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Dr Alison Hale

Temporary Lecturer in Statistics

Alison Hale

Fylde College



Research Interests

My most recent interests revolve around statistical analysis in relation to health-related applications, including: the relationship between socio-ecconomic factors and the transmission of infectious disease; longitudinal analysis of hospital patient data; and real-time disease surveillance using routinely recorded data.

I have spent several years researching in the Mathematical Physics Group where, notably in 2013, I developed a covariant electrodynamic constitutive field theory for hysteresis (both ferromagnetic and ferroelectric) materials which directly couples to Maxwell’s equations; to our knowledge this was a previously unsolved problem.  The hysteretic material may be either stationary or moving (up to around the speed of light). Furthermore I have worked on ways to extend standard models for stationary media (dispersive materials) to models of media in motion (relativistic and non-relativistic). For situations where analytical solutions are unobtainable I have successfully developed numerical algorithms e.g. to simulate the evolution of electromagnetic fields in the presence of a hysteretic material in three dimensional space.

For a short period I also undertook research in the Nonlinear Biomedical Physics Group which included creating mathematical models to simulate macroscopic human brain dynamics. The models were compared to electroencephalographic (EEG) signals from surgical patients. Biological systems are intriguing as they present highly challenging nonlinear open regimes with a spectacular ability to form patterns.


I have a broad background gained in industry and business where I spent many years, first training and then working as an electronic engineer at GEC Marconi. Later I was employed as an IT Senior Systems Analyst at Ford Motor Company. In 2002 I commenced my university education at Lancaster University, gaining a First Class Honours Masters degree in ‘Physics with Cosmology’ in just three years, then submitting my PhD thesis (supervised by Prof. R.W. Tucker) three years later in 2008. Since then I have had the good fortune to conduct research in the mathematical physics group and non-linear biomedical physics group; often developing new equations and models.  Following a vocation towards statistical analysis in health-related applications, I won an MRC Skill Development Fellowship.  I based myself in CHICAS, Lancaster Medical School, where I developed methodology for real-time epidemiological surveillance.  Most recently, now based in the Department for Mathematics and Statistics, I've developing my own mathematical approach for incorporating socioeconomic factors into infectious disease transmission models: this work was motivated by, and is applied to, Covid-19.

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