Paul Hynds (Ireland)

Technological University Dublin Environmental Health Institute
Dr Paul Hynds is a Principal Investigator in the Environmental Sustainability and Health Institute (ESHI), Technological University Dublin. Pauls primary interests are in environmental fate modelling, waterborne infection and statistical modelling. His work is borne out of the “dual receptor” model thus acknowledging that both the environment and humans are affected by contamination, and particularly microbial contamination by agriculture and human wastewater. As such, he use's statistics and numerical modelling to predict the presence, frequency, and movement of enteric pathogens in the Irish environment, and how, when and where these pathogens cause infectious diseases such as VTEC enteritis and cryptosporidiosis. He tries to identify the times and places that contamination and infection are most likely to occur, and thus prevent them via improved scientific monitoring and communication with scientists, policymakers and the public.

Presenter of 1 Presentation

PROGRESSION FROM VTEC ENTERITIS TO HAEMOLYTIC URAEMIC SYNDROME (HUS) AMONG PAEDIATRIC CASES IN THE REPUBLIC OF IRELAND: A RETROSPECTIVE CASE/CASE STUDY (ID 147)

Lecture Time
10:42 - 10:49
Room
Hall 01

Abstract

Background

Ireland currently has the highest VTEC notification rate in Europe, progressing to haemolytic uraemic syndrome (HUS) in approximately 5-10% of cases and most frequently among paediatric cases. To date the effect of “place” as it relates to VTEC serotype, source, pathway and receptor have received little attention.

Methods

All confirmed cases of paediatric (≤ 5 years ) VTEC enteritis notified from January 1st 2013 to December 31st 2017 were geo-coded to one of ~19,000 Census Small Areas, and binary coded (Y/N) for HUS progression. Several national datasets were geo-referenced to the case dataset including socioeconomic profile, hydrogeological setting, landuse, and infrastructure , with penalised classification models employed to account for statistical “rarity”. Chi-square Automatic Interaction Detector (CHAID) trees were used to identifyattribute “breakpoints” .

Results

Overall, 63 cases of paediatric HUS (63/1,102; 5.7%) were analysed, with a classification accuracy of approximately 96% (60% of HUS cases accurately classified). Case age (breakpoint ≤3 years), case type (hospital inpatient), and VTEC serotype (O157, O26) were significantly predictive. Socioeconomic components (female unemployment rate ≤13%, rented accommodation >20%) and groundwater vulnerability classification (breakpoint: high/extreme) were also predictive. Local spatial attributes (deprivation, groundwater) were more significant than regional variables.

Conclusions

Developed models could be used as an “early-warning” system for HUS progression among paediatric VTEC cases. While VTEC progression appears to be both case- and therapy-related (i.e., severity), there is also a level of spatiotemporality. The association with groundwater vulnerability indicates a waterborne mode of transmission, with elevated groundwater vulnerability in parallel with higher rates of progression potentially due to higher VTEC contamination rates (i.e., dose). Higher levels of affluence associated with HUS progression may potentially serve as a proxy for exposure i.e. international travel, dietary variation and/or healthcare access.

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