University of Exeter
Job title:
PhD Studentship: An Integrated Hydro-epidemiological Approach to Prevent and Mitigate Water-related Zoonotic Diseases Leveraging Nature-based Solutions
Company
University of Exeter
Job description
About the GW4 BioMed2 Doctoral Training PartnershipThe partnership brings together the Universities of Bath, Bristol, Cardiff (lead) and Exeter to develop the next generation of biomedical researchers. Students will have access to the combined research strengths, training expertise and resources of the four research-intensive universities, with opportunities to participate in interdisciplinary and ‘team science’. The DTP already has over 90 studentships over 6 cohorts in its first phase, along with 58 students over 3 cohorts in its second phase.Lead Supervisor: Dr Diego Panici, University of ExeterResearch Theme: Population Health SciencesSummary: Waterborne zoonotic diseases, such as Cryptosporidium, E.coli, and Leptospira are a serious threat to drinking water safety, especially in rural, farm-dominated lands. Nature-based solutions (NbS) in hydrology and landscape management are highly effective in improving catchment water quality (by reducing agrochemical loads) and enhancing biodiversity. However, benefits of NbS in preventing waterborne zoonotic disease have been largely unexplored. This PhD, will utilise hydro-epidemiological modelling and spatial data analysis to investigate how NbS can effectively prevent and mitigate waterborne zoonoses outbreaks at multiple spatial scales, and will inform management and prevention of public health agencies and water companies.Project Description:Waterborne zoonotic diseases pose a significant threat to public health, particularly in rural and agricultural regions. Pathogens are often released through runoff from manure and slurry heaps, contaminating water streams and affecting wildlife, recreational activities, and water supplies. Incidents in water distribution networks can also result in contaminated runoff causing severe consequences. Identifying and eradicating some waterborne zoonoses is challenging. For instance, Cryptosporidium, which recently caused an outbreak in Devon appearing in the news, is highly resistant to chlorine disinfection and persists in water environments. E.coli can cause severe gastrointestinal distress, and Leptospira bacteria, shed in the urine of infected animals, can lead to severe kidney damage, liver failure, and respiratory distress, especially in areas with heavy rainfall or flooding. These pathogens can spread through water, affecting distant populations. Addressing this issue involves identifying potential sources of pathogens and preventing or mitigating outbreaks at the source. Nature-based solutions (NbS) in hydrology and landscape management have emerged over the last decade as effective strategies to improve water quality in areas affected by high concentrations of agrochemicals. NbS store water in the landscape, slow the flow in streams and hillslopes, reduce sediment erosion, and encourage natural processes such as groundwater infiltration and natural filtering. An example is the Upstream Thinking programme in South-West England (developed since 2010 by the University of Exeter/CREWW and South West Water), where NbS reduce both point and diffuse pollution from agriculture. Hydrological NbS include wetland restoration, which acts as natural filters trapping sediments and pollutants, riparian buffer zones that reduce runoffs and sediment transport, and sustainable agricultural practices like cover cropping, reduced tillage, and controlled grazing. While NbS are documented for improving water quality and enhancing biodiversity, their effectiveness in preventing and mitigating waterborne zoonotic disease outbreaks remains largely unexplored. This PhD project aims to investigate how NbS can be leveraged to manage waterborne zoonoses, and will be achieved through advanced hydro-epidemiological modelling and spatial data analysis.
Expected salary
£19237 per year
Location
Exeter
Job date
Fri, 13 Sep 2024 01:04:59 GMT
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