This PhD studentship offers an exciting opportunity to contribute to a collaborative, high-impact research programme focussed on developing transmission models that include information on ethnicity and the downstream impacts on infection transmission and control. The student will be based within the HPRU team and will join a cohort of PhD students working on projects in the area of Health Analytics and Modelling. The project will equip the student with advanced epidemiological and modelling skills, experience in data analysis and fitting models to data, and the opportunity to participate in relevant patient and public involvement and engagement.

Background
Respiratory viruses, such as RSV, influenza and Covid-19, exhibit disparities in impact by ethnicity in England [1. The reasons for these differences are not fully elucidated and evidence is needed to understand drivers of disparities and to design strategies that could mitigate them [2].

Social contact data are frequently used to parameterise transmission models of respiratory viruses, but until recently, social contact data stratified by ethnicity or socioeconomic status have not been available. This project will analyse new data from the UK Social Contact Survey survey, in which participants have reported their own and their contact's ethnicity. This will allow the student to estimate mixing matrices stratified by age and ethnicity and characterise resulting assortativity.

Project objectives
The student will work on research in some of the following topics, in the context of respiratory virus dynamics:

Development of methods to characterise social mixing across dimensions of age, ethnicity and potentially other factors (e.g. geography, socioeconomic status [3]).
Construction and interpretation of models that include heterogeneities in social contact patterns by age and ethnicity. This could include differences in household structure in different ethnic and demographic groups using Census data.
Efficient methods for simulating epidemics across age and ethnicity.
Fitting models to available data on respiratory virus circulation in a Bayesian framework [4], with special consideration of health inequalities, inequities and the role of vaccines.
The exact focus of the PhD will be finalised with the successful candidate depending on their interests and prior expertise. Applicants are asked to contact the project supervisors for an informal discussion prior to applying.