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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.

Understanding patient progression from symptomatic COVID-19 infection to a severe outcome represents an important tool for improved diagnoses, surveillance, and triage. A series of models have been developed and validated to elucidate hospitalization, admission to an intensive care unit (ICU) and mortality in patients from the Republic of Ireland. This retrospective cohort study of patients with laboratory-confirmed symptomatic COVID-19 infection included data extracted from national COVID-19 surveillance forms (i.e., age, gender, underlying health conditions, occupation) and geographically-referenced potential predictors (i.e., urban/rural classification, socio-economic profile). Generalised linear models and recursive partitioning and regression trees were used to elucidate COVID-19 progression. The incidence of symptomatic infection over the study-period was 0.96% (n = 47,265), of whom 3781 (8%) required hospitalisation, 615 (1.3%) were admitted to ICU and 1326 (2.8%) died. Models demonstrated an increasingly efficacious fit for predicting hospitalization [AUC 0.816 (95% CI 0.809, 0.822)], admission to ICU [AUC 0.885 (95% CI 0.88 0.89)] and death [AUC of 0.955 (95% CI 0.951 0.959)]. Severe obesity (BMI ≥ 40) was identified as a risk factor across all prognostic models; severely obese patients were substantially more likely to receive ICU treatment [OR 19.630] or die [OR 10.802]. Rural living was associated with an increased risk of hospitalization (OR 1.200 (95% CI 1.143–1.261)]. Urban living was associated with ICU admission [OR 1.533 (95% CI 1.606–1.682)]. Models provide approaches for predicting COVID-19 prognoses, allowing for evidence-based decision-making pertaining to targeted non-pharmaceutical interventions, risk-based vaccination priorities and improved patient triage.

Approximately 1.5 million individuals in Ontario are supplied by private water wells (private groundwater supplies). Unlike municipal supplies, private well water quality remains unregulated, with owners responsible for testing, treating, and maintaining their own water supplies. The COVID-19 global pandemic and associated non-pharmaceutical interventions (NPIs) have impacted many environmental (e.g., surface water and air quality) and human (e.g., healthcare, transportation) systems over the past 15-months (January 2020 to March 2021). To date, the impact of these interventions on private groundwater systems remains largely unknown. Accordingly, the current study aimed to investigate the impact of a province-wide COVID-19 lockdown (late-March 2020) on health behaviours (i.e., private domestic groundwater sampling) and groundwater quality (via Escherichia coli (E. coli) detection and concentration) in private well water in Ontario, using time-series analyses (seasonal decomposition, interrupted time-series) of a large-spatio-temporal dataset (January 2016 to March 2021; N = 743,200 samples). Findings indicate that lockdown concurred with an immediate (p = 0.015) and sustained (p < 0.001) decrease in sampling rates, equating to approximately 2200 fewer samples received per week post-interruption. Likewise, a slightly decreased E. coli detection rate was observed approximately one month after lockdowns began (p = 0.003), while the proportion of “highly contaminated” samples (i.e., E. coli > 10 CFU/100 mL) was shown to increase within one month (p = 0.02), followed by a sustained decrease for the remainder of the year (May 2020–December 2020). Analyses strongly suggest that COVID-19 interventions resulted in discernible impacts on both well user behaviours and hydrogeological mechanisms. Findings may be used as an evidence-base for assisting policy makers, public health practitioners and private well owners in developing recommendations and mitigation strategies to manage public health risks during extreme and/or unprecedented future events.

BackgroundTo 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 23rdof March 2020, followed by a succession of restriction increases and decreases (phases) over the 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 FindingsConfirmed, anonymised COVID-19 cases occurring between the 29thof February 2020 and 30thNovember 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 NCIs 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.ConclusionsStudy 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. Mitigation strategies and interventions may need to be increasingly bespoke, based on sub-population profiles and required responses.

The Republic of Ireland (ROI) currently reports the highest incidence rates of Shiga-toxin producing Escherichia coli (STEC) enteritis and cryptosporidiosis in Europe, with the spatial distribution of both infections exhibiting a clear urban/rural divide. To date, no investigation of the role of socio-demographic profile on the incidence of either infection in the ROI has been undertaken. The current study employed bivariate analyses and Random Forest classification to identify associations between individual components of a national deprivation index and spatially aggregated cases of STEC enteritis and cryptosporidiosis. Classification accuracies ranged from 78.2% (STEC, urban) to 90.6% (cryptosporidiosis, rural). STEC incidence was (negatively) associated with a mean number of persons per room and percentage of local authority housing in both urban and rural areas, addition to lower levels of education in rural areas, while lower unemployment rates were associated with both infections, irrespective of settlement type. Lower levels of third-level education were associated with cryptosporidiosis in rural areas only. This study highlights settlement-specific disparities with respect to education, unemployment and household composition, associated with the incidence of enteric infection. Study findings may be employed for improved risk communication and surveillance to safeguard public health across socio-demographic profiles.

Extreme Weather Events (EWEs) impose a substantial health and socio-economic burden on exposed populations. Projected impacts on public health, based on increasing EWE frequencies since the 1950s, alongside evidence of human-mediated climatic change represents a growing concern. To date, the impacts of EWEs on mental health remain ambiguous, largely due to the inherent complexities in linking extreme weather phenomena with psychological status. This exploratory investigation provides a new empirical and global perspective on the psychological toll of EWEs by exclusively focusing on psychological morbidity among individuals exposed to such events. Morbidity data collated from a range of existing psychological and well-being measures have been integrated to develop a single ("holistic") metric, namely, psychological impairment. Morbidity, and impairment, were subsequently pooled for key disorders-, specifically PTSD, anxiety and depression. A "composite" (any impairment) post-exposure pooled-prevalence rate of 23% was estimated, with values of 24% calculated for depression and ⁓17% for both PTSD and anxiety. Notably, calculated pooled odds ratios (pOR = 1.9) indicate a high likelihood of any negative psychological outcome (+90%) following EWE exposure. Pooled analyses of reported risk factors (p < 0.05) highlight the pronounced impacts of EWEs among individuals with higher levels of event exposure or experienced stressors (14.5%) and socio-demographic traits traditionally linked to vulnerable sub-populations, including female gender (10%), previous history (i.e., pre-event) of psychological impairment (5.5%), lower socio-economic status (5.5%), and a lower education level (5.2%). Inherent limitations associated with collating mental health data from populations exposed to EWEs, and key knowledge gaps in the field are highlighted. Study findings provide a robust evidence base for developing and implementing public health intervention strategies aimed at ameliorating the psychological impacts of extreme weather among exposed populations.

Environmentally associated infectious diseases, including those driven by extreme weather events, represent a critical challenge for public health as their source and transmission are frequently sporadic and associated mechanisms often not well understood. Over the past decade, the Republic of Ireland (ROI) has persistently reported the highest incidence of confirmed verotoxigenic E. coli (VTEC) and cryptosporidiosis infection in the European Union. Moreover, recent climate projections indicate that the incidence, severity and timing of extreme rainfall events and flooding will increase dramatically over the next century, with Ireland forecast to be the second most affected European country with respect to the mean proportion of the population residing in flood-prone areas by 2100. This study aimed to assess the association(s) between potential flood risk exposure and the spatial occurrence of confirmed VTEC and cryptosporidiosis infection in Ireland over a 10-year period (2008-2017).In 2012, the Irish Office of Public Works (OPW) initiated the National Catchment Flood Risk Assessment and Management (CFRAM) Programme within the framework of the Flood Directive (2007/60/CE), with high-resolution flood maps produced for coastal and fluvial risks and three risk scenarios based on calculated return periods (low, medium and high probability). Small area identifiers (national census area centroids) were used to attach anonymised spatially referenced case data to CFRAM polygons using Geographical Information Systems (GIS) to produce an anonymised dataframe of confirmed infection events linked to geographically explicit flood risk attributes. Generalised linear modelling with binary link functions (infection presence/absence) were used to calculate probabilistic odds ratios (OR) between flood risk (presence/absence and scenarios) and confirmed human infection.Preliminary results indicate a clear relationship between both infections and hydrological risk. Over one third of all infection cases were reported within areas exposed to flood risk (VTEC 948/2755 cases; cryptosporidiosis 1548/4509 cases). Census areas categorised by a high (10-year Return Period) fluvial flood risk probability exhibited significantly higher incidence rates for both VTEC (OR: 1.83, P = 0.0003) and cryptosporidiosis (OR: 1.80, P = 0.0015). Similarly, areas characterised by low (1000-year Return Period) coastal flood risk probability were over twice as likely to report ≥1 confirmed case of cryptosporidiosis during the study period (OR: 2.2, P= 0.003). Space-time scan statistics (temporally-specific spatial autocorrelation) indicate an unseasonal peak of cryptosporidiosis cases occurring during April 2016, a majority of which took place within or adjacent to high flood risk areas (56% of total cases), revealing a potential relationship with the exceptional flooding events experienced during winter 2015-2016 (November-January). Further work will seek to identify the individual/combined flood risk (CFRAM) elements most significantly associated with the incidence of infections.Flood risk assessment mapping may represent an innovative approach to assessing the human health impacts of flood risk exposure and climate change. The outcomes of this study will contribute to predictive modelling of VTEC and cryptosporidiosis in Ireland, thus aiding surveillance and control of these diseases in the future, and the causative nature of regional hydrology and climate.

During a 6-week period in November and December 2015, a series of Atlantic Storms swept across the Republic of Ireland (ROI) causing widespread pluvial and fluvial flooding. Flooding was particularly severe in the west and midlands, with rainfall up to 200% above normal in many regions, making it the wettest winter ever recorded. While the infrastructural damage and subsequent costs associated with flood events have, and continue to receive widespread attention, far less coverage is given to the associated adverse human health effects. This is particularly significant in the ROI, which is characterised by the highest crude incidence rates of verotoxigenic E. coli (VTEC) enteritis and cryptosporidiosis in Europe. Accordingly, weekly spatially-referenced infection incidence from July 2015 to June 2016 were employed in concurrence with weekly time-series of cumulative antecedent rainfall, surface water discharge and groundwater level, and high-resolution flood risk mapping. An ensemble of statistical and time-series analyses were used to quantify the influence of flood hydrometeorology on the incidence of confirmed infections. Seasonal decomposition (excluding seasonal patterns and long-term trends) identified a high residual infection peak during April 2016, with space-timing scanning used to identify the location, size and temporal extent of clustering. Excess cases of VTEC enteritis were geographically associated with the midlands, while cryptosporidiosis clusters were widespread. Generalised linear modelling of infection locations show that areas with a surface water body exhibited significantly higher incidence rates for both VTEC (OR: 1.225; p

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.

Resume Objectif L’objectif de cette etude prospective longitudinale etait d’explorer le role de la douleur de l’accouchement, de la detresse et des experiences dissociatives perinatales dans l’apparition de symptomes de stress post-traumatique en post-partum. Patientes et methodes Cent dix-sept femmes ont participe a l’etude. Vingt-quatre heures apres l’accouchement elles ont complete le questionnaire douleur de Saint-Antoine (QDSA), le peritraumatic distress inventory (PDI) pour mesurer la detresse perinatale, et le peritraumatic dissociative experience questionnaire (PDEQ) pour evaluer les reactions dissociatives. Six semaines apres l’accouchement etaient administres l’impact of event scale-revised (IES-R) mesurant l’etat de stress post-traumatique et l’Edinburgh postnatal depression scale (EPDS) mesurant les symptomes depressifs. Resultats Seuls les scores d’emotions dysphoriques et de perception d’une menace vitale s’averaient etre des predicteurs significatifs du score a l’IES-R. Le score affectif du QDSA apparaissait comme un predicteur significatif des emotions dysphoriques. Discussion et conclusion La detresse emotionnelle etait le meilleur predicteur des symptomes de stress post-traumatique. Les emotions dysphoriques, predictives de la symptomatologie post-traumatique etaient predites par la dimension affective de la douleur. Ainsi, le fait de presenter des reactions emotionnelles intenses a la douleur augmenterait le risque de symptomes de stress post-traumatique en post-partum.