The DISPERSE project will increase current scientific understanding of the historical, current and likely future human health risks, exposures, and outcomes associated with multiple exposures and pathways in the Republic of Ireland. It will be the first Irish study to investigate the concurrent influence of shifting socioeconomic, environmental, meteorological and infrastructural profiles on multiple health outcomes (Winter Vomiting Bug, Asthma, Skin Cancer and Campylobacteriosis) in the ROI via development of an entirely novel and bespoke health-centric spatial unit (i.e., “HEALTHSCAPE”) for visualisation and modelling. Accordingly, DISPERSE will elucidate the individual and overlapping transmission/exposure mechanisms associated with campylobacteriosis, norovirus infection, asthma and skin cancer in the ROI, and translate findings into enhanced environmental, infrastructural and healthcare policies, interventions and compliance e.g., mapping/modelling tools, surveillance recommendations and healthcare planning. Using “gold standard” outcome variables (laboratory confirmed infections/diagnoses), the first Irish HEALTHSCAPE will be developed using an ensemble of Machine Learning and geo-informatic approaches, followed by spatially-specific integration with myriad existing datasets (Objective 2). The HEALTHSCAPE dataset will be modelled using an “Intrinsic-Specific-Infrastructural (ISI) pipeline of statistical and ML models, with results subsequently overlain to develop a “Healthscape Index” (i.e., an updateable tool for use in elucidating where, when and why human health outcomes have and will occur. The SPHeRE Scholar will be based in the SpatioTemporal Envirnmental Epidemiology Research (STEER) Group in TU Dublin, and collaborate with partners from University College Cork, Met Eireann and the Health Protection Surveillance Centre. Interested candidates should have a strong background and interest in public health and/or epidemiological modelling, with evidenced experience with or a commitment to learning to used code-based statistical programming (e.g., R, Python) and GIS software.
Interested candidates should have a strong background and interest in public health and/or epidemiological modelling, with evidenced experience with or a commitment to learning to used code-based statistical programming (e.g., R, Python) and GIS software.
Funding Agency HRB Student Stipend per annum €18,500 Materials & Travel Budget per annum €2000 Fees covered by the funding per annum €5,500 Duration of Funding 48 MNTHS
Deadline to submit an application 6/9/2023
If you are interested in submitting an application for this project, please complete an Expression of Interest.