** I encourage people who are interested in the project to contact me by email (p.white@imperial.ac.uk). **

Sexually-transmitted infections present a growing threat to global public health, with increasing incidence, increasing antimicrobial resistance leading to multidrug-resistant infection, and the emergence of mpox – with men who have sex with men (MSM) disproportionately affected in the UK. Fortunately, vaccines are available for gonorrhoea and mpox, and are in development for other STIs. For gonorrhoea the Bexsero (4CMenB) meningitis B vaccine offers partial protection, and gonorrhoea-specific vaccines are in development, with results from trials expected during the project.

We published in Lancet Infectious Diseases (Whittles et al. 2022: doi.org/10.1016/S1473-3099(21)00744-1) the first transmission-dynamic model of gonorrhoea vaccination used for cost-effectiveness analysis, providing essential evidence which underpinned the decision by the UK’s Joint Committee on Vaccination and Immunisation (JCVI) to advise the UK to become the first country to implement a national vaccination programme.

Key questions are how to target vaccination to maximise health gains and address inequalities within a limited health budget, which requires identifying groups most at risk, and understanding their views on vaccination (“vaccine sentiment”) to inform promotion campaigns and provision of services.

We now have an exciting opportunity to collect the most representative data set on sexual behaviour and vaccine sentiment (for multiple vaccines) in MSM, sampling from the large, population-based REACT cohort [https://www.imperial.ac.uk/medicine/research-and-impact/groups/react-study/], and use these data to parameterise a transmission-dynamic model of STIs more robustly than has been previously possible. The student will be involved in both analysis of the survey and the transmission-dynamic modelling.

The modelling will involve further development of our gonovax R package, which has evolved as it has been used for papers in Clinical Infectious Diseases 2020, Lancet Infectious Diseases 2022, and Journal of Infectious Diseases 2024, and is used in other papers in preparation.

There will be scope to tailor to work to the student's particular interests as the project evolves. For example, there can be further data collection, including qualitative (via focus groups) or quantitative (further surveys), use of machine learning in data analysis, or development of methods for dynamic representation of behaviour in transmission-dynamic models.

The project will be supervised by Prof Peter White [https://profiles.imperial.ac.uk/p.white & https://www.linkedin.com/in/profpeterjwhite/], who is Professor of Public Health Modelling at Imperial College London and Head of the Modelling & Economics Unit at the UK Health Security Agency.
The project team will include Dr Lilith Whittles [https://profiles.imperial.ac.uk/l.whittles & https://www.linkedin.com/in/lilith-whittles/], Prof Helen Ward [https://profiles.imperial.ac.uk/h.ward & https://www.linkedin.com/in/helen-ward-29209725/], and others, including from LSHTM and UKHSA.

Candidates need to have a Masters degree (or equivalent) in a relevant quantitative subject, ideally with experience in transmission-dynamic modelling, and strong skills in coding (ideally in R). Experience of analysis of survey data would be beneficial but not essential.