Dr Alison Hale

Senior Research Software Engineer

  Department of Mathematics and Statistics
Lancaster University

Contact details

Modelling the impact of social mixing and behaviour on infectious disease transmission

In regard to infectious diseases socioeconomic determinants are strongly associated with differential exposure and susceptibility however they are seldom accounted for by standard compartmental infectious disease models. To address this issue I have developed a novel compartmental infectious disease model which, stratified by deprivation and age, accounts for population-level behaviour including social mixing patterns. Outputs related to this work include:

• Interview by Plus Magazine, University of Cambridge, The inequalities of COVID-19
• Workshop Organisation - I organised 1-day workshop at Newton Gateway to Mathematics (INI and University of Cambridge), Socio-Economic Determinants of Coronavirus in the UK
• Preprint - Modelling the impact of social mixing and behaviour on infectious disease transmission

Disease Surveillance

In collaboration with colleagues based at the University of Liverpool and University of Bristol I have been working on designing a system to detect outbreaks of disease among small companion animals. We used data acquired through SAVSNET from participating UK veterinary surgeries. Recently published items include:

• Journal paper A real-time spatio-temporal syndromic surveillance system with application to small companion animals in Scientific Reports (nature research).
• News bulletin on SAVSNET website, here.
• Interview on SAVSNET website, here.
• Poster view here.

Map-based Visualisation and Statistical Inference with Dynamic Atlas

One aspect of this work is to create visual representations of the variations in the health landscape of populations over space and time. To visualise this data I developed the Dynamic Atlas app. This open-source software is a stand-alone JavaScript based app intended to reside on a web server.

• Demo Follow this link to see a full demo of the Dynamic Atlas.
• Shiny To upload your data right now use the Shiny interface for the Dynamic Atlas. Note: your data is not stored on our servers beyond your web browser session.
• Download The full Dynamic Atlas app is open-source and can be downloaded from https://gitlab.com/achale/dynamicatlas; this is a working demo which can be viewed at https://achale.gitlab.io/dynamicatlas/.
  This is supported by a tutorial which can be accessed at https://achale.gitlab.io/dynamicatlastutorial/ and downloaded from https://gitlab.com/achale/dynamicatlastutorial/.

Why not write a thesis in R Markdown?

R Markdown is a great way to include data analysis and modelling results directly within a thesis or report. The layout of the thesis is formatted with Markdown. Given some data, R-code is then used to produce results directly within the thesis document. There is no need to create tables by hand or generate and save figure files.
 
Tutorial Producing a coherent thesis can be a little tricky so I wrote a tutorial to explain how to properly format the text, equations, tables, figures, images, page numbers, appendix, and so on. My tutorial is available from https://achale.gitlab.io/tutorialmarkdownthesis/
 
Template I wrote an MSc thesis of around 30,000 words using R Markdown. I have created a skeleton thesis template, skeletonThesis.Rmd, which can be used on its own or in conjunction with my tutorial. Download the R Markdown template skeletonThesis.Rmd and its corresponding PDF from my gitlab repository.

My profile and contact details can be found on Pure.