been due to opportunistic pathogens. Characteristics of opportunistic pathogens that make them problematic for water treatment include: (1) they are normally present in aquatic environments, (2) they grow in biofilms that protect the bacteria from disinfectants, and (3) under appropriate conditions in drinking water systems (e.g., warm water, stagnation, low disinfectant levels, etc.), these bacteria can amplify to levels that can pose a public health risk. The three most common opportunistic pathogens in drinking water systems are Legionella pneumophila, Mycobacterium avium, and Pseudomonas aeruginosa. This report focuses on these organisms to provide information on their public health risk, occurrence in drinking water systems, susceptibility to various disinfectants, and other operational practices (like flushing and cleaning of pipes and storage tanks). In addition, information is provided on a group of nine other opportunistic pathogens that are less commonly found in drinking water systems, including Aeromonas hydrophila, Klebsiella pneumoniae, Serratia marcescens, Burkholderia pseudomallei, Acinetobacter baumannii, Stenotrophomonas maltophilia, Arcobacter butzleri, and several free-living amoebae including Naegleria fowleri and species of Acanthamoeba. The public health risk for these microbes in drinking water is still unclear, but in most cases, efforts to manage Legionella, mycobacteria, and Pseudomonas risks will also be effective for these other opportunistic pathogens. The approach to managing opportunistic pathogens in drinking water supplies focuses on controlling the growth of these organisms. Many of these microbes are normal inhabitants in biofilms in water, so the attention is less on eliminating these organisms from entering the system and more on managing their occurrence and concentrations in the pipe network. With anticipated warming trends associated with climate change, the factors that drive the growth of opportunistic pathogens in drinking water systems will likely increase. It is important, therefore, to evaluate treatment barriers and management activities for control of opportunistic pathogen risks. Controls for primary treatment, particularly for turbidity management and disinfection, should be reviewed to ensure adequacy for opportunistic pathogen control. However, the major focus for the utility's opportunistic pathogen risk reduction plan is the management of biological activity and biofilms in the distribution system. Factors that influence the growth of microbes (primarily in biofilms) in the distribution system include, temperature, disinfectant type and concentration, nutrient levels (measured as AOC or BDOC), stagnation, flushing of pipes and cleaning of storage tank sediments, and corrosion control. Pressure management and distribution system integrity are also important to the microbial quality of water but are related more to the intrusion of contaminants into the distribution system rather than directly related to microbial growth. Summarizing the identified risk from drinking water, the availability and quality of disinfection data for treatment, and guidelines or standards for control showed that adequate information is best available for management of L. pneumophila. For L. pneumophila, the risk for this organism has been clearly established from drinking water, cases have increased worldwide, and it is one of the most identified causes of drinking water outbreaks. Water management best practices (e.g., maintenance of a disinfectant residual throughout the distribution system, flushing and cleaning of sediments in pipelines and storage tanks, among others) have been shown to be effective for control of L. pneumophila in water supplies. In addition, there are well documented management guidelines available for the control of the organism in drinking water distribution systems. By comparison, management of risks for Mycobacteria from water are less clear than for L. pneumophila. Treatment of M. avium is difficult due to its resistance to disinfection, the tendency to form clumps, and attachment to surfaces in biofilms. Additionally, there are no guidelines for management of M. avium in drinking water, and one risk assessment study suggested a low risk of infection. The role of tap water in the transmission of the other opportunistic pathogens is less clear and, in many cases, actions to manage L. pneumophila (e.g., maintenance of a disinfectant residual, flushing, cleaning of storage tanks, etc.) will also be beneficial in helping to manage these organisms as well.

Relationship between extreme precipitation and acute gastrointestinal illness in Toronto, Ontario, 2012-2022

Extreme precipitation events are occurring more intensely in Canada. This can contaminate water sources with enteric pathogens, potentially increasing the risk of acute gastrointestinal illness. This study aimed to investigate the relationship between extreme precipitation and emergency department (ED) visits for acute gastrointestinal illness in Toronto from 2012 to 2022. Distributed lag non-linear models were constructed on ED visit counts with a Quasi Poisson distribution. Extreme precipitation was modelled as a 21-day lag variable, with a linear relationship assumed at levels ≧95th percentile. Separate models were also conducted on season-specific data sets. Daily precipitation and gastrointestinal illness ED visits ranged between 0 to 126 mm, and 12 to 180 visits respectively. Overall, a 10-mm increase in precipitation >95th percentile had no significant relationship with the risk of ED visits. However, stratification by seasons revealed significant relationships during spring (lags 1-19, peak at lag 14 RR = 1.04; 95% CI: 1.03, 1.06); the overall cumulative effect across the 21-day lag was also significant (RR = 1.94; 95% CI: 1.47, 2.57). Extreme precipitation has a seasonal effect on gastrointestinal health outcomes in Toronto city, suggesting varying levels of enteric pathogen exposures through drinking water or other environmental pathway during different seasons.

Environmental Factors Associated with Cryptosporidium and Giardia

Environmental factors significantly influence the transmission of intestinal protozoan diseases. Cryptosporidiosis and giardiasis are important zoonotic diseases characterized by diarrhea, and are mainly water or foodborne diseases caused by fecal-borne oocysts. The One Health approach effectively addresses environmentally influenced zoonotic diseases. However, the impact of environmental factors on the survival of Cryptosporidium/Giardia (oo)cysts or disease transmission is mostly uncharacterized. Associations between cryptosporidiosis and giardiasis incidence and environmental variables (e.g., climatic conditions, soil characteristics, and water characteristics) have been reported; however, the identified relationships are not consistently reported. Whether these are country-specific or global observations is unclear. Herein, we review the evidence for the influence of environmental factors on Cryptosporidium/Giardia and corresponding diseases from three perspectives: climatic, soil, and water characteristics. The (oo)cyst concentration or survival of Cryptosporidium/Giardia and the incidence of corresponding diseases are related to environmental variables. The associations identified varied among studies and have different levels of importance and lag times in different locations. This review summarizes the influence of relevant environmental factors on Cryptosporidium/Giardia from the One Health perspective and provides recommendations for future research, monitoring, and response.

Hurricane flooding and acute gastrointestinal illness in North Carolina

Hurricanes often flood homes and industries, spreading pathogens. Contact with pathogen-contaminated water can result in diarrhea, vomiting, and/or nausea, known collectively as acute gastrointestinal illness (AGI). Hurricanes Matthew and Florence caused record-breaking flooding in North Carolina (NC) in October 2016 and September 2018, respectively. To examine the relationship between hurricane flooding and AGI in NC, we first calculated the percent of each ZIP code flooded after Hurricanes Matthew and Florence. Rates of all-cause AGI emergency department (ED) visits were calculated from NC's ED surveillance system data. Using controlled interrupted time series, we compared AGI ED visit rates during the three weeks after each hurricane in ZIP codes with a third or more of their area flooded to the predicted rates had these hurricanes not occurred, based on AGI 2016-2019 ED trends, and controlling for AGI ED visit rates in unflooded areas. We examined alternative case definitions (bacterial AGI) and effect measure modification by race and age. We observed an 11% increase (rate ratio (RR): 1.11, 95% CI: 1.00, 1.23) in AGI ED visit rates after Hurricanes Matthew and Florence. This effect was particularly strong among American Indian patients and patients aged 65 years and older after Florence and elevated among Black patients for both hurricanes. Florence's effect was more consistent than Matthew's effect, possibly because little rain preceded Florence and heavy rain preceded Matthew. When restricted to bacterial AGI, we found an 85% (RR: 1.85, 95% CI: 1.37, 2.34) increase in AGI ED visit rate after Florence, but no increase after Matthew. Hurricane flooding is associated with an increase in AGI ED visit rate, although the strength of effect may depend on total storm rainfall or antecedent rainfall. American Indians and Black people-historically pushed to less desirable, flood-prone land-may be at higher risk for AGI after storms.

Immune function differs among tropical environments but is not downregulated during reproduction in three year-round breeding equatorial lark populations

Seasonal variation in immune function can be attributed to life history trade-offs, and to variation in environmental conditions. However, because phenological stages and environmental conditions co-vary in temperate and arctic zones, their separate contributions have not been determined. We compared immune function and body mass of incubating (female only), chick-feeding (female and male), and non-breeding (female and male) red-capped larks Calandrella cinerea breeding year-round in three tropical equatorial (Kenya) environments with distinct climates. We measured four immune indices: haptoglobin, nitric oxide, agglutination, and lysis. To confirm that variation in immune function between breeding (i.e., incubating or chick-feeding) and non-breeding was not confounded by environmental conditions, we tested if rainfall, average minimum temperature (T_min), and average maximum temperature (T_max) differed during sampling times among the three breeding statuses per location. T_min and T_max differed between chick-feeding and non-breeding, suggesting that birds utilized environmental conditions differently in different locations for reproduction. Immune indices did not differ between incubating, chick-feeding and non-breeding birds in all three locations. There were two exceptions: nitric oxide was higher during incubation in cool and wet South Kinangop, and it was higher during chick-feeding in the cool and dry North Kinangop compared to non-breeding birds in these locations. For nitric oxide, agglutination, and lysis, we found among-location differences within breeding stage. In equatorial tropical birds, variation in immune function seems to be better explained by among-location climate-induced environmental conditions than by breeding status. Our findings raise questions about how within-location environmental variation relates to and affects immune function.

Application of QMRA to prioritise water supplies for Cryptosporidium risk in New South Wales, Australia

A Quantitative Microbial Risk Assessment (QMRA) framework was applied to assess 312 drinking water supply systems across regional New South Wales (NSW). The framework was needed to support the implementation of a recommendation in the Australian Drinking Water Guidelines (ADWG) for appropriate treatment barriers to be operating in systems 'at risk' for Cryptosporidium. The objective was to prioritise systems so that those with the highest risk could be identified and addressed first. The framework was developed in a pilot study of 30 systems, selected to represent the range of water supplies across regional NSW. From these, source water categories were defined to represent local conditions with reference to the literature and Cryptosporidium risk factors. Values for Cryptosporidium oocyst concentration were assigned to the categories to allow quantification of the health risk from those water sources. The framework was then used to assess the risks in all 312 regional drinking water supply systems. Combining the disciplined approach of QMRA with simple catchment and treatment information and categorical risk outputs provided a useful and transparent method for prioritising systems for further investigation and potential risk management intervention. The risk rankings for drinking water supplies from this QMRA process have been used to set priorities for a large State Government funding program.

Importance of Distributional Forms for the Assessment of Protozoan Pathogens Concentrations in Drinking-Water Sources

The identification of appropriately conservative statistical distributions is needed to predict microbial peak events in drinking water sources explicitly. In this study, Poisson and mixed Poisson distributions with different upper tail behaviors were used for modeling source water Cryptosporidium and Giardia data from 30 drinking water treatment plants. Small differences (<0.5-log) were found between the "best" estimates of the mean Cryptosporidium and Giardia concentrations with the Poisson-gamma and Poisson-log-normal models. However, the upper bound of the 95% credibility interval on the mean Cryptosporidium concentrations of the Poisson-log-normal model was considerably higher (>0.5-log) than that of the Poisson-gamma model at four sites. The improper choice of a model may, therefore, mislead the assessment of treatment requirements and health risks associated with the water supply. Discrimination between models using the marginal deviance information criterion (mDIC) was unachievable because differences in upper tail behaviors were not well characterized with available data sets ( n<30 ). Therefore, the gamma and the log-normal distributions fit the data equally well but may predict different risk estimates when they are used as an input distribution in an exposure assessment. The collection of event-based monitoring data and the modeling of larger routine monitoring data sets are recommended to identify appropriately conservative distributions to predict microbial peak events.

Impact of Hydrometeorological Events for the Selection of Parametric Models for Protozoan Pathogens in Drinking-Water Sources

Temporal variations in concentrations of pathogenic microorganisms in surface waters are well known to be influenced by hydrometeorological events. Reasonable methods for accounting for microbial peaks in the quantification of drinking water treatment requirements need to be addressed. Here, we applied a novel method for data collection and model validation to explicitly account for weather events (rainfall, snowmelt) when concentrations of pathogens are estimated in source water. Online in situ β-d-glucuronidase activity measurements were used to trigger sequential grab sampling of source water to quantify Cryptosporidium and Giardia concentrations during rainfall and snowmelt events at an urban and an agricultural drinking water treatment plant in Quebec, Canada. We then evaluate if mixed Poisson distributions fitted to monthly sampling data ( n = 30 samples) could accurately predict daily mean concentrations during these events. We found that using the gamma distribution underestimated high Cryptosporidium and Giardia concentrations measured with routine or event-based monitoring. However, the log-normal distribution accurately predicted these high concentrations. The selection of a log-normal distribution in preference to a gamma distribution increased the annual mean concentration by less than 0.1-log but increased the upper bound of the 95% credibility interval on the annual mean by about 0.5-log. Therefore, considering parametric uncertainty in an exposure assessment is essential to account for microbial peaks in risk assessment.

Automated Targeted Sampling of Waterborne Pathogens and Microbial Source Tracking Markers Using Near-Real Time Monitoring of Microbiological Water Quality

Waterborne pathogens are heterogeneously distributed across various spatiotemporal scales in water resources, and representative sampling is therefore crucial for accurate risk assessment. Since regulatory monitoring of microbiological water quality is usually conducted at fixed time intervals, it can miss short-term fecal contamination episodes and underestimate underlying microbial risks. In the present paper, we developed a new automated sampling methodology based on near real-time measurement of a biochemical indicator of fecal pollution. Online monitoring of β-D-glucuronidase (GLUC) activity was used to trigger an automated sampler during fecal contamination events in a drinking water supply and at an urban beach. Significant increases in protozoan parasites, microbial source tracking markers and E. coli were measured during short-term (<24 h) fecal pollution episodes, emphasizing the intermittent nature of their occurrence in water. Synchronous triggering of the automated sampler with online GLUC activity measurements further revealed a tight association between the biochemical indicator and culturable E. coli. The proposed event sampling methodology is versatile and in addition to the two triggering modes validated here, others can be designed based on specific needs and local settings. In support to regulatory monitoring schemes, it should ultimately help gathering crucial data on waterborne pathogens more efficiently during episodic fecal pollution events.

Using surrogate data to assess risks associated with microbial peak events in source water at drinking water treatment plants

A monitoring strategy was implemented at two drinking water treatment plants in Quebec, Canada, to evaluate microbial reduction performances of full-scale treatment processes under different source water conditions. β-D-glucuronidase activity in source water was automatically monitored in near-real-time to establish baseline and event conditions at each location. High-volume water samples (50-1,500 L) were collected at the inflow and the outflow of coagulation/flocculation, filtration, and UV disinfection processes and were analysed for two naturally occurring surrogate organisms: Escherichia coli and Clostridium perfringens. Source water Cryptosporidium data and full-scale C. perfringens reduction data were entered into a quantitative microbial risk assessment (QMRA) model to estimate daily infection risks associated with exposures to Cryptosporidium via consumption of treated drinking water. Daily mean E. coli and Cryptosporidium concentrations in source water under event conditions were in the top 5% (agricultural site) or in the top 15% (urban site) of what occurs through the year at these drinking water treatment plants. Reduction performances of up to 6.0-log for E. coli and 5.6-log for C. perfringens were measured by concentrating high-volume water samples throughout the treatment train. For both drinking water treatment plants, removal performances by coagulation/flocculation/sedimentation processes were at the high end of the range of those reported in the literature for bacteria and bacterial spores. Reductions of E. coli and C. perfringens by floc blanket clarification, ballasted clarification and rapid sand filtration did not deteriorate during two snowmelt/rainfall events. QMRA results suggested that daily infection risks were similar during two rainfall/snowmelt events than during baseline conditions. Additional studies investigating full-scale reductions would be desirable to improve the evaluation of differences in treatment performances under various source water conditions.

Genetic Microbial Source Tracking Support QMRA Modeling for a Riverine Wetland Drinking Water Resource

Riverine wetlands are important natural habitats and contain valuable drinking water resources. The transport of human- and animal-associated fecal pathogens into the surface water bodies poses potential risks to water safety. The aim of this study was to develop a new integrative modeling approach supported by microbial source tracking (MST) markers for quantifying the transport pathways of two important reference pathogens, Cryptosporidium and Giardia, from external (allochthonous) and internal (autochthonous) fecal sources in riverine wetlands considering safe drinking water production. The probabilistic-deterministic model QMRAcatch (v 1.1 python backwater) was modified and extended to account for short-time variations in flow and microbial transport at hourly time steps. As input to the model, we determined the discharge rates, volumes and inundated areas of the backwater channel based on 2-D hydrodynamic flow simulations. To test if we considered all relevant fecal pollution sources and transport pathways, we validated QMRAcatch using measured concentrations of human, ruminant, pig and bird associated MST markers as well as E. coli in a Danube wetland area from 2010 to 2015. For the model validation, we obtained MST marker decay rates in water from the literature, adjusted them within confidence limits, and simulated the MST marker concentrations in the backwater channel, resulting in mean absolute errors of < 0.7 log₁₀ particles/L (Kruskal–Wallis p > 0.05). In the scenarios, we investigated (i) the impact of river discharges into the backwater channel (allochthonous sources), (ii) the resuspension of pathogens from animal fecal deposits in inundated areas, and (iii) the pathogen release from animal fecal deposits after rainfall (autochthonous sources). Autochthonous and allochthonous human and animal sources resulted in mean loads and concentrations of Cryptosporidium and Giardia (oo)cysts in the backwater channel of 3–13 × 10⁹ particles/hour and 0.4–1.2 particles/L during floods and rainfall events, and in required pathogen treatment reductions to achieve safe drinking water of 5.0–6.2 log₁₀. The integrative modeling approach supports the sustainable and proactive drinking water safety management of alluvial backwater areas.

Occurrence of Giardia duodenalis in selected stations and tributary rivers of Laguna Lake, Philippines

Fecal pollution is a major contributor to the progressive degradation of Laguna Lake, the Philippines' largest inland lake used for aquaculture, recreation, and as a source of irrigation and domestic water. Consequently, intestinal parasites may be present in this body of water, posing risks to water safety and human health. This study was able to detect the protozoan parasite, Giardia duodenalis, in three Laguna Lake stations and seven tributary rivers in a 13-month monitoring period by PCR amplification of the small subunit ribosomal RNA (SSU rRNA) gene of Giardia cysts concentrated from water samples. The pathogen was present in 37.7% of tributary samples (n = 69) and 16.7% of lake samples (n = 36). Notable frequencies of detection were observed in four tributary rivers -Bagumbayan, Taguig (66.7%); Santa Rosa, Laguna (55.6%); San Cristobal, Cabuyao, Laguna (44.4%); and Biñan, Laguna (42.9%). All test SSU rRNA gene sequences were identified as human-infective genotypes of G. duodenalis predominated by Assemblage A (94.1%). Furthermore, analysis of the glutamate dehydrogenase (gdh) gene revealed the possible presence of mixed genotypes in at least two samples. These results support the pressing need to include protozoan pathogen monitoring in Laguna Lake and its tributaries to prevent Giardia infection in humans and animals. This study also recommends microbial source tracking to identify fecal pollution sources and aid in regulation of waste discharges into the lake and its tributaries.

Molecular surveillance of Cryptosporidium spp. for microbial source tracking of fecal contamination in Laguna Lake, Philippines

Water quality deterioration in source waters poses increased health, environmental, and economic risks. Here, we genotyped Cryptosporidium spp. obtained from water samples of Laguna Lake, Philippines, and its tributaries for the purpose of source-tracking fecal contamination. A total of 104 surface water samples were collected over a 1-year period (March 2018 to April 2019). Detection of Cryptosporidium was carried out using genus-specific primers targeting a fragment of the small subunit (SSU) rRNA gene. The study revealed 8 (14%) tributary samples and 1 (2.77%) lake sample positive for contamination. The species were determined to be C. parvum (n = 4), C. muris (n = 2), C. hominis (n = 1), C. galli (n = 1), C. baileyi (n = 1), C. suis (n = 1), as well as rat genotype IV (n = 1). Two species were detected in duck (C. baileyi) and cattle (C. parvum) fecal samples. The data presented suggest that Cryptosporidium contamination is likely to come from sewage or human feces as well as various agricultural sources (i.e. cattle, swine, and poultry). This information reveals the importance of mitigating fecal pollution in the lake system and minimizing health risks due to exposure to zoonotic Cryptosporidium species.

Role of Environmental Variables in the Transport of Microbes in Stormwater

Microbial pathogens present in stormwater, which originate from human sewage and animal faecal matters, are one of the major impediments in stormwater reuse. The transport of microbes in stormwater is more than just a physical process. The mobility of microbes in stormwater is governed by many factors, such as dissolved organic matter, cations, pH, temperature and water flow. This paper examined the roles of three environmental variables, namely: dissolved organic matter, positive cations and stormwater flow on the transport of two faecal indicator bacteria (FIB), Enterococcus spp. and Escherichia coli. Stormwater runoff samples were collected during twelve wet weather events and one dry weather event from a medium density residential urban catchment in Brisbane. Enterococcus spp. numbers as high as 3 × 104 cfu/100 mL were detected in the stormwater runoff, while Escherichia coli numbers up to 3.6 × 103 cfu/100 mL were observed. The dissolved organic carbon (DOC) in the stormwater samples was in the range of 2.2–5.9 mg/L with an average concentration of 4.5 mg/L in which the hydrophilic carbon constituted the highest mass fraction of 60–80%. The results also showed that the transport of FIB in stormwater was reduced with an increasing concentration of the hydrophilic organic fraction, especially the humic fraction. On the contrary, the concentration of trivalent cations and stormwater flow rate showed a positive correlation with the FIB numbers. These findings indicated the potentiality to make a good use and measurement of simple environmental variables to reflect the degree of microbe transport in stormwater from residential/suburban catchments.

Bacterial community structure upstream and downstream of cascade dams along the Lancang River in southwestern China

Extensive construction of dams by humans has caused alterations in flow regimes and concomitant alterations in river ecosystems. Even so, bacterioplankton diversity in large rivers influenced by cascade dams has been largely ignored. In this study, bacterial community diversity and profiles of seven cascade dams along the720 km of the Lancang River were studied using Illumina sequencing of the V3-V4 hypervariable region of the 16S rRNA gene. Spatiotemporal variations of bacterial communities in sediment and water of the Gongguoqiao hydroelectric dam and factors affecting these variations were also examined. Microbial diversity and richness in surface water increased slightly from upstream toward downstream along the river. A significant positive correlation between spatial distance and dissimilarities in bacterial community structure was confirmed (Mantel test, r = 0.4826, p = 0.001). At the Gongguoqiao hydroelectric dam, temporal differences in water overwhelmed spatial variability in bacterial communities. Temperature, precipitation, and nutrient levels were major drivers of seasonal microbial changes. Most functional groups associated with carbon cycling in sediment samples decreased from winter to summer. Our findings improve our understanding of associations, compositions, and predicted functional profiles of microbial communities in a large riverine ecosystem influenced by multiple cascade dams.

Influence of weather and climate on cryptosporidiosis-A review

Studies have shown that climatic factors can significantly influence transmission of many waterborne diseases. However, knowledge of the impact of climate variability on cryptosporidiosis is much less certain. Associations between the incidence of cryptosporidiosis and climatic variables have been reported in several countries. Given that the identified relationships were not consistently reported across studies, it is not known whether these were country-specific observations or can be considered more globally. Variation in the disease risk in both low- and middle-income countries and high-income countries presents new challenges and opportunities to enact responsive changes in research and public health policies. Available epidemiological evidence of the influence of weather and climate on cryptosporidiosis is reviewed. Fourteen studies met the inclusion criteria, and most studies showed that the incidence of cryptosporidiosis is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. The identified associations varied across studies, with different conditions of importance and lag times across different locations. Therefore, there is a need for countries at risk to assess Cryptosporidium transmission routes based on the spatiotemporal patterns of the disease and what role climate and other socio-ecological changes play in the transmission. Information gathering will then allow us to provide information for evidence-based control strategies and mitigation of transmission. This review offers new perspectives on the role of climate variability on Cryptosporidium transmission. It highlights different epidemiological approaches adopted and provides the potential for future research and surveillance to reduce the disease burden. By evaluating the epidemiological transmission of this organism in high-income countries, all mitigation strategies, for example filtration and water catchment management, can be used as exemplars of preventing infection in low- to middle-income countries.

Investigating the public health risks of low impact developments at residential, neighbourhood, and municipal levels

Low Impact Developments (LIDs) employ a series of vegetative techniques to retain rainfall close to the site of origin. Although LIDs offer sustainable runoff management, these infrastructures can be considered a risk to public health due to the presence of pathogens in the runoff and human exposure to contaminated water held in and transported by LIDs. The objective of this study is to examine the disease burden of Gastrointestinal illness (GI) from exposure to LIDs at the residential, neighbourhood, and municipal levels. The authors conducted a meta-analysis of literature on three water features: (1) harvested rainwater obtained from LIDs, (2) surface water, and (3) floodwater. A set of 32 studies were systematically selected to collect values of risks of infection and expressed as the disease burden, i.e. disability adjusted life years (DALYs). The results showed that the percentage of GI illness exceeding the health guidelines were high for harvested rainwater, i.e. 22% of annual disease burden exceeded the WHO guidelines (0.001 DALYs/1000 persons), and 2% exceeded the US EPA guidelines (5.75 DALYs/1000 bathers). Among the six exposures for harvested rainwater, exposure to spray irrigation, exceeded US EPA guidelines whereas; five exposures, i.e. flushing, hosing, daily shower, spray irrigation, and children playing, surpassed the WHO guidelines. Considering LID treatment, the values of annual disease burden from all the selected barriers were below US EPA guidelines however, these values exceeded the WHO guidelines for three barriers i.e. water plaza, grass swale, and open storage ponds. These findings provide a broader perspective of the disease burden associated with LIDs and emphasise to consider the type of exposures and required treatment barriers for developing LID infrastructures in urban areas.

Can routine monitoring of E. coli fully account for peak event concentrations at drinking water intakes in agricultural and urban rivers?

In several jurisdictions, the arithmetic mean of Escherichia coli concentrations in raw water serves as the metric to set minimal treatment requirements by drinking water treatment plants (DWTPs). An accurate and precise estimation of this mean is therefore critical to define adequate requirements. Distributions of E. coli concentrations in surface water can be heavily skewed and require statistical methods capable of characterizing uncertainty. We present four simple parametric models with different upper tail behaviors (gamma, log-normal, Lomax, mixture of two log-normal distributions) to explicitly account for the influence of peak events on the mean concentration. The performance of these models was tested using large E. coli data sets (200-1800 samples) from raw water regulatory monitoring at six DWTPs located in urban and agricultural catchments. Critical seasons of contamination and hydrometeorological factors leading to peak events were identified. Event-based samples were collected at an urban DWTP intake during two hydrometeorological events using online β-d-glucuronidase activity monitoring as a trigger. Results from event-based sampling were used to verify whether selected parametric distributions predicted targeted peak events. We found that the upper tail of the log-normal and the Lomax distributions better predicted large concentrations than the upper tail of the gamma distribution. Weekly sampling for two years in urban catchments and for four years in agricultural catchments generated reasonable estimates of the average raw water E. coli concentrations. The proposed methodology can be easily used to inform the development of sampling strategies and statistical indices to set site-specific treatment requirements.

Heavy precipitation, drinking water source, and acute gastrointestinal illness in Philadelphia, 2015-2017

Runoff from heavy precipitation events can lead to microbiological contamination of source waters for public drinking water supplies. Philadelphia is a city of interest for a study of waterborne acute gastrointestinal illness (AGI) because of frequent heavy precipitation, extensive impervious landcover, and combined sewer systems that lead to overflows. We conducted a time-series analysis of the association between heavy precipitation and AGI incidence in Philadelphia, served by drinking water from Delaware River and Schuylkill River source waters. AGI cases on each day during the study period (2015-2017) were captured through syndromic surveillance of patients' chief complaint upon presentation at local emergency departments. Daily precipitation was represented by measurements at the Philadelphia International Airport and by modeled precipitation within the watershed boundaries, and we also evaluated stream flowrate as a proxy of precipitation. We estimated the association using distributed lag nonlinear models, assuming a quasi-Poisson distribution of the outcome variable and with adjustment for potential confounding by seasonal and long-term time trends, ambient temperature, day-of-week, and major holidays. We observed an association between heavy precipitation and AGI incidence in Philadelphia that was primarily limited to the spring season, with significant increases in AGI that peaked from 8 to 16 days following a heavy precipitation event. For example, the increase in AGI incidence related to airport precipitation above the 95th percentile (vs no precipitation) during spring reached statistical significance on lag day 7, peaked on day 16 (102% increase, 95% confidence interval: 16%, 252%), and declined while remaining significantly elevated through day 28. Similar associations were observed in analyses of watershed-specific precipitation in relation to AGI cases within the populations served by drinking water from each river. Our results suggest that heavy precipitation events in Philadelphia result in detectable local increases in waterborne AGI.

Investigations from Northern Greece on mussels cultivated in areas proximal to wastewaters discharges, as a potential source for human infection with Giardia and Cryptosporidium

Marine bivalves are usually cultivated in shallow, estuarine waters where there is a high concentration of nutrients. Many micro-pollutants, including the protozoan parasites Giardia duodenalis and Cryptosporidium spp., which also occur in such environments, may be concentrated in shellfish tissues during their feeding process. Shellfish can thus be considered as vehicles for foodborne infections, as they are usually consumed lightly cooked or raw. Therefore, the main objective of this study was to investigate the presence of both parasites in Mediterranean mussels, Mytilus galloprovincialis that are cultivated in Thermaikos Gulf, North Greece, which is fed by four rivers that are contaminated with both protozoa. Moreover, the occurrence of these protozoa was monitored in treated wastewaters from 3 treatment plants that discharge into the gulf. In order to identify potential sources of contamination and to estimate the risk for human infection, an attempt was made to genotype Giardia and Cryptosporidium in positive samples. Immunofluorescence was used for detection and molecular techniques were used for both detection and genotyping of the parasites. In total, 120 mussel samples, coming from 10 farms, were examined for the presence of both protozoa over the 6-month farming period. None of them were found positive by immunofluorescence microscopy for the presence of parasites. Only in 3 mussel samples, PCR targeting the GP60 gene detected Cryptosporidium spp. DNA, but sequencing was not successful. Thirteen out of 18 monthly samples collected from the 3 wastewater treatment plants, revealed the presence of Giardia duodenalis cysts belonging to sub-assemblage AII, at relatively low counts (up to 11.2 cysts/L). Cryptosporidium oocysts (up to 0.9 oocysts/L) were also detected in 4 out of 8 samples, although sequencing was not successful at any of the target genes. At the studied location and under the sampling conditions described, mussels tested were not found to be harboring Giardia cysts and the presence of Cryptosporidium was found only in few cases (by PCR detection only). Our results suggest that the likelihood that mussels from these locations act as vehicles of human infection for Giardia and Cryptosporidium seems low.

Projected local rain events due to climate change and the impacts on waterborne diseases in Vancouver, British Columbia, Canada

BACKGROUND

Climate change is increasing the number and intensity of extreme weather events in many parts of the world. Precipitation extremes have been linked to both outbreaks and sporadic cases of waterborne illness. We have previously shown a link between heavy rain and turbidity to population-level risk of sporadic cryptosporidiosis and giardiasis in a major Canadian urban population. The risk increased with 30 or more dry days in the 60 days preceding the week of extreme rain. The goal of this study was to investigate the change in cryptosporidiosis and giardiasis risk due to climate change, primarily change in extreme precipitation.

METHODS

Cases of cryptosporidiosis and giardiasis were extracted from a reportable disease system (1997-2009). We used distributed lag non-linear Poisson regression models and projections of the exposure-outcome relationship to estimate future illness (2020-2099). The climate projections are derived from twelve statistically downscaled regional climate models. Relative Concentration Pathway 8.5 was used to project precipitation derived from daily gridded weather observation data (~ 6 × 10 km resolution) covering the central of three adjacent watersheds serving metropolitan Vancouver for the 2020s, 2040s, 2060s and 2080s.

RESULTS

Precipitation is predicted to steadily increase in these watersheds during the wet season (Oct. -Mar.) and decrease in other parts of the year up through the 2080s. More weeks with extreme rain (>90th percentile) are expected. These weeks are predicted to increase the annual rates of cryptosporidiosis and giardiasis by approximately 16% by the 2080s corresponding to an increase of 55-136 additional cases per year depending upon the climate model used. The predicted increase in the number of waterborne illness cases are during the wet months. The range in future projections compared to historical monthly case counts typically differed by 10-20% across climate models but the direction of change was consistent for all models.

DISCUSSION

If new water filtration measures had not been implemented in our study area in 2010-2015, the risk of cryptosporidiosis and giardiasis would have been expected to increase with climate change, particularly precipitation changes. In addition to the predicted increase in the frequency and intensity of extreme precipitation events, the frequency and length of wet and dry spells could also affect the risk of waterborne diseases as we observed in the historical period. These findings add to the growing evidence regarding the need to prepare water systems to manage and become resilient to climate change-related health risks.

Microbiological Contamination of Strawberries from U-Pick Farms in Guangzhou, China

This study quantified the association of rodent fruit damage and the microbiological quality of irrigation water on the risk of microbiological contamination of strawberries collected from 18 U-pick farms across five different districts in the Guangzhou metropolitan region of southern China. Fifty-four composite strawberries samples, with or without evidence of rodent or avian foraging damage (i.e., bitten), along with 16 irrigation water samples, were collected during the spring of 2014 and winter of 2015 from our cohort of 18 farms. Composite strawberry samples and irrigation water were analyzed for total coliforms, E. coli, Salmonella, E. coli O157, Giardia, and Cryptosporidium. Total coliforms and E. coli were detected in 100% and ~90% of irrigation water samples, respectively. In contrast, Cryptosporidium was detected in only two water samples, while Salmonella, E. coli O157, and Giardia were not detected in any water samples. Strawberries with signs of being bitten by wildlife had significantly higher concentrations of total coliforms and E. coli, compared to strawberries with no physical evidence of rodent damage (p < 0.001). Similarly, Cryptosporidium was detected in 7/18 (39%) of bitten, 4/18 (22%) of edge, and 5/18 (28%) of central strawberry samples, respectively. Concentration of E. coli on strawberries (p < 0.001), air temperature (p = 0.025), and presence of Cryptosporidium in irrigation water (p < 0.001) were all associated with the risk of Cryptosporidium contamination on strawberries. Salmonella and Giardia were detected in <4% strawberry samples and E. coli O157 was not detected in any samples. These results indicate the potential food safety and public health risks of consuming unwashed strawberries from U-pick farms, and the need for improved rodent biosecurity of U-pick strawberry fields and enhanced microbiological quality of irrigation water used at these facilities.

Precipitation effects on parasite, indicator bacteria, and wastewater micropollutant loads from a water resource recovery facility influent and effluent

The variability of fecal microorganisms and wastewater micropollutants (WWMPs) loads in relation to influent flow rates was evaluated for a water resource recovery facility (WRRF) in support of a vulnerability assessment of a drinking water source. Incomplete treatment and bypass discharges often occur following intense precipitation events that represent conditions that deviate from normal operation. Parasites, fecal indicator bacteria, and WWMPs concentrations and flow rate were measured at the WRRF influent and effluent during dry and wet weather periods. Influent concentrations were measured to characterize potential bypass concentrations that occur during wet weather. Maximum influent Giardia and C. perfringens loads and maximum effluent Escherichia coli and C. perfringens loads were observed during wet weather. Influent median loads of Cryptosporidium and Giardia were 6.8 log oocysts/day and 7.9 log cysts/day per 1,000 people. Effluent median loads were 3.9 log oocysts/day and 6.3 log cysts/day per 1,000 people. High loads of microbial contaminants can occur during WRRF bypasses following wet weather and increase with increasing flow rates; thus, short-term infrequent events such as bypasses should be considered in vulnerability assessments of drinking water sources in addition to the increased effluent loads during normal operation following wet weather.

Cryptosporidium concentrations in rivers worldwide

Cryptosporidium is a leading cause of diarrhoea and infant mortality worldwide. A better understanding of the sources, fate and transport of Cryptosporidium via rivers is important for effective management of waterborne transmission, especially in the developing world. We present GloWPa-Crypto C1, the first global, spatially explicit model that computes Cryptosporidium concentrations in rivers, implemented on a 0.5 × 0.5° grid and monthly time step. To this end, we first modelled Cryptosporidium inputs to rivers from human faeces and animal manure. Next, we use modelled hydrology from a grid-based macroscale hydrological model (the Variable Infiltration Capacity model). Oocyst transport through the river network is modelled using a routing model, accounting for temperature- and solar radiation-dependent decay and sedimentation along the way. Monthly average oocyst concentrations are predicted to range from 10^-6 to 10² oocysts L^-1 in most places. Critical regions ('hotspots') with high concentrations include densely populated areas in India, China, Pakistan and Bangladesh, Nigeria, Algeria and South Africa, Mexico, Venezuela and some coastal areas of Brazil, several countries in Western and Eastern Europe (incl. The UK, Belgium and Macedonia), and the Middle East. Point sources (human faeces) appears to be a more dominant source of pollution than diffuse sources (mainly animal manure) in most world regions. Validation shows that GloWPa-Crypto medians are mostly within the range of observed concentrations. The model generally produces concentrations that are 1.5-2 log10 higher than the observations. This is likely predominantly due to the absence of recovery efficiency of the observations, which are therefore likely too low. Goodness of fit statistics are reasonable. Sensitivity analysis showed that the model is most sensitive to changes in input oocyst loads. GloWPa-Crypto C1 paves the way for many new opportunities at the global scale, including scenario analysis to investigate the impact of global change and management options on oocysts concentrations in rivers, and risk analysis to investigate human health risk.

Maxent estimation of aquatic Escherichia coli stream impairment

BACKGROUND

The leading cause of surface water impairment in United States' rivers and streams is pathogen contamination. Although use of fecal indicators has reduced human health risk, current approaches to identify and reduce exposure can be improved. One important knowledge gap within exposure assessment is characterization of complex fate and transport processes of fecal pollution. Novel modeling processes can inform watershed decision-making to improve exposure assessment.

METHODS

We used the ecological model, Maxent, and the fecal indicator bacterium Escherichia coli to identify environmental factors associated with surface water impairment. Samples were collected August, November, February, and May for 8 years on Sinking Creek in Northeast Tennessee and analyzed for 10 water quality parameters and E. coli concentrations. Univariate and multivariate models estimated probability of impairment given the water quality parameters. Model performance was assessed using area under the receiving operating characteristic (AUC) and prediction accuracy, defined as the model's ability to predict both true positives (impairment) and true negatives (compliance). Univariate models generated action values, or environmental thresholds, to indicate potential E. coli impairment based on a single parameter. Multivariate models predicted probability of impairment given a suite of environmental variables, and jack-knife sensitivity analysis removed unresponsive variables to elicit a set of the most responsive parameters.

RESULTS

Water temperature univariate models performed best as indicated by AUC, but alkalinity models were the most accurate at correctly classifying impairment. Sensitivity analysis revealed that models were most sensitive to removal of specific conductance. Other sensitive variables included water temperature, dissolved oxygen, discharge, and NO3. The removal of dissolved oxygen improved model performance based on testing AUC, justifying development of two optimized multivariate models; a 5-variable model including all sensitive parameters, and a 4-variable model that excluded dissolved oxygen.

DISCUSSION

Results suggest that E. coli impairment in Sinking Creek is influenced by seasonality and agricultural run-off, stressing the need for multi-month sampling along a stream continuum. Although discharge was not predictive of E. coli impairment alone, its interactive effect stresses the importance of both flow dependent and independent processes associated with E. coli impairment. This research also highlights the interactions between nutrient and fecal pollution, a key consideration for watersheds with multiple synergistic impairments. Although one indicator cannot mimic theplethora of existing pathogens in water, incorporating modeling can fine tune an indicator's utility, providing information concerning fate, transport, and source of fecal pollution while prioritizing resources and increasing confidence in decision making.

Cryptosporidium and Giardia in Wastewater and Surface Water Environments

and spp. are significant contributors to the global waterborne disease burden. Waterways used as sources of drinking water and for recreational activity can become contaminated through the introduction of fecal materials derived from humans and animals. Multiple studies have reported the occurence or concentrations of these pathogens in the environment. However, this information has not been comprehensively reviewed. Quantitative microbial risk assessment (QMRA) for and can be beneficial, but it often relies on the concentrations in environmental sources reported from the literature. A thorough literature review was conducted to develop an inventory of reported and concentrations in wastewater and surface water available in the literature. This information can be used to develop QMRA inputs. and (oo)cyst concentrations in untreated wastewater were up to 60,000 oocysts L and 100,000 cysts L, respectively. The maximum reported concentrations for and in surface water were 8400 oocysts L and 1000 cysts L, respectively. A summary of the factors for interpretation of concentration information including common quantification methods, survival and persistence, biofilm interactions, genotyping, and treatment removal is provided in this review. This information can help in identifying assumptions implicit in various QMRA parameters, thus providing the context and rationale to guide model formulation and application. Additionally, it can provide valuable information for water quality practitioners striving to meet the recreational water quality or treatment criteria. The goal is for the information provided in the current review to aid in developing source water protection and monitoring strategies that will minimize public health risks.

Associations between extreme precipitation and acute gastro-intestinal illness due to cryptosporidiosis and giardiasis in an urban Canadian drinking water system (1997-2009)

Drinking water related infections are expected to increase in the future due to climate change. Understanding the current links between these infections and environmental factors is vital to understand and reduce the future burden of illness. We investigated the relationship between weekly reported cryptosporidiosis and giardiasis (n = 7,422), extreme precipitation (>90th percentile), drinking water turbidity, and preceding dry periods in a drinking water system located in greater Vancouver, British Columbia, Canada (1997-2009) using distributed lag non-linear Poisson regression models adjusted for seasonality, secular trend, and the effect of holidays on reporting. We found a significant increase in cryptosporidiosis and giardiasis 4-6 weeks after extreme precipitation. The effect was greater following a dry period. Similarly, extreme precipitation led to significantly increased turbidity only after prolonged dry periods. Our results suggest that the risk of cryptosporidiosis and giardiasis increases with extreme precipitation, and that the effects are more pronounced after a prolonged dry period. Given that extreme precipitation events are expected to increase with climate change, it is important to further understand the risks from these events, develop planning tools, and build resilience to these future risks.

Contribution of environmental media to cryptosporidiosis and giardiasis prevalence in Tehran: a focus on surface waters

The occurrences of Cryptosporidium and Giardia in surface sources of drinking water in Tehran were monitored, using US EPA method 1623.1. The prevalence ratios (PR) of positive samples among other media (animal's stools, vegetables, and human's stools) were also estimated from literature data. The density of Giardia and Cryptosporidium in water samples were 0.129 ± 0.069 cysts/L and 0.005 ± 0.002 oocysts/L, respectively. Estimated PR in vegetables, animal stools, surface waters, and human stools were 6.65, 20.42, 21.05, and 4.28 % for Cryptosporidium and 6.46, 17.13, 73.68, and 15.65 % for Giardia, respectively. These reveal the importance of surface waters' and animal stools' roles in the prevalence of cryptosporidiosis and giardiasis in Tehran's population. Giardia's prevalence in untreated surface waters in Tehran was found 3.5 times as much as Cryptosporidium while this found 2.3 times on a global scale. Moreover, the prevalence of giardiasis to cryptosporidiosis infections in Tehran's human population was 3.65. These values could be a clue to attribute the infections to the occurrence of parasites in surface waters. Significant (p < 0.05) associations were observed between rainfalls and presence of Giardia (r = 0.62) and Cryptosporidium (r = 0.60) in surface waters. In autumn, rainfalls can increase the parasites occurrences in surface waters. Significant (p < 0.05) difference on the density of parasites was found between some seasons using Kruskal-Wallis and multiple comparison tests. A significant correlation (r = 0.86) between Giardia and Cryptosporidium densities also confirms the common sources of pollution in surface waters. Findings suggest that untreated surface waters in Tehran may be a potential route of human exposure to protozoan parasites.

Occurrence of Cryptosporidium oocysts and Giardia cysts in raw waters in Norway

Aims: This paper reports the first investigation into the occurrence of Cryptosporidium and Giardia in Norwegian raw water sources. Methods: Between June 1998 and October 1999, 408 raw water samples, collected from 147 different sites across Norway, were analysed for these parasites. Analysis was based upon US EPA Method 1623. Results: In 305 samples (75%), parasites were not detected. In 55 samples (13.5%), Cryptosporidium only was detected. In 38 samples (9%), Giardia only was detected. In 10 samples (2.5%) both Cryptosporidium and Giardia were detected. Of the sites sampled, parasites were not detected at 100 (68%) of them, Cryptosporidium only was detected at 20 (13.5%), Giardia only was detected at 11 (7.5%), and both Cryptosporidium and Giardia were detected at 16 (11%). Concentrations of parasites were low; usually one cyst/ oocyst detected per 10 litres of water. Conclusions: Significant associations were demonstrated for these samples between the detection of these parasites and (a) turbidity ≥2.0 NTU, and (b) high numbers of domestic animals within the catchment area. No association between seasonality and the occurrence of these parasites could be detected. The results are discussed in relation to other studies and the potential public health implications for Norway.

Post-industrial river water quality-Fit for bathing again?

For the Ruhr River, bathing has been prohibited for decades. However, along with significant improvements of the hygienic water quality, there is an increasing demand of using the river for recreational purposes, in particular for bathing. In the "Safe Ruhr" interdisciplinary research project, demands, options and chances for lifting the bathing ban for the Ruhr River were investigated. As being the prominent reason for persisting recreational restrictions, microbiological water quality was in the focus of interest. Not only the faecal indicator organisms (FIOs) as required by the European Bathing Water Directive were considered, but also pathogens such as Salmonella, Pseudomonas aeruginosa, Legionella pneumophila, Campylobacter, Leptospira, enteroviruses and protozoan parasites. In this introductory paper, we firstly relate current recreational desires to historical experiences of river bathing. After recapitulating relevant microbial river contamination sources (predominantly sewage treatment plants, combined sewer overflows, and surface runoffs), we review existing knowledge about the relationships of FIOs and pathogens in rivers designated for recreational purposes, and then trace the evolution, rationale and validity of recreational freshwater quality criteria which are, despite obvious uncertainties, mostly relying on the FIO paradigm. In particular, the representativeness of FIOs is critically discussed. The working programme of Safe Ruhr, aiming at initiating and facilitating a process towards legalisation of Ruhr River bathing, is outlined. Sources of contamination can be technically handled which leaves the actual measures to political decisions. As contaminations are transient, only occasionally exceeding legal limits, a flexible bathing site management, warning bathers of non-safe situations, may amend technical interventions and offer innovative solutions. As a result, a situation-adapted system for lifting of the bathing ban for Ruhr River appears realistic.

Boiling over: A Descriptive Analysis of Drinking Water Advisories in First Nations Communities in Ontario, Canada

Access to safe and reliable drinking water is commonplace for most Canadians. However, the right to safe and reliable drinking water is denied to many First Nations peoples across the country, highlighting a priority public health and environmental justice issue in Canada. This paper describes trends and characteristics of drinking water advisories, used as a proxy for reliable access to safe drinking water, among First Nations communities in the province of Ontario. Visual and statistical tools were used to summarize the advisory data in general, temporal trends, and characteristics of the drinking water systems in which advisories were issued. Overall, 402 advisories were issued during the study period. The number of advisories increased from 25 in 2004 to 75 in 2013. The average advisory duration was 294 days. Most advisories were reported in summer months and equipment malfunction was the most commonly reported reason for issuing an advisory. Nearly half of all advisories occurred in drinking water systems where additional operator training was needed. These findings underscore that the prevalence of drinking water advisories in First Nations communities is a problem that must be addressed. Concerted and multi-faceted efforts are called for to improve the provision of safe and reliable drinking water First Nations communities.

The effects of combined sewer overflow events on riverine sources of drinking water

This study was set out to investigate the impacts of Combined Sewer Overflows (CSOs) on the microbiological water quality of a river used as a source of drinking water treatment plants. Escherichia coli concentrations were monitored at various stations of a river segment located in the Greater Montreal Area including two Drinking Water Intakes (DWIs) in different weather conditions (dry weather and wet weather (precipitation and snowmelt period)). Long-term monitoring data (2002-2011) at DWIs revealed good microbiological water quality with E. coli median concentrations of 20 and 30 CFU/100 mL for DWI-1 and DWI-2 respectively. However, E. coli concentration peaks reached up to 510 and 1000 CFU/100 mL for both DWIs respectively. Statistical Process Control (SPC) analysis allowed the identification of E. coli concentration peaks in almost a decade of routine monitoring data at DWIs. Almost 80% of these concentrations were linked to CSO discharges caused by precipitation exceeding 10 mm or spring snowmelt. Dry weather monitoring confirmed good microbiological water quality. Wet weather monitoring showed an increase of approximately 1.5 log of E. coli concentrations at DWIs. Cumulative impacts of CSO discharges were quantified at the river center with an increase of approximately 0.5 log of E. coli concentrations. Caffeine (CAF) was tested as a potential chemical indicator of CSO discharges in the river and CAF concentrations fell within the range of previous measurements performed for surface waters in the same area (∼20 ng/L). However, no significant differences were observed between CAF concentrations in dry and wet weather, as the dilution potential of the river was too high. CSO event based monitoring demonstrated that current bi-monthly or weekly compliance monitoring at DWIs underestimate E. coli concentrations entering DWIs and thus, should not be used to quantify the risk at DWIs. High frequency event-based monitoring is a desirable approach to establish the importance and duration of E. coli peak concentrations entering DWIs.

Quantitative analysis of burden of bacillary dysentery associated with floods in Hunan, China

BACKGROUND

Jishou and Huaihua, two cities in the west of Hunan Province, had suffered from severe floods because of long-lasting and heavy rainfall during the end of June and July 2012. However, the Disability Adjusted of Life Years (DALYs) of bacillary dysentery caused by the floods have not been examined before. The study aimed to quantify the impact of the floods on the burden of bacillary dysentery in Hunan, China.

METHODS

A unidirectional case-crossover study was firstly conducted to determine the relationship between daily cases of bacillary dysentery and the floods in Jishou and Huaihua of Hunan Province in 2012. Odds ratios (ORs) estimated by conditional logistic regression were used to quantify the risk of the floods on the disease. The years lived with disability (YLDs) of bacillary dysentery attributable to floods were then estimated based on the WHO framework to calculate potential impact fraction in the Burden of Disease study.

RESULTS

Multivariable analysis showed that floods were significantly associated with an increased risk of the number of cases of bacillary dysentery (OR=3.270, 95% CI: 1.299-8.228 in Jishou; OR=2.212, 95% CI: 1.052-4.650 in Huaihua). The strongest effect was shown with a 1-day lag in Jishou and a 4-day lag in Huaihua. Attributable YLD per 1000 of bacillary dysentery due to the floods was 0.0296 in Jishou and 0.0157 in Huaihua.

CONCLUSIONS

Our study confirms that floods have significantly increased the risks of bacillary dysentery in the study areas. In addition, a sudden and severe flooding with a shorter duration may cause more burdens of bacillary dysentery than a persistent and moderate flooding. Public health preparation and intervention programs should be taken to reduce and prevent a potential risk of bacillary dysentery epidemics after floods.

A descriptive analysis of the spatio-temporal distribution of enteric diseases in New Brunswick, Canada

Background

Enteric diseases affect thousands of Canadians annually and several large outbreaks have occurred due to infection with enteric pathogens. The objectives of this study were to describe the spatial and temporal distributions of reportable Campylobacter, Escherichia coli, Giardia, Salmonella and Shigella from 1994 to 2002 in New Brunswick, Canada. By examining the spatial and temporal distributions of disease incidence, hypotheses as to potential disease risk factors were formulated.

Methods

Time series plots of monthly disease incidence were examined for seasonal and secular trends. Seasonality of disease incidence was evaluated using the temporal scan statistic and seasonal–trend loess (STL) decomposition methods. Secular trends were evaluated using negative binomial regression modeling. The spatial distribution of disease incidence was examined using maps of empirical Bayes smoothed estimates of disease incidence. Spatial clustering was examined by multiple methods, which included Moran’s I and the spatial scan statistic.

Results

The peak incidence of Giardia infections occurred in the spring months. Salmonella incidence exhibited two peaks, one small peak in the spring and a main peak in the summer. Campylobacter and Escherichia coli O157 disease incidence peaked in the summer months. Moran’s I indicated that there was significant positive spatial autocorrelation for the incidence of Campylobacter, Giardia and Salmonella. The spatial scan statistic identified clusters of high disease incidence in the northern areas of the province for Campylobacter, Giardia and Salmonella infections. The incidence of Escherichia coli infections clustered in the south-east and north-east areas of the province, based on the spatial scan statistic results. Shigella infections had the lowest incidence rate and no discernable spatial or temporal patterns were observed.

Conclusions

By using several different spatial and temporal methods a robust picture of the spatial and temporal distributions of enteric disease in New Brunswick was produced. Disease incidence for several reportable enteric pathogens displayed significant geographic clustering indicating that a spatially distributed risk factor may be contributing to disease incidence. Temporal analysis indicated peaks in disease incidence, including previously un-reported peaks.

The impact of meteorology on the occurrence of waterborne outbreaks of vero cytotoxin-producing Escherichia coli (VTEC): a logistic regression approach

This study analyses the relationship between meteorological phenomena and outbreaks of waterborne-transmitted vero cytotoxin-producing Escherichia coli (VTEC) in the Republic of Ireland over an 8-year period (2005-2012). Data pertaining to the notification of waterborne VTEC outbreaks were extracted from the Computerised Infectious Disease Reporting system, which is administered through the national Health Protection Surveillance Centre as part of the Health Service Executive. Rainfall and temperature data were obtained from the national meteorological office and categorised as cumulative rainfall, heavy rainfall events in the previous 7 days, and mean temperature. Regression analysis was performed using logistic regression (LR) analysis. The LR model was significant (p < 0.001), with all independent variables: cumulative rainfall, heavy rainfall and mean temperature making a statistically significant contribution to the model. The study has found that rainfall, particularly heavy rainfall in the preceding 7 days of an outbreak, is a strong statistical indicator of a waterborne outbreak and that temperature also impacts waterborne VTEC outbreak occurrence.

Developing an easy-to-apply model for identifying relevant pathogen pathways into surface waters used for recreational purposes

Swimming in inner-city surface waters is popular in the warm season, but can have negative consequences such as gastro-intestinal, ear and skin infections. The pathogens causing these infections commonly enter surface waters via several point source discharges such as the effluents from wastewater treatment plants and sewer overflows, as well as through diffuse non-point sources such as surface runoff. Nonetheless, the recreational use of surface waters is attractive for residents. In order to save financial and organizational resources, local authorities need to estimate the most relevant pathways of pathogens into surface waters. In particular, when detailed data on a local scale are missing, this is quite difficult to achieve. For this reason, we have developed an easy-to-apply model using the example of Escherichia coli and intestinal enterococci as a first approach to the local situation, where missing data can be replaced by data from literature. The model was developed based on a case study of a river arm monitored in western Germany and will be generalized for future applications. Although the limits of the EU Bathing Water Directive are already fulfilled during dry weather days, we showed that the effluent of wastewater treatment plants and overland flow had the most relevant impact on the microbial surface water quality. On rainy weather days, combined sewer overflows are responsible for the highest microbial pollution loads. The results obtained in this study can help decision makers to focus on reducing the relevant pathogen sources within a catchment area.

Fine-Scale Spatial Heterogeneity in the Distribution of Waterborne Protozoa in a Drinking Water Reservoir

Background: The occurrence of faecal pathogens in drinking water resources constitutes a threat to the supply of safe drinking water, even in industrialized nations. To efficiently assess and monitor the risk posed by these pathogens, sampling deserves careful design, based on preliminary knowledge on their distribution dynamics in water. For the protozoan pathogens Cryptosporidium and Giardia, only little is known about their spatial distribution within drinking water supplies, especially at fine scale. Methods: Two-dimensional distribution maps were generated by sampling cross-sections at meter resolution in two different zones of a drinking water reservoir. Samples were analysed for protozoan pathogens as well as for E. coli, turbidity and physico-chemical parameters. Results: Parasites displayed heterogeneous distribution patterns, as reflected by significant (oo)cyst density gradients along reservoir depth. Spatial correlations between parasites and E. coli were observed near the reservoir inlet but were absent in the downstream lacustrine zone. Measurements of surface and subsurface flow velocities suggest a role of local hydrodynamics on these spatial patterns. Conclusion: This fine-scale spatial study emphasizes the importance of sampling design (site, depth and position on the reservoir) for the acquisition of representative parasite data and for optimization of microbial risk assessment and monitoring. Such spatial information should prove useful to the modelling of pathogen transport dynamics in drinking water supplies.

A systematic review and meta-analysis of the effects of extreme weather events and other weather-related variables on Cryptosporidium and Giardia in fresh surface waters

Global climate change is expected to impact drinking water quality through multiple weather-related phenomena. We conducted a systematic review and meta-analysis of the relationship between various weather-related variables and the occurrence and concentration of Cryptosporidium and Giardia in fresh surface waters. We implemented a comprehensive search in four databases, screened 1,228 unique citations for relevance, extracted data from 107 relevant articles, and conducted random-effects meta-analysis on 16 key relationships. The average odds of identifying Cryptosporidium oocysts and Giardia cysts in fresh surface waters was 2.61 (95% CI = 1.63-4.21; I² = 16%) and 2.87 (95% CI = 1.76-4.67; I² = 0%) times higher, respectively, during and after extreme weather events compared to baseline conditions. Similarly, the average concentration of Cryptosporidium and Giardia identified under these conditions was also higher, by approximately 4.38 oocysts/100 L (95% CI = 2.01-9.54; I(2) = 0%) and 2.68 cysts/100 L (95% CI = 1.08-6.55; I² = 48%). Correlation relationships between other weather-related parameters and the density of these pathogens were frequently heterogeneous and indicated low to moderate effects. Meta-regression analyses identified different study-level factors that influenced the variability in these relationships. The results can be used as direct inputs for quantitative microbial risk assessment. Future research is warranted to investigate these effects and potential mitigation strategies in different settings and contexts.

Precipitation increases the occurrence of sporadic legionnaires' disease in Taiwan

Legionnaires' disease (LD) is an acute form of pneumonia, and changing weather is considered a plausible risk factor. Yet, the relationship between weather and LD has rarely been investigated, especially using long-term daily data. In this study, daily data was used to evaluate the impacts of precipitation, temperature, and relative humidity on LD occurrence in Taiwan from 1995-2011. A time-stratified 2:1 matched-period case-crossover design was used to compare each case with self-controlled data using a conditional logistic regression analysis, and odds ratios (ORs) for LD occurrence was estimated. The city, gender and age were defined as a stratum for each matched set to modify the effects. For lag day- 0 to 15, the precipitation at lag day-11 significantly affected LD occurrence (p<0.05), and a 2.5% (95% CIs = 0.3-4.7%) increased risk of LD occurrence was associated with every 5-mm increase in precipitation. In addition, stratified analyses further showed that positive associations of precipitation with LD incidence were only significant in male and elderly groups and during the warm season ORs = 1.023-1.029). However, such an effect was not completely linear. Only precipitations at 21-40 (OR = 1.643 (95% CIs = 1.074-2.513)) and 61-80 mm (OR = 2.572 (1.106-5.978)) significantly increased the risk of LD occurrence. Moreover, a negative correlation between mean temperature at an 11-day lag and LD occurrence was also found (OR = 0.975 (0.953-0.996)). No significant association between relative humidity and LD occurrence was identified (p>0.05). In conclusion, in warm, humid regions, an increase of daily precipitation is likely to be a critical weather factor triggering LD occurrence where the risk is found particularly significant at an 11-day lag. Additionally, precipitation at 21-40 and 61-80 mm might make LD occurrence more likely.

Changes in Escherichia coli to Cryptosporidium ratios for various fecal pollution sources and drinking water intakes

Assessing the presence of human pathogenic Cryptosporidium oocysts in surface water remains a significant water treatment and public health challenge. Most drinking water suppliers rely on fecal indicators, such as the well-established Escherichia coli (E. coli), to avoid costly Cryptosporidium assays. However, the use of E. coli has significant limitations in predicting the concentration, the removal and the transport of Cryptosporidium. This study presents a meta-analysis of E. coli to Cryptosporidium concentration paired ratios to compare their complex relationships in eight municipal wastewater sources, five agricultural fecal pollution sources and at 13 drinking water intakes (DWI) to a risk threshold based on US Environmental Protection Agency (USEPA) regulations. Ratios lower than the USEPA risk threshold suggested higher concentrations of oocysts in relation to E. coli concentrations, revealing an underestimed risk for Cryptosporidium based on E. coli measurements. In raw sewage (RS), high ratios proved E. coli (or fecal coliforms) concentrations were a conservative indicator of Cryptosporidium concentrations, which was also typically true for secondary treated wastewater (TWW). Removals of fecal indicator bacteria (FIB) and parasites were quantified in WWTPs and their differences are put forward as a plausible explanation of the sporadic ratio shift. Ratios measured from agricultural runoff surface water were typically lower than the USEPA risk threshold and within the range of risk misinterpretation. Indeed, heavy precipitation events in the agricultural watershed led to high oocyst concentrations but not to E. coli or enterococci concentrations. More importantly, ratios established in variously impacted DWI from 13 Canadian drinking water plants were found to be related to dominant fecal pollution sources, namely municipal sewage. In most cases, when DWIs were mainly influenced by municipal sewage, E. coli or fecal coliforms concentrations agreed with Cryptosporidium concentrations as estimated by the meta-analysis, but when DWIs were influenced by agricultural runoff or wildlife, there was a poor relationship. Average recovery values were available for 6 out of 22 Cryptosporidium concentration data sets and concomitant analysis demonstrated no changes in trends, with and without correction. Nevertheless, recovery assays performed along with every oocyst count would have enhanced the precision of this work. Based on our findings, the use of annual averages of E. coli concentrations as a surrogate for Cryptosporidium concentrations can result in an inaccurate estimate of the Cryptosporidium risk for agriculture impacted drinking water intakes or for intakes with more distant wastewater sources. Studies of upstream fecal pollution sources are recommended for drinking water suppliers to improve their interpretation of source water quality data.

Leaching of Escherichia coli from sheep faeces during simulated rainfall events

Sheep faeces are known to harbour to a high concentration of microbial indicators and pathogens. These can be released under rainfall and may result in contamination of waterways, potentially leading to illnesses in humans. A study was designed to determine the concentration of Escherichia coli released from fresh and aged (0-21 days old) ovine faeces. In summer and autumn, ovine faeces were subjected to simulated rainfall and the resultant run-off collected. Escherichia coli were enumerated in both the run-off and the faeces. In autumn total suspended solids (TSS) and turbidity were also monitored in the run-off. This study provides quantitative evidence that E. coli in aged sheep faeces is mobilized by rainfall events. Simulated rainfall events released between 10(3) and 10(4) CFU E. coli ml(-1) throughout the 21 days. TSS or turbidity with fresh faeces may be indicative of microbial contamination, but from aged faeces, this may not be the case.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study confirms that faecal bacteria can be released from fresh and aged ovine faeces under stimulated rainfall. It demonstrates that aged faeces remain a source of faecal bacteria, which under rainfall can release the bacteria and result in pollution of waterways. This study aids in our understanding of the potential impact of grazing sheep on the microbial quality of surface waters in NZ.

Spatial and temporal distribution of Cryptosporidium and Giardia in a drinking water resource: implications for monitoring and risk assessment

Because of their significant public health impact, waterborne Cryptosporidium and Giardia have been monitored in surface water in order to assess microbial quality of water bodies used for drinking water production and/or for recreational purposes. In this context, sampling strategy is of key importance and should be representative enough to appropriately assess the related microbial risk. This, however, requires sound knowledge on the behaviour of both pathogens in water. In the present study, the spatial and temporal distribution of Cryptosporidium and Giardia was explored in the rural Upper-Sûre watershed used for drinking water production in Luxembourg. By subdividing it into three compartments including (i) sub-catchments, (ii) the Sûre River fed by the sub-catchments and (iii) the Upper-Sûre reservoir fed by the Sûre River, parasite distribution was assessed using sampling designs adapted to the hydro-dynamic characteristics of the respective compartments. Results highlighted the high spatial and temporal variability in parasite distribution at watershed scale, as well as the prevalence of Giardia over Cryptosporidium. Besides land use features and catchment characteristics, hydro-climatology appeared to be a major driver of parasite behaviour in the watershed. It introduced a seasonal trend in their occurrence, highest densities being detected during the wet season. Peaks of contamination triggered out by rainfall-induced runoff were further observed in the three compartments. In the Sûre River, Cryptosporidium and Giardia fluxes peaked at 10(9) and 10(10) (oo)cysts.d(-1), respectively, and were discharged into the drinking water reservoir, where they underwent a 2 to 3 log10 removal rate. Despite this, parasite fluxes entering the drinking water treatment plant were still high (10(6) to 10(7) (oo)cysts.d(-1)) and stressed on the need for improved watershed management upstream the water treatment barrier. The catchment-wide analysis described here constitutes a valuable tool for assessment of catchment microbial dynamics, especially within the framework of Water Safety Plans.