A rapid on-site loop-mediated isothermal amplification technology as an early warning system for the detection of Shiga toxin-producing Escherichia coli in water.

Shiga toxin-producing Escherichia coli (STEC) is an important waterborne pathogen capable of causing serious gastrointestinal infections with potentially fatal complications, including haemolytic-uremic syndrome. All STEC serogroups harbour genes that encode at least one Shiga toxin (stx1 and/or stx2), which constitute the primary virulence factors of STEC. Loop-mediated isothermal amplification (LAMP) enables rapid real-time pathogen detection with a high degree of specificity and sensitivity. The aim of this study was to develop and validate an on-site portable diagnostics workstation employing LAMP technology to permit rapid real-time STEC detection in environmental water samples. Water samples (n=28) were collected from groundwater wells (n=13), rivers (n=12), a turlough (n=2) and an agricultural drain (n=1) from the Corrib catchment in Galway. Water samples (100 ml) were passed through a 0.22 µm filter, and buffer was added to elute captured cells. Following filtration, eluates were tested directly using LAMP assays targeting stx1, stx2 and E. coli phoA genes. The portable diagnostics workstation was used in field studies to demonstrate the on-site testing capabilities of the instrument. Real-time PCR assays targeting stx1 and stx2 genes were used to confirm the results. The limit of detection for stx1, stx2 and phoA LAMP assays were 2, 2 and 6 copies, respectively. Overall, stx1, stx2 and phoA genes were detected by LAMP in 15/28 (53.6 %), 9/28 (32.2 %) and 24/28 (85.7 %) samples, respectively. For confirmation, the LAMP results for stx1 and stx2 correlated perfectly (100 %) with those obtained using PCR. The portable diagnostics workstation exhibited high sensitivity throughout the on-site operation, and the average time from sample collection to final result was 40 min. We describe a simple, transferable and efficient diagnostic technology for on-site molecular analysis of various water sources. This method allows on-site testing of drinking water, enabling evidence-based decision-making by public health and water management authorities.

Behavioral pathways to private well risk mitigation: A structural equation modeling approach.

Complex, multihazard risks such as private groundwater contamination necessitate multiannual risk reduction actions including seasonal, weather-based hazard evaluations. In the Republic of Ireland (ROI), high rural reliance on unregulated private wells renders behavior promotion a vital instrument toward safeguarding household health from waterborne infection. However, to date, pathways between behavioral predictors remain unknown while latent constructs such as extreme weather event (EWE) risk perception and self-efficacy (perceived behavioral competency) have yet to be sufficiently explored. Accordingly, a nationwide survey of 560 Irish private well owners was conducted, with structural equation modeling (SEM) employed to identify underlying relationships determining key supply management behaviors. The pathway analysis (SEM) approach was used to model three binary outcomes: information seeking, post-EWE action, and well testing behavior. Upon development of optimal models, perceived self-efficacy emerged as a significant direct and/or indirect driver of all three behavior types-demonstrating the greatest indirect effect (ß = -0.057) on adoption of post-EWE actions and greatest direct (ß = 0.222) and total effect (ß = 0.245) on supply testing. Perceived self-efficacy inversely influenced EWE risk perception in all three models but positively influenced supply awareness (where present). Notably, the presence of a vulnerable (infant and/or elderly) household member negatively influenced adoption of post-EWE actions (ß = -0.131, p = 0.016). Results suggest that residential and age-related factors constitute key demographic variables influencing risk mitigation and are strongly mediated by cognitive variables-particularly self-efficacy. Study findings may help contextualize predictors of private water supply management, providing a basis for future risk-based water interventions.

Spatiotemporal Dynamics of Sporadic Shiga Toxin-Producing Escherichia coli Enteritis, Ireland, 2013-2017.

The Republic of Ireland regularly reports the highest annual crude incidence rates of Shiga toxin-producing Escherichia coli (STEC) enteritis in the European Union, ≈10 times the average. We investigated spatiotemporal patterns of STEC enteritis in Ireland using multiple statistical tools. Overall, we georeferenced 2,755 cases of infection during January 2013-December 2017; we found >1 case notified in 2,340 (12.6%) of 18,641 Census Small Areas. We encountered the highest case numbers in children 0-5 years of age (n = 1,101, 39.6%) and associated with serogroups O26 (n = 800, 29%) and O157 (n = 638, 23.2%). Overall, we identified 17 space-time clusters, ranging from 2 (2014) to 5 (2017) clusters of sporadic infection per year; we detected recurrent clustering in 3 distinct geographic regions in the west and mid-west, all of which are primarily rural. Our findings can be used to enable targeted epidemiologic intervention and surveillance.

Planning for the health impacts of climate change: Flooding, private groundwater contamination and waterborne infection - A cross-sectional study of risk perception, experience and behaviours in the Republic of Ireland.

The frequency and severity of flooding events will increase over the coming decades due to global climate change. While close attention has typically been paid to infrastructural and environmental outcomes of flood events, the potential adverse human health consequences associated with post-event consumption from private groundwater sources have received minimal attention, leading to a poor understanding of private well users' preparedness and the drivers of positive behavioural adoption. The current study sought to quantify the capacity of private well users to cope with flood-triggered contamination risks and identify the social psychological determinants of proactive attitudes in the Republic of Ireland, using a cross-sectional questionnaire incorporating two distinct models of health behaviour, the Health Belief Model and Risk-Attitude-Norms-Ability-Self Regulation model. Adoption of healthy behaviours prior to flooding was evaluated with respect to respondents' risk exposure, risk experience and risk perception, in addition to systematic supply stewardship under normal conditions. Associations between adoption of protective behaviours and perception, experience and socio-demographic factors were evaluated through multinomial and multiple logistic regressions, while a multi-model inferential approach was employed with the predictors of health behaviour models. Findings suggest that floods are not considered likely to occur, nor were respondents worried about their occurrence, with 72.5% of respondents who reported previous flooding experience failing to adopt protective actions. Prior experience of well water contamination increased adoption of proactive attitudes when flooding occurred (+47%), with a failure to adopt healthy behaviours higher among rural non-agricultural residents (136%). Low levels of preparedness to deal with flood-related contamination risks are a side-effect of the general lack of appropriate well stewardship under normal conditions; just 10.1% of respondents adopted both water treatment and frequent testing, in concurrence with limited risk perception and poor awareness of the nexus between risk factors (e.g. floods, contamination sources) and groundwater quality. Perceived risk, personal norms and social norms were the best predictors of protective behaviour adoption and should be considered when developing future awareness campaigns.

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.

Microbiological assessment of private groundwater-derived potable water supplies in the Mid-West Region of Ireland.

Determining the likelihood that groundwater contains faecal coliforms can aid water resource management in facilitating the protection of drinking water supplies. This study assesses the incidence of the faecal indicator organism Escherichia coli in 125 private water supplies (PWSs) serving individual houses in the Mid-West Region of Ireland. Two factors, aquifer type and rainfall (mm), were chosen as independent variables that can affect the vulnerability of a groundwater body. Using a geographical information system, the relative hydrogeological and climatological features unique to each sampling location were derived. Utilising this information, a logistic regression (LR) model was used to predict the probability of contamination of PWSs with E. coli. The model contained two independent variables: rainfall (mm; p < 0.001) and aquifer characteristics (p = 0.001). The full model, containing both predictors, was statistically significant at p < 0.001, indicating that the model distinguished between the independent variables' relationship to the incidence of contamination. The likelihood of E. coli contamination is greater with increased rainfall and in areas where a bedrock aquifer is dominant. The LR model explained between 27.4% (Cox and Snell R squared) and 36.8% (Nagelkerke R squared) of the variance in contamination and correctly classified 75.2% of cases.

An ecological study of the spatiotemporal dynamics and drivers of domestically acquired campylobacteriosis in Ireland, 2011-2018.

In 2021, Campylobacteriosis was the main gastrointestinal disease in the European Union since 2007 according to the European Centre for Disease Prevention and Control. In the Republic of Ireland, the incidence of the disease is particularly high with approximately 3,000 cases per annum, raising significant concerns for national health authorities with an expected increase in the number of cases in the light of climate change. The current study sought to assess the spatio-temporal patterns of campylobacteriosis in the Republic of Ireland using 20,391 cases from January 2011 to December 2018. An ensemble of spatial statistics techniques including seasonal decomposition, spatial clustering and space-time scanning, were used to elucidate the main individual and spatio-temporal characteristics of the disease in the country. Findings revealed that cases from the paediatric age group (i.e., under 5 years old) were more likely to occur in rural areas (aOR: 1.1.27, CI 95% 1.14-1.41) while cases from the intermediate age group (i.e., >5 & <65 years old) were associated with urban living (aOR: 1.30, CI 95% 1.21-1.4). The disease exhibited a peak during Irish summer, with a stronger seasonal signal reported in counties located on the Western part of the country. Infection hotspots were more likely to occur in urban areas, and more particularly on the Southern part of the island and around the main metropolitan areas. Overall, research findings pointed out the influence of local and spatio-temporally specific socio-demographic and environmental risk factors (i.e., cooking habits, local weather, dietary types) therefore highlighting the need for initiating spatio-temporally targeted health management and surveillance strategies.

The antimicrobial resistance profiles of Escherichia coli and Pseudomonas aeruginosa isolated from private groundwater wells in the Republic of Ireland.

The role of the natural environment in the dissemination of antimicrobial resistant bacteria has been increasingly recognised in the literature. However, knowledge surrounding the critical factors and mechanisms mediating their occurrence is still limited, particularly in relatively 'pristine' groundwater environments. In the Republic of Ireland (RoI), a country characterised by high groundwater reliance, household-based (unregulated) wells provide drinking water to 11% of the population. These private wells are generally located in rural areas, where the risk of microbiological contamination is high due to intensive agricultural practices and high reliance on domestic wastewater treatment systems; both of which are also potential sources of antimicrobials and antimicrobial resistant bacteria. Accordingly, the current research sought to elucidate current rates of antimicrobial resistant bacteria and the principal factors associated with their presence in private wells in the RoI. A total of 250 samples (from 132 wells nationwide) were assessed for the presence of faecal (Escherichia coli) and environmental (Pseudomonas aeruginosa) bacteria, with single isolates from each contaminated sample tested phenotypically against 18 and 9 antimicrobials, respectively. Findings show that while 16.7% of E. coli (n = 8/48) were categorically resistant to ≥1 antimicrobial, with a further 79.2% classified as intermediately resistant, no categorical resistance was found among P. aeruginosa isolates (n = 0/6), with just one intermediately resistant isolate detected. Multivariate regression modelling indicates significantly higher odds of resistant E. coli detection in concurrence with elevated cattle density (OR = 1.028, p = 0.032), aligning with findings of highest resistance rates to veterinary antimicrobials (e.g., streptomycin = 14.6%, tetracycline = 12.5%, and ampicillin = 12.5%). Multivariate model results also suggest overland flow culminating in direct wellhead ingress as a primary ingress mechanism for resistant E. coli. Study findings may inform groundwater source protection initiatives and antimicrobial resistance surveillance moving forward.

Assessing antimicrobial and metal resistance genes in Escherichia coli from domestic groundwater supplies in rural Ireland.

Natural ecosystems can become significant reservoirs and/or pathways for antimicrobial resistance (AMR) dissemination, with the potential to affect nearby microbiological, animal, and ultimately human communities. This is further accentuated in environments that provide direct human exposure, such as drinking water. To date, however, few studies have investigated AMR dissemination potential and the presence of co-selective stressors (e.g., metals/metalloids) in groundwater environments of human health significance. Accordingly, the present study analysed samples from rural (drinking) groundwater supplies (i.e., private wells) in the Republic of Ireland, where land use is dominated by livestock grazing activities. In total, 48 Escherichia coli isolates tested phenotypically for antimicrobial susceptibility in an earlier study were further subject to whole genome sequencing (WGS) and corresponding water samples were further analysed for trace metal/metalloid concentrations. Eight isolates (i.e., 16.7%) were genotypically resistant to antimicrobials, confirming prior phenotypic results through the identification of ten antimicrobial resistance genes (ARGs); namely: aph(3″)-lb (strA; n=7), aph(6)-Id (strA; n = 6), blaTEM (n = 6), sul2 (n = 6), tetA (n = 4), floR (n = 2), dfrA5 (n = 1), tetB (n = 1), and tetY (n = 1). Additional bioinformatic analysis revealed that all ARGs were plasmid-borne, except for two of the six sul2 genes, and that 31.2% of all tested isolates (n = 15) and 37.5% of resistant ones (n = 3) carried virulence genes. Study results also found no significant relationships between metal concentrations and ARG abundance. Additionally, just one genetic linkage was identified between ARGs and a metal resistance gene (MRG), namely merA, a mercury-resistant gene found on the same plasmid as blaTEM, dfrA5, strA, strB, and sul2 in the only isolate of inferred porcine (as opposed to bovine) origin. Overall, findings suggest that ARG (and MRG) acquisition may be occurring prior to groundwater ingress, and are likely a legacy issue arising from agricultural practices.

Fluorescent Dissolved Organic Matter Components as Surrogates for Disinfection Byproduct Formation in Drinking Water: A Critical Review.

Disinfection byproduct (DBP) formation, prediction, and minimization are critical challenges facing the drinking water treatment industry worldwide where chemical disinfection is required to inactivate pathogenic microorganisms. Fluorescence excitation-emission matrices-parallel factor analysis (EEM-PARAFAC) is used to characterize and quantify fluorescent dissolved organic matter (FDOM) components in aquatic systems and may offer considerable promise as a low-cost optical surrogate for DBP formation in treated drinking waters. However, the global utility of this approach for quantification and prediction of specific DBP classes or species has not been widely explored to date. Hence, this critical review aims to elucidate recurring empirical relationships between common environmental fluorophores (identified by PARAFAC) and DBP concentrations produced during water disinfection. From 45 selected peer-reviewed articles, 218 statistically significant linear relationships (R2 ≥ 0.5) with one or more DBP classes or species were established. Trihalomethanes (THMs) and haloacetic acids (HAAs), as key regulated classes, were extensively investigated and exhibited strong, recurrent relationships with ubiquitous humic/fulvic-like FDOM components, highlighting their potential as surrogates for carbonaceous DBP formation. Conversely, observed relationships between nitrogenous DBP classes, such as haloacetonitriles (HANs), halonitromethanes (HNMs), and N-nitrosamines (NAs), and PARAFAC fluorophores were more ambiguous, but preferential relationships with protein-like components in the case of algal/microbial FDOM sources were noted. This review highlights the challenges of transposing site-specific or FDOM source-specific empirical relationships between PARAFAC component and DBP formation potential to a global model.

Characterization of Shiga toxin-producing Escherichia coli presence, serogroups and risk factors from private groundwater sources in western Ireland.

Over recent years, Ireland has reported the highest crude incidence rates of Shiga toxin-producing Escherichia coli (STEC) enteritis in Europe. Unregulated private groundwater sources have emerged as an important potential transmission route for STEC, with up to 750,000 Irish residents reliant on these sources for domestic waters. This study aimed to investigate the prevalence and serogroup profile of STEC contamination from domestic private wells in western Ireland. Fifty-two groundwater sources were analysed during two sampling campaigns in the autumn (September/October) of 2019 (n = 21) and 2021 (n = 31). Untreated groundwater samples (30 L) were collected and analysed using the "CapE" (capture, amplify, extract) method. Extracted DNA was tested using multiplex real-time PCR for Shiga toxin stx1 and/or stx2 and eae genes. STEC positive DNA samples were tested for clinically relevant serogroups by real-time PCR. Data relating to 27 potential groundwater contamination risk factors were geospatially linked to each well and assessed for association with E. coli, stx1 and/or stx2 and eae presence/absence. Overall, 20/52 wells (38.4 %) were positive for E. coli (median concentration 8.5 MPN/100 mL as assessed by Colilert-18 method). Stx1 and/or stx2 was detected in 10/52 (19.2 %) wells overall and 8/20 E. coli positive wells, equating to a STEC to "generic" E. coli detection ratio of 40 %. Six of these wells (30 %) were also positive for eae. One or more serogroup-specific gene targets were identified in all but one stx1 and/or stx2 positive sample, with O145 (n = 6), O157 (n = 5) and O103 (n = 4) most prevalent. STEC presence was significantly associated with decreasing well depth (U = -2.243; p = 0.024) and increasing 30-day mean antecedent rainfall (U = 2.126; p = 0.034). Serogroup O104 was associated with increased sheep density (U = 2.089; p = 0.044) and detection of stx1 and/or stx2 + eae with increased septic tank density (U = 2.246 p = 0.023). Findings indicate high detection rates of clinically relevant STEC in E. coli contaminated groundwater sources in Ireland.

Spatiotemporal dynamics of Escherichia coli presence and magnitude across a national groundwater monitoring network, Republic of Ireland, 2011-2020.

Groundwater is a vital drinking water resource and its protection from microbiological contamination is paramount to safeguard public health. The Republic of Ireland (RoI) is characterised by the highest incidence of verocytotoxigenic Escherichia coli (VTEC) enteritis in the European Union (EU), linked to high reliance on unregulated groundwater sources (~16% of the population). Yet, the spatio-temporal factors influencing the frequency and magnitude of microbial contamination remain largely unknown, with past studies typically constrained to spatio-temporally 'limited' sampling campaigns. Accordingly, the current investigation sought to analyse an extensive spatially distributed time-series (2011-2020) of groundwater monitoring data in the RoI. The dataset, compiled by the Environmental Protection Agency (EPA), showed 'high' contamination rates, with 66.7% (88/132) of supplies testing positive for E. coli, and 29.5% (39/132) exceeding concentrations of 10MPN/100 ml (i.e. gross contamination) at least once during the 10-year monitoring period. Seasonal decomposition analyses indicate that E. coli detection rates peak during late autumn/early winter, coinciding with increases in annual rainfall, while gross contamination peaks in spring (May) and late-summer (August), likely reflecting seasonal shifts in agricultural practices. Mixed effects logistic regression modelling indicates that monitoring sources located in karst limestone are statistically associated with E. coli presence (OR = 2.76, p = 0.03) and gross contamination (OR = 2.54, p = 0.037) when compared to poorly productive aquifers (i.e., transmissivity below 10m2/d). Moreover, 5-day and 30-day antecedent rainfall increased the likelihood of E. coli contamination (OR = 1.027, p < 0.001 and OR = 1.005, p = 0.016, respectively), with the former also being associated with gross contamination (OR = 1.042, p < 0.001). As such, it is inferred that preferential flow and direct ingress of surface runoff are the most likely ingress mechanisms associated with E. coli groundwater supply contamination. The results presented are expected to inform policy change around groundwater source protection and provide insight for the development of groundwater monitoring programmes in geologically heterogeneous regions.

Breakpoint modelling of temporal associations between non-pharmaceutical interventions and symptomatic COVID-19 incidence in the Republic of Ireland.

BACKGROUND: To constrain propagation and mitigate the burden of COVID-19, most countries initiated and continue to implement several non-pharmaceutical interventions (NPIs), including national and regional lockdowns. In the Republic of Ireland, the first national lockdown was decreed on 23rd of March 2020, followed by a succession of restriction increases and decreases (phases) over the following year. To date, the effects of these interventions remain unclear, and particularly within differing population subsets. The current study sought to assess the impact of individual NPI phases on COVID-19 transmission patterns within delineated population subgroups in the Republic of Ireland. METHODS AND FINDINGS: Confirmed, anonymised COVID-19 cases occurring between the 29th of February 2020 and 30th November 2020 (n = 72,654) were obtained. Segmented modelling via breakpoint regression with multiple turning points was employed to identify structural breaks across sub-populations, including primary/secondary infections, age deciles, urban/commuter/rural areas, patients with underlying health conditions, and socio-demographic profiles. These were subsequently compared with initiation dates of eight overarching NPI phases. Five distinct breakpoints were identified. The first breakpoint, associated with a decrease in the daily COVID-19 incidence, was reported within 14 days of the first set of restrictions in mid-March 2020 for most population sub-groups. Results suggest that moderately strict NPIs were more effective than the strictest Phase 5 (National Lockdown). Divergences were observed across population sub-groups; lagged response times were observed among populations >80 years, residents of rural/ commuter regions, and cases associated with a below-median deprivation score. CONCLUSIONS: Study findings suggest that many NPIs have been successful in decreasing COVID-19 incidence rates, however the strictest Phase 5 NPI was not. Moreover, NPIs were not equally successful across all sub-populations, with differing response times noted. Future strategies and interventions may need to be increasingly bespoke, based on sub-population profiles and required responses.

Geocoding cryptosporidiosis cases in Ireland (2008-2017)-development of a reliable, reproducible, multiphase geocoding methodology.

BACKGROUND: Geocoding (the process of converting a text address into spatial data) quality may affect geospatial epidemiological study findings. No national standards for best geocoding practice exist in Ireland. Irish postcodes (Eircodes) are not routinely recorded for infectious disease notifications and > 35% of dwellings have non-unique addresses. This may result in incomplete geocoding and introduce systematic errors into studies. AIMS: This study aimed to develop a reliable and reproducible methodology to geocode cryptosporidiosis notifications to fine-resolution spatial units (Census 2016 Small Areas), to enhance data validity and completeness, thus improving geospatial epidemiological studies. METHODS: A protocol was devised to utilise geocoding tools developed by the Health Service Executive's Health Intelligence Unit. Geocoding employed finite-string automated and manual matching, undertaken sequentially in three additive phases. The protocol was applied to a cryptosporidiosis notification dataset (2008-2017) from Ireland's Computerised Infectious Disease Reporting System. Outputs were validated against devised criteria. RESULTS: Overall, 92.1% (4266/4633) of cases were successfully geocoded to one Small Area, and 95.5% (n = 4425) to larger spatial units. The proportion of records geocoded increased by 14% using the multiphase approach, with 5% of records re-assigned to a different spatial unit. CONCLUSIONS: The developed multiphase protocol improved the completeness and validity of geocoding, thus increasing the power of subsequent studies. The authors recommend capturing Eircodes ideally using application programming interface for infectious disease or other health-related datasets, for more efficient and reliable geocoding. Where Eircodes are not recorded/available, for best geocoding practice, we recommend this (or a similar) quality driven protocol.

Groundwater resources as a global reservoir for antimicrobial-resistant bacteria.

Antimicrobial resistance represents one of our most significant global health threats, with increasing incidences noted in both clinical and environmental settings. As such, identifying and understanding the sources and pathways for antimicrobial-resistant bacteria (ARB) is critical. The current study presents the first systematic review and pooled analysis of ARB occurrence in global groundwater supplies, which are used as primary drinking water sources by 2.2 billion people worldwide and are recurrently linked to significant outbreaks of infection. Seventy peer-reviewed studies were identified and included; findings reveal that 80.2% ± 29.0 and 57.2% ± 36.8 of aggregated groundwater isolates were resistant to ≥1 and ≥3 antimicrobials, respectively. Where bacteria were present, ARB were identified in 76.9% ± 33.7 of individual wells and springs. Our results leave little doubt that groundwater represents a major global reservoir for ARB, however significant research is required to establish environmental determinants and mechanisms mediating their occurrence.

Gender-Related Differences in Flood Risk Perception and Behaviours among Private Groundwater Users in the Republic of Ireland.

Extreme weather events including flooding can have severe personal, infrastructural, and economic consequences, with recent evidence pointing to surface flooding as a pathway for the microbial contamination of private groundwater supplies. There is a pressing need for increasingly focused information and awareness campaigns to highlight the risks posed by extreme weather events and appropriate subsequent post-event actions. To date, little is known about the presence, directionality or magnitude of gender-related differences regarding flood risk awareness and behaviour among private groundwater users, a particularly susceptible sub-population due to an overarching paucity of infrastructural regulation across many regions. The current study investigated gender-related differences in flood risk perception and associated mitigation behaviours via a cross-sectional, national survey of 405 (168 female, 237 male) private groundwater supply users. The developed survey instrument assessed socio-demographic profile, previous flood experience, experiential and conjectural health behaviours (contingent on previous experience), and Risk, Attitude, Norms, Ability, Self-regulation (RANAS) framework questions. Statistically significant gender differences were found between both 'Norm-Descriptive' and 'Ability-Self-efficacy' RANAS elements (p < 0.05). Female respondents reported a lower level of awareness of the need for post-flood action(s) (8.9% vs. 16.5%), alongside a perceived "lack of information" as a reason for not testing their domestic well (4.9% vs. 11.5%). Conversely, male respondents were more likely to report awareness of their well location in relation to possible contamination sources (96.6% vs. 89.9%) and awareness of previous water testing results (98.9% vs. 93.0%). Gender-related gaps exist within the studied private groundwater reliant cohort, a sub-population which has to date remained under-studied within the context of climate change and extreme weather events. Accordingly, findings suggest that gender-focused communication and education may represent an effective tool for protecting current and future generations of global groundwater users.

Wood waste decomposition in landfills: An assessment of current knowledge and implications for emissions reporting.

Large quantities of wood products have historically been disposed of in landfills. The fate of this vast pool of carbon plays an important role in national carbon balances and accurate emission reporting. The Republic of Ireland, like many EU countries, utilises the 2006 Intergovernmental Panel on Climate Change (IPCC) guidelines for greenhouse gas reporting in the waste sector, which provides default factors for emissions estimation. For wood products, the release of carbon is directly proportional to the decomposition of the degradable organic carbon fraction of the product, for which the IPCC provides a value of 0.5 (50%). However, in situ analytic results of the decomposition rates of carbon in landfilled wood do not corroborate this figure; suggesting that carbon emissions are likely overestimated. To assess the impact of this overestimation on emission reporting, carbon decomposition values obtained from literature and the IPCC default factor were applied to the Irish wood fraction of landfilled waste for the years 1957-2016 and compared. Univariate analysis found a statistically significant difference between carbon (methane) emissions calculated using the IPCC default factor and decomposition factors from direct measurements for softwoods (F = 45.362, p = <.001), hardwoods (F = 20.691, p = <.001) and engineered wood products (U = 4.726, p = <.001). However, there was no significant difference between emissions calculated using only the in situ analytic decomposition factors, regardless of time in landfill, location or subsequently, climate. This suggests that methane emissions from the wood fraction of landfilled waste in Ireland could be drastically overestimated; potentially by a factor of 56. The results of this study highlight the implications of emission reporting at a lower tierand prompts further research into the decomposition of wood products in landfills at a national level.

Development of a hierarchical model for predicting microbiological contamination of private groundwater supplies in a geologically heterogeneous region.

Private groundwater sources in the Republic of Ireland provide drinking water to an estimated 750,000 people or 16% of the national population. Consumers of untreated groundwater are at increased risk of infection from pathogenic microorganisms. However, given the volume of private wells in operation, remediation or even quantification of public risk is both costly and time consuming. In this study, a hierarchical logistic regression model was developed to 'predict' contamination with E. coli based on the results of groundwater quality analyses of private wells (n = 132) during the period of September 2011 to November 2012. Assessment of potential microbial contamination risk factors were categorised into three groups: Intrinsic (environmental factors), Specific (local features) and Infrastructural (groundwater source characteristics) which included a total of 15 variables. Overall, 51.4% of wells tested positive for E. coli during the study period with univariate analysis indicating that 11 of the 15 assessed risk factors, including local bedrock type, local subsoil type, septic tank reliance, 5 day antecedent precipitation and temperature, along with well type and depth, were all significantly associated with E. coli presence (p < 0.05). Hierarchical logistic regression was used to develop a private well susceptibility model with the final model containing 8 of the 11 associated variables. The model was shown to be highly efficient; correctly classifying the presence of E. coli in 94.2% of cases, and the absence of E. coli in 84.7% of cases. Model validation was performed using an external data set (n = 32) and it was shown that the model has promising accuracy with 90% of positive E. coli cases correctly predicted. The developed model represents a risk assessment and management tool that may be used to develop effective water-quality management strategies to minimize public health risks both in Ireland and abroad.

Evaluation of the Complex Nomenclature of the Clinically and Veterinary Significant Pathogen Salmonella.

Salmonella encompasses a vast and highly related population of clinically and veterinary significant pathogens. The genus is responsible for an array of diseases such as typhoid fever and salmonellosis (a variety of illnesses including gastroenteritis), which cause public health issues globally. Even with the global recognition of Salmonella as a significant human and veterinary pathogen, the highly complex and evolving nomenclature system of Salmonella is problematic for clinicians, veterinarians, and microbiologists to comprehend. The present paper offers a review of the ever developing nomenclature for this bacterial species.

Assessment of the Bacterial Diversity of Aircraft Water: Identification of the Frequent Fliers.

The aim of this study was to determine and identify bacteria inhabiting the supply chain of an airline's drinking water using phenotypic and 16S rDNA sequence-based analysis. Water samples (n = 184) were sourced from long-haul and short-haul aircraft, the airline water source and a water service vehicle. In total, 308 isolates were characterised and their identity determined, which produced 82 identified bacterial species belonging to eight classes: γ-Proteobacteria; ß-Proteobacteria; α-Proteobacteria; Bacilli; Actinobacteria; Flavobacteria; Sphingobacteria and Cytophaga. Statistical differences in bacterial diversity were found to exist across sampling locations (X2 = 39.220, p = 0.009) and furthermore, differences were observed (X2 = 15.475, p = 0.030) across aircraft type (long- or short-haul). This study demonstrates the diverse nature of microorganisms within the aircraft drinking water supply chain. To the best of our knowledge, this is the most extensive study undertaken to date of microbial diversity in aircraft drinking water.