Publications by authors named "P Hynds"

42 Publications

Genetic Background of Antimicrobial Resistance in Multiantimicrobial-Resistant Isolates from Feces of Healthy Broiler Chickens in Tunisia.

Biomed Res Int 2021 1;2021:1269849. Epub 2021 Oct 1.

Université de Tunis El Manar, Faculté de Médecine de Tunis, Laboratoire de Résistance Aux Antibiotiques LR99ES09, Tunisia.

Multiantimicrobial-resistant isolates are a global human health problem causing increasing morbidity and mortality. Genes encoding antimicrobial resistance are mainly harbored on mobile genetic elements (MGEs) such as transposons and plasmids as well as integrons, which enhance their rapid spread. The aim of this study was to characterize 83 multiantimicrobial-resistant isolates recovered from healthy broiler chickens. Among 78 tetracycline-resistant isolates, the , , and genes were detected in 59 (75.6%), 14 (17.9%), and one (1.2%) isolates, respectively. The , , and genes were detected 31 (46.2%), 16 (23.8%), and 6 (8.9%) isolates, respectively, among 67 sulfonamide-resistant isolates. The PCR-based replicon typing method showed plasmids in 29 isolates, IncFIB (19), IncI1-I (17), IncF (14), IncK (14), IncFIC (10), IncP (8), IncY (3), IncHI2 (1), and IncX (1). The class 1 and 2 integrons were detected in 57 and 2 isolates, respectively; one isolate harbored both integrons. Seven and one gene cassette arrays were identified in class 1 and class 2 integrons, respectively. Our findings show that multiantimicrobial-resistant isolates from chickens serve as reservoirs of highly diverse and abundant and genes and plasmid replicons. Such isolates and MGEs pose a potential health threat to the public and animal farming.
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http://dx.doi.org/10.1155/2021/1269849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8500769PMC
October 2021

Psychological impairment and extreme weather event (EWE) exposure, 1980-2020: A global pooled analysis integrating mental health and well-being metrics.

Int J Hyg Environ Health 2021 Sep 17;238:113840. Epub 2021 Sep 17.

School of Biological, Earth and Environmental Science (BEES), University College Cork, Cork, Ireland; Environmental Research Institute, University College Cork, Cork, Ireland; Irish Centre for Research in Applied Geoscience, University College Dublin, Dublin, Ireland. Electronic address:

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.
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http://dx.doi.org/10.1016/j.ijheh.2021.113840DOI Listing
September 2021

Modelling COVID-19 severity in the Republic of Ireland using patient co-morbidities, socioeconomic profile and geographic location, February to November 2020.

Sci Rep 2021 09 16;11(1):18474. Epub 2021 Sep 16.

Spatiotemporal Environmental Epidemiology Research (STEER) Group, Environmental Sustainability and Health Institute, Technological University Dublin, Dublin, Ireland.

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.
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http://dx.doi.org/10.1038/s41598-021-98008-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8446039PMC
September 2021

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

BMC Infect Dis 2021 Aug 28;21(1):880. Epub 2021 Aug 28.

Environmental Sustainability and Health Institute (ESHI), Technological University Dublin, Greenway Hub, Grangegorman, Dublin 7, D07 H6K8, Republic of Ireland.

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.
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http://dx.doi.org/10.1186/s12879-021-06598-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8401175PMC
August 2021

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

Emerg Infect Dis 2021 09;27(9):2421-2433

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.
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http://dx.doi.org/10.3201/eid2709.204021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8386769PMC
September 2021
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