Analysis of spatial inequalities in public health prescription rates to predict antibiotic resistance risk

Supervisor(s)

Contact Professor Lex Comber to discuss this project further informally.

Project description

The government provides full details of all NHS prescription data. It aims to gain spatial intelligence about the spatial / temporal patterns and costs of prescriptions. The reasons for this are 1) economic, relating to the spiraling costs of prescriptions, and 2) the very real and increasing threat of antibiotic resistance amongst the population. However, pseudo-anonymised individual prescription data are also available and these can provide much deeper insight into the wider socio-economic of prescribing.

This research will use data  mining techniques to analyse high volumes of prescribing data (anonymised and pseudo-anonymised) within the context of geo-demographic information on population and social economic variables  in order to examine:

  • relationships between poor health and prescribing rates.
  • spatial inequalities in uptake in health provision, access to GPs and prescribing (which might then exaggerate the inequalities).
  • whether people in less deprived areas go to GPs sooner than those in more deprived areas. 
  • where GPs are prescribing more than expected.
  • where antibiotic resistance is likely to emerge. How / in what way / pattern will it spread?
  • what spatial and temporal trends are in prescriptions volume, type and cost. How does this project into the future spatially?

Entry requirements

Applications are invited from candidates with or expecting a minimum of a UK upper second class honours degree (2:1), and/or a Master's degree in the relevant subject area.

If English is not your first language, you must provide evidence that you meet the University’s minimum English Language requirements.

How to apply

Formal applications for research degree study should be made online through the university's website. Please state clearly in the research information section that the PhD you wish to be considered for is the ‘Analysis of spatial inequalities in public health prescription rates to predict antibiotic resistance risk' as well as Professor Lex Comber as your proposed supervisor.

We welcome scholarship applications from all suitably-qualified candidates, but UK black and minority ethnic (BME) researchers are currently under-represented in our Postgraduate Research community, and we would therefore particularly encourage applications from UK BME candidates. All scholarships will be awarded on the basis of merit.

If you require any further information about the application process please contact Jacqui Manton e: j.manton@leeds.ac.uk