Burden of infectious disease studies in Europe and the United Kingdom: a review of methodological design choices.

This systematic literature review aimed to provide an overview of the characteristics and methods used in studies applying the disability-adjusted life years (DALY) concept for infectious diseases within European Union (EU)/European Economic Area (EEA)/European Free Trade Association (EFTA) countries and the United Kingdom. Electronic databases and grey literature were searched for articles reporting the assessment of DALY and its components. We considered studies in which researchers performed DALY calculations using primary epidemiological data input sources. We screened 3053 studies of which 2948 were excluded and 105 studies met our inclusion criteria. Of these studies, 22 were multi-country and 83 were single-country studies, of which 46 were from the Netherlands. Food- and water-borne diseases were the most frequently studied infectious diseases. Between 2015 and 2022, the number of burden of infectious disease studies was 1.6 times higher compared to that published between 2000 and 2014. Almost all studies (97%) estimated DALYs based on the incidence- and pathogen-based approach and without social weighting functions; however, there was less methodological consensus with regards to the disability weights and life tables that were applied. The number of burden of infectious disease studies undertaken across Europe has increased over time. Development and use of guidelines will promote performing burden of infectious disease studies and facilitate comparability of the results.

High-risk clonal lineages among extended-spectrum ß-lactamase producing Escherichia coli and Klebsiella pneumoniae from urban and rural stagnant water samples in Tunisia.

This study sought to investigate the occurrence and subsequently to characterize extended-spectrum beta-lactamase (ESBL)-producing Enterobacteriaceae from urban and rural stagnant water samples during the wet season (December to February) in several regions of northern Tunisia. From 56 stagnant water samples, 14 ESBL-producing Enterobacteriaceae were recovered, including 9 Escherichia coli, 3 Klebsiella pneumoniae, and 2 K. oxytoca. Most isolates were multidrug-resistant, with ESBL production primarily encoded by blaCTX-M-15 (n = 8) and blaCTX-M-1 (n = 4) followed by blaCTX-M-55 (n = 1) and blaTEM-26 (n = 1). One K. pneumoniae isolate co-harbored blaKPC and blaCTX-M-15 genes. Class 1 integrons were detected in 4 isolates, however, sul1, sul2, and aac(6')-Ib-cr genes were detected in eleven, two, and four isolates, respectively. The nine E. coli isolates belonged to seven sequence types namely, B2/ST131 (3 isolates), A/ST164, A/ST10, A/ST224, A/ST38, A/ST155, and A/ST69 (each of them one isolate). The three K. pneumoniae isolates were assigned to three sequence types: ST101, ST405 (harboring CTX-M-15 and KPC), and ST1564. Overall, the phenotypic and genotypic traits of collected isolates mirror the molecular epidemiology of ESBL-producing enterobacteria in Tunisia and highlight the potential role of stagnant water in both urban and rural areas as a reservoir of ESBL-producing Enterobacteriaceae.

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.

Integrating consumer risk perception and awareness with simulation-based quantitative microbial risk assessment using a coupled systems framework: A case study of private groundwater users in Ontario.

Private well users in Ontario are responsible for ensuring the potability of their own private drinking water source through protective actions (i.e., water treatment, well maintenance, and regular water quality testing). In the absence of regulation and limited surveillance, quantitative microbial risk assessment (QMRA) represents the most practical and robust approach to estimating the human health burden attributable to private wells. For an increasingly accurate estimation, QMRA of private well water should be represented by a coupled model, which includes both the socio-cognitive and physical aspects of private well water contamination and microbial exposure. The objective of the current study was to determine levels of waterborne exposure via well water consumption among three sub-groups (i.e., clusters) of private well users in Ontario and quantify the risk of waterborne acute gastrointestinal illness (AGI) attributed to Giardia, shiga-toxin producing E. coli (STEC) and norovirus from private drinking water sources in Ontario. Baseline simulations were utilized to explore the effect of varying socio-cognitive scenarios on model inputs (i.e., increased awareness, protective actions, aging population). The current study uses a large spatio-temporal groundwater quality dataset and cross-sectional province-wide survey to create socio-cognitive-specific QMRA simulations to estimate the risk of waterborne AGI attributed to three enteric pathogens in private drinking waters source in Ontario. Findings suggest significant differences in the level of exposure among sub-groups of private well users. Private well users within Cluster 3 are characterised by higher levels of exposure and annual illness attributable to STEC, Giardia and norovirus than Clusters 1 and 2. Provincial incidence rates of 520.9 (1522 illness per year), 532.1 (2211 illness per year) and 605.5 (5345 illness per year) cases/100,000 private well users per year were predicted for private well users associated with Clusters 1 through 3. Established models will enable development of necessary tools tailored to specific groups of at-risk well users, allowing for preventative public health management of private groundwater sources.

Methodological considerations in injury burden of disease studies across Europe: a systematic literature review.

BACKGROUND: Calculating the disease burden due to injury is complex, as it requires many methodological choices. Until now, an overview of the methodological design choices that have been made in burden of disease (BoD) studies in injury populations is not available. The aim of this systematic literature review was to identify existing injury BoD studies undertaken across Europe and to comprehensively review the methodological design choices and assumption parameters that have been made to calculate years of life lost (YLL) and years lived with disability (YLD) in these studies. METHODS: We searched EMBASE, MEDLINE, Cochrane Central, Google Scholar, and Web of Science, and the grey literature supplemented by handsearching, for BoD studies. We included injury BoD studies that quantified the BoD expressed in YLL, YLD, and disability-adjusted life years (DALY) in countries within the European Region between early-1990 and mid-2021. RESULTS: We retrieved 2,914 results of which 48 performed an injury-specific BoD assessment. Single-country independent and Global Burden of Disease (GBD)-linked injury BoD studies were performed in 11 European countries. Approximately 79% of injury BoD studies reported the BoD by external cause-of-injury. Most independent studies used the incidence-based approach to calculate YLDs. About half of the injury disease burden studies applied disability weights (DWs) developed by the GBD study. Almost all independent injury studies have determined YLL using national life tables. CONCLUSIONS: Considerable methodological variation across independent injury BoD assessments was observed; differences were mainly apparent in the design choices and assumption parameters towards injury YLD calculations, implementation of DWs, and the choice of life table for YLL calculations. Development and use of guidelines for performing and reporting of injury BoD studies is crucial to enhance transparency and comparability of injury BoD estimates across Europe and beyond.

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.

Spatiotemporal epidemiology of cryptosporidiosis in the Republic of Ireland, 2008-2017: development of a space-time "cluster recurrence" index.

BACKGROUND: Ireland frequently reports the highest annual Crude Incidence Rates (CIRs) of cryptosporidiosis in the EU, with national CIRs up to ten times the EU average. Accordingly, the current study sought to examine the spatiotemporal trends associated with this potentially severe protozoan infection. METHODS: Overall, 4509 cases of infection from January 2008 to December 2017 were geo-referenced to a Census Small Area (SA), with an ensemble of geo-statistical approaches including seasonal decomposition, Local Moran's I, and space-time scanning used to elucidate spatiotemporal patterns of infection. RESULTS: One or more confirmed cases were notified in 3413 of 18,641 Census SAs (18.3%), with highest case numbers occurring in the 0-5-year range (n = 2672, 59.3%). Sporadic cases were more likely male (OR 1.4) and rural (OR 2.4), with outbreak-related cases more likely female (OR 1.4) and urban (OR 1.5). Altogether, 55 space-time clusters (≥ 10 confirmed cases) of sporadic infection were detected, with three "high recurrence" regions identified; no large urban conurbations were present within recurrent clusters. CONCLUSIONS: Spatiotemporal analysis represents an important indicator of infection patterns, enabling targeted epidemiological intervention and surveillance. Presented results may also be used to further understand the sources, pathways, receptors, and thus mechanisms of cryptosporidiosis in Ireland.

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.

Drinking Water Consumption Patterns among Private Well Users in Ontario: Implications for Exposure Assessment of Waterborne Infection.

Understanding the water consumption patterns within a specific population informs development of increasingly accurate, spatially specific exposure and/or risk assessment of waterborne infection. The current study examined the consumption patterns of private well users in Ontario while considering potentially influential underlying sociodemographics, household characteristics, and experiential factors. A province-wide online survey was circulated between May and August 2018 (n = 1,162). Overall, 81.5% of respondents reported daily well water consumption (i.e., tap water). Results indicate a mean daily well water consumption rate of 1,132 mL/day (SD = 649 mL/day) among well water consumers. Gender was significantly associated with well water consumption, with higher consumption rates found among female respondents. The experience of acute gastrointestinal illness (AGI) symptoms or diagnosis in the past 12 months did not impact the volume of water consumed, suggesting that experiencing previous AGI does not decrease consumption volumes, and therefore exposure over time. Significantly higher rates of well water consumption were found among respondents who reported previous testing or ongoing water treatment. Approximately 45.5% of survey respondents who stated that they do not consume well water selected bottled water as their primary household drinking water supply. Bottled water consumption was also not associated with previous AGI experiences. Findings will inform future quantitative microbial risk assessments associated with private well water use by providing spatially and demographically specific estimates of well water consumption.

Classification of white blood cells (leucocytes) from blood smear imagery using machine and deep learning models: A global scoping review.

Machine learning (ML) and deep learning (DL) models are being increasingly employed for medical imagery analyses, with both approaches used to enhance the accuracy of classification/prediction in the diagnoses of various cancers, tumors and bloodborne diseases. To date however, no review of these techniques and their application(s) within the domain of white blood cell (WBC) classification in blood smear images has been undertaken, representing a notable knowledge gap with respect to model selection and comparison. Accordingly, the current study sought to comprehensively identify, explore and contrast ML and DL methods for classifying WBCs. Following development and implementation of a formalized review protocol, a cohort of 136 primary studies published between January 2006 and May 2023 were identified from the global literature, with the most widely used techniques and best-performing WBC classification methods subsequently ascertained. Studies derived from 26 countries, with highest numbers from high-income countries including the United States (n = 32) and The Netherlands (n = 26). While WBC classification was originally rooted in conventional ML, there has been a notable shift toward the use of DL, and particularly convolutional neural networks (CNN), with 54.4% of identified studies (n = 74) including the use of CNNs, and particularly in concurrence with larger datasets and bespoke features e.g., parallel data pre-processing, feature selection, and extraction. While some conventional ML models achieved up to 99% accuracy, accuracy was shown to decrease in concurrence with decreasing dataset size. Deep learning models exhibited improved performance for more extensive datasets and exhibited higher levels of accuracy in concurrence with increasingly large datasets. Availability of appropriate datasets remains a primary challenge, potentially resolvable using data augmentation techniques. Moreover, medical training of computer science researchers is recommended to improve current understanding of leucocyte structure and subsequent selection of appropriate classification models. Likewise, it is critical that future health professionals be made aware of the power, efficacy, precision and applicability of computer science, soft computing and artificial intelligence contributions to medicine, and particularly in areas like medical imaging.

Dynamic life cycle assessment of commercial and household food waste: A critical global review of emerging techniques.

DLCA has been applied to several food waste streams, however, to date no critical assessment of its strengths, weaknesses, opportunities, and threats (SWOT) is available in the scientific literature. Accordingly, the present review aims to provide a comprehensive overview of the available literature on DLCA and its application to Household and Commercial Food Waste (HCFW) by providing critical assessment and perspectives for future research. The Population, Intervention, Comparison, and Outcome (PICO) framework for literature review was employed, with just 12 relevant studies identified between 1999 and 2022, highlighting a dearth of research on DLCA of food waste and the need for further research. Identified studies exhibit significant variations with respect to DLCA methodology, boundary settings, and data quality and reporting, with more attention typically given to combining conventional LCA with dynamic characterization models, thus making it difficult to draw conclusive findings or identify consistent trends. Additionally, most identified studies employed DLCA for a specific case study and comparison with traditional LCA outcomes was typically ignored; just one study presented the projected impact from both LCA and DLCA for the entire life cycle of a product. Employed functional/reference units ranged from specific quantities such as 1 kg of refined crystals or syrup, 1 g L-1 Sophorolipid solution, and 1 kg of dry food with packaging material, to broader indicators like 1 kg of biofuel or 1 MJ of primary energy. Monte Carlo simulation was the most frequently employed method for uncertainty analyses within identified studies. Sensitivity analyses were conducted in just 4 studies, but it was not always clearly reported. While DLCA is undoubtedly a more realistic approach to impact assessment, and thus likely more accurate, a need exists for increasingly standardized and regulated versions of DLCA for global and multi-criteria practices.

Development of a "big data" groundwater microbial contamination index and spatial comparisons with enteric infection rates in southern Ontario.

Big data have become increasingly important for policymakers and scientists but have yet to be employed for the development of spatially specific groundwater contamination indices or protecting human and environmental health. The current study sought to develop a series of indices via analyses of three variables: Non-E. coli coliform (NEC) concentration, E. coli concentration, and the calculated NEC:E. coli concentration ratio. A large microbial water quality dataset comprising 1,104,094 samples collected from 292,638 Ontarian wells between 2010 and 2021 was used. Getis-Ord Gi* (Gi*), Local Moran's I (LMI), and space-time scanning were employed for index development based on identified cluster recurrence. Gi* and LMI identify hot and cold spots, i.e., spatially proximal subregions with similarly high or low contamination magnitudes. Indices were statistically compared with mapped well density and age-adjusted enteric infection rates (i.e., campylobacteriosis, cryptosporidiosis, giardiasis, verotoxigenic E. coli (VTEC) enteritis) at a subregional (N = 298) resolution for evaluation and final index selection. Findings suggest that index development via Gi* represented the most efficacious approach. Developed Gi* indices exhibited no correlation with well density, implying that indices are not biased by rural population density. Gi* indices exhibited positive correlations with mapped infection rates, and were particularly associated with higher bacterial (Campylobacter, VTEC) infection rates among younger sub-populations (p < 0.05). Conversely, no association was found between developed indices and giardiasis rates, an infection not typically associated with private groundwater contamination. Findings suggest that a notable proportion of bacterial infections are associated with groundwater and that the developed Gi* index represents an appropriate spatiotemporal reflection of long-term groundwater quality. Bacterial infection correlations with the NEC:E. coli ratio index (p < 0.001) were markedly different compared to correlations with the E. coli index, implying that the ratio may supplement E. coli monitoring as a groundwater assessment metric capable of elucidating contamination mechanisms. This study may serve as a methodological blueprint for the development of big data-based groundwater contamination indices across the globe.

Influence of Seasonality and Public-Health Interventions on the COVID-19 Pandemic in Northern Europe.

BACKGROUND: Most government efforts to control the COVID-19 pandemic revolved around non-pharmaceutical interventions (NPIs) and vaccination. However, many respiratory diseases show distinctive seasonal trends. In this manuscript, we examined the contribution of these three factors to the progression of the COVID-19 pandemic. METHODS: Pearson correlation coefficients and time-lagged analysis were used to examine the relationship between NPIs, vaccinations and seasonality (using the average incidence of endemic human beta-coronaviruses in Sweden over a 10-year period as a proxy) and the progression of the COVID-19 pandemic as tracked by deaths; cases; hospitalisations; intensive care unit occupancy and testing positivity rates in six Northern European countries (population 99.12 million) using a population-based, observational, ecological study method. FINDINGS: The waves of the pandemic correlated well with the seasonality of human beta-coronaviruses (HCoV-OC43 and HCoV-HKU1). In contrast, we could not find clear or consistent evidence that the stringency of NPIs or vaccination reduced the progression of the pandemic. However, these results are correlations and not causations. IMPLICATIONS: We hypothesise that the apparent influence of NPIs and vaccines might instead be an effect of coronavirus seasonality. We suggest that policymakers consider these results when assessing policy options for future pandemics. LIMITATIONS: The study is limited to six temperate Northern European countries with spatial and temporal variations in metrics used to track the progression of the COVID-19 pandemic. Caution should be exercised when extrapolating these findings.

Unregulated private wells in the Republic of Ireland: consumer awareness, source susceptibility and protective actions.

While the safety of public drinking water supplies in the Republic of Ireland is governed and monitored at both local and national levels, there are currently no legislative tools in place relating to private supplies. It is therefore paramount that private well owners (and users) be aware of source specifications and potential contamination risks, to ensure adequate water quality. The objective of this study was to investigate the level of awareness among private well owners in the Republic of Ireland, relating to source characterisation and groundwater contamination issues. This was undertaken through interviews with 245 private well owners. Statistical analysis indicates that respondents' source type significantly influences owner awareness, particularly regarding well construction and design parameters. Water treatment, source maintenance and regular water quality testing are considered the three primary "protective actions" (or "stewardship activities") to consumption of contaminated groundwater and were reported as being absent in 64%, 72% and 40% of cases, respectively. Results indicate that the level of awareness exhibited by well users did not significantly affect the likelihood of their source being contaminated (source susceptibility); increased awareness on behalf of well users was associated with increased levels of protective action, particularly among borehole owners. Hence, lower levels of awareness may result in increased contraction of waterborne illnesses where contaminants have entered the well. Accordingly, focused educational strategies to increase awareness among private groundwater users are advocated in the short-term; the development and introdiction of formal legislation is recommended in the long-term, including an integrated programme of well inspections and risk assessments.

Classification of sub-populations for quantitative risk assessment based on awareness and perception: A cross-sectional population study of private well users in Ontario.

Private well users in Ontario are responsible for protective actions, including source maintenance, treatment, and submitting samples for laboratory testing. However, low participation rates are reported, thus constituting a public health concern, as risk mitigation behaviours can directly reduce exposure to waterborne pathogens. The current study examined the combined effects of socio-demographic profile, experience(s), and "risk domains" (i.e., awareness, attitudes, risk perceptions and beliefs) on behaviours, and subsequently classified private well users in Ontario based on cognitive factors. A province-wide online survey (n = 1228) was employed to quantify Ontario well owners' awareness, perceptions, and behaviours in relation to their personal groundwater supply and local contamination sources. A scoring protocol for four risk domains was developed. Two-step cluster analysis was used to classify respondents based on individual risk domain scores. Logistic regression was employed to identify key variables associated with cluster membership (i.e., profile analysis). Overall, 1140 survey respondents were included for analyses. Three distinct clusters were identified based on two risk domains; groundwater awareness and source risk perception. Profile analyses indicate "low awareness and source risk perception" (Low A/SRP) members were more likely male, while "low awareness and moderate source risk perception" (Low A/Mod SRP) members were more likely female and bottled water users. Well users characterised as "high awareness and source risk perception" (High A/SRP) were more likely to report higher educational attainment and previous well water testing. Findings illustrate that socio-cognitive clusters and their components (i.e., demographics, awareness, attitudes, perceptions, experiences, and protective actions) are distinct based on the likelihood, frequency, and magnitude of waterborne pathogen exposures (i.e., risk-based). Risk-based clustering, when incorporated into quantitative microbial risk assessment, enables the development of effective risk management and communication initiatives that are demographically focused and tailored to specific sub-groups.

Identifying Novel Data-Driven Dietary Patterns via Dimensionality Reduction and Associations with Socioeconomic Profile and Health Outcomes in Ireland.

Dietary patterns and body mass index (BMI) play a significant role in the development of noncommunicable diseases (NCDs), which are the leading cause of mortality worldwide, including Ireland. A cross-sectional survey was conducted across Ireland to collate respondents' socioeconomic profiles, health status, and dietary patterns with a representative sample size of 957 adult respondents. Principal component analysis (PCA) and statistical analyses were subsequently employed. To the author's knowledge, this is the first study to use recent (2021) nationally representative data to characterise dietary patterns in Ireland via dimensionality reduction. Five distinct dietary patterns ("meat-focused", "dairy/ovo-focused", "vegetable-focused", "seafood-focused", and "potato-focused") were identified and statistically characterised. The "potato-focused" group exhibited the highest mean BMI (26.88 kg/m2), while the "vegetable-focused" group had the lowest (24.68 kg/m2). "Vegetable-focused" respondents were more likely to be associated with a categorically healthy BMI (OR = 1.90) and urban residency (OR = 2.03). Conversely, "meat-focused" respondents were more likely to have obesity (OR = 1.46) and rural residency (OR = 1.72) along with the "potato-focused" group (OR = 2.15). Results show that data-derived dietary patterns may better predict health outcomes than self-reported dietary patterns, and transitioning to diets focusing on vegetables, seafood, and lower meat consumption may improve health.

Assessing the risk of acute gastrointestinal illness attributable to three enteric pathogens from contaminated private water wells in Ontario.

The province of Ontario compromises the largest groundwater reliant population in Canada serving approximately 1.6 million individuals. Unlike municipal water systems, private well water is not required to meet water quality regulatory standards and thus source maintenance, treatment and testing remains the responsibility of the well owner. Infections associated with private drinking water systems are rarely documented given their typically sporadic nature, thus the human health effects (e.g., acute gastrointestinal illness (AGI)) on consumers remains relatively unknown, representing a significant gap in water safety management. The current study sought to quantify the risk of waterborne AGI attributed to Giardia, shiga-toxin producing E. coli (STEC) and norovirus from private drinking water sources in Ontario using Monte Carlo simulation-based quantitative microbial risk assessment (QMRA). Findings suggest that consumption of contaminated private well water in Ontario is responsible for approximately 4823 AGI cases annually, with 3464 (71.8%) and 1359 (28.1%) AGI cases predicted to occur in consolidated and unconsolidated aquifers, respectively. By pathogen, waterborne AGI was attributed to norovirus (62%; 2991/4823), Giardia (24.6%; 1186/4823) and STEC (13.4%; 646/4823). The developed QMRA framework was used to assess the potential health impacts of partial and total well water treatment system failure. In the unlikely event of total treatment failure, total mean annual illnesses are predicted to almost double (4217 to 7064 cases per year), highlighting the importance of effective water treatment and comprehensive testing programs in reducing infectious health risks attributable to private well water in Ontario. Study findings indicate significant underreporting of waterborne AGI rates at the provincial level likely biasing public health interventions and programs that are effective in monitoring and minimizing the health risk associated with private well water.

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.

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.

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.