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PhD Studentship Opportunity in Environment and Diseases: A general Method Linking Mechanism and Phenomenology

University of Surrey

Qualification Type: PhD
Location: Guildford
Funding for: UK Students, EU Students
Funding amount: £15,000 per year (See further details below)
Hours: Full Time
Placed On: 13th June 2019
Closes: 19th August 2019

The impact of environment on infectious diseases is well–known. It can affect pathogen abundance, survival, and virulence, host susceptibility to infection as well as human behaviour.  Aim: to develop a general tool to assess the risk of infectious diseases (in particular zoonosis) when we have information of relevant environmental factors. Accordingly, we are interested in the following over-arching questions: 

  • Can we identify and access “big data” – existing information that can be interrogated to yield new evidence for decision-making in One Health? The generation of new analytical approaches would provide tools that could then be adapted to specific animal or human health issues where environment plays a key role in aetiology. 
  • Can we identify the key environmental processes triggering and propagating zoonoses? 
  • Can we disentangle the role of animal, human (including socio-economic factors) and environmental factors in zoonoses? 
  • Can we identify the delay between variations in the environment (e.g. increase in the temperature or behavioural change) and the occurrence of a foodborne outbreak? 
  • How can we quantify their impact on Animal and Public Health? 

As proof of concept, we will use Salmonella, for which we have plenty of data from Public Health England (PHE). This case study will be used to validate our approach (e.g. Leptospirosis). 

A huge advantage is the high spatio-temporal resolution of data available through the MEDMI platform, a resource linking the data from PHE with data from the MetOffice (see http://tools.data-mashup.org.uk/medmi/). Land use and socio-economic data are being collected as part of on-going projects (e.g. from APHA for livestock data, Centre for Ecology and Hydrology and/or VITO satellite images for land use data). Appending animal health data to these resources is an important step that should enable further exploitation for animal disease.  The student will work under the supervision of Dr Gianni Lo Iacono and Prof Alasdair Cook and in collaboration with Prof Gordon Nichols and other members OHEJP consortium.  

This project will start in October 2019.

Entry requirements

Computational and mathematical skills as well as a good understanding of biological processes are required. Applicants need to hold an undergraduate degree in Mathematics or a related subjects (e.g. Physics, Engineering). Undergraduates with a degree in Biological Sciences or a related subjects are also welcomed as long as they have a strong interest in mathematical modelling. A Masters degree in a public health or epidemiological-related subject is desirable. Experience in mathematical modelling, biostatistics is desirable but not essential.  If English is not your first language, you will be required to have an IELTS Academic of 6.5 or above (or equivalent), with no sub-test score below 6. 

Funding

Funding will cover University fees at the UK/EU rate and a stipend for three years at RCUK levels (£15,000 per year). In addition, funding includes bench fees to a value of £10,000 over the three years to cover conference attendance.

How to apply

Please apply for this PhD through the School of Veterinary Medicine PhD applications portal https://www.surrey.ac.uk/postgraduate/veterinary-medicine-and-science-phd (click on the “Apply” tab). Please clearly state the studentship title on your application. Applicants are invited to contact Dr Lo Iacono to discuss the project informally prior to making an application.

Closing date for applications

Monday 19th August 2019

Application enquiries

Giovanni Lo Iacono, g.loiacono@surrey.ac.uk +44 (0) 1483 688893

   
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