This PhD opportunity is being offered as part of the LSTM and Lancaster University Doctoral Training Partnership. Find out more about the studentships and how to apply.
| Abstract | Background: Sexually transmitted infections are a substantial and growing public health problem with rates of gonorrhoea and syphilis in the UK increasing substantially over the last 20 years - with gonorrhea cases reaching an all time high in 2023 and with syphilis cases reaching their highest since 1948. Rates of chlamydia have remained comparatively stable, but burden remains high - with chlamydia diagnoses comprising over 50% of UK STI diagnoses. In the UK, there are marked disparities in STI incidence rates between different ethnicities, between different regions, and between different socioeconomic groups. STI incidence rates are in part determined by patterns of sexual behaviour, but previous research has suggested that some differences in STI incidence rates (e.g. between ethnicities) cannot be fully explained by individual-level differences in sexual behaviour (1-3). However, only limited research has been done to explain the underlying drivers of the observed heterogeneities in STI transmission when transmission is considered as a dynamic process (a single known example being a 2004 study, looking at gonorrhoea in 3 London health authorities (4)). Alongside individual sexual behaviour, disparities in STI incidence may occur because of assortativity between different population groups, because of network structure (e.g. differing levels of concurrent partnerships), because of different screening rates between population subgroups, or some combination of these different factors. Transmission-dynamic modelling is required to understand whether these differences can explain observed patterns, and this project will explore whether these differences can occur when STI transmission is simulated across a population with realistic sexual mixing patterns and testing rates. Aims: This PhD project will aim to: 1. Design and calibrate subgroup-stratified models of STI transmission in the UK, to to understand the extent to which a) differences in sexual behaviour, b) differences in mixing between groups, c) different network features (concurrency), and d) differences in testing rates explain differences in STI incidence rates between population subgroups. 2. Using a suite of appropriately calibrated models, to understand the extent to which model stratification impacts the predicted effectiveness of different STI control measures. 3. To understand whether STI control measures reduce or exacerbate inequalities, examining a) measures that do not depend on network structure (e.g. vaccination) and b) measures that utilise network structure (e.g. partner notification). |
| Where does this project lie in the translational pathway? | T1 - Basic Research |
| Methodological Aspects | The candidate will perform statistical analysis on sexual behaviour data collected in the fourth iteration of the National Survey of Sexual Attitudes and Lifestyle (Natsal-4) (5) to determine differences in individual sexual behaviour between ethnicity groups, between regions, and between socioeconomic groups. Using this behavioural data, the candidate will design stratified transmission-dynamic models of STI transmission in the UK, exploring a range of approaches (from deterministic compartmental models to stochastic dynamic network simulations), with an initial focus on stratification by ethnicity. Models will be via Bayesian model calibration (using Markov-Chain Monte Carlo techniques or similar) to ethnicity-stratified STI incidence data collected under UK’s GUMCAD and GRASP surveillance systems. The candidate will explore the extent to which sexual network features including but not limited to a) assortativity between subgroups and b) concurrency of partnerships explain patterns of STI incidence by ethnicity, or whether c) differences in screening rates explain patterns. The candidate will go on to develop models with different stratifications (with ethnicity, with regional structure, with socioeconomic structure, without these), and calibrate these via a Bayesian framework, to understand the potential impact of an STI control measure in the UK, and use techniques from Bayesian model selection to determine the most appropriate model. The candidate will have flexibility to explore different STIs recorded in GUMCAD based on their specific research interests. The candidate will undertake scenario-based intervention modelling to explore a) whether disparities in incidence between subgroups impact the effectiveness of STI control measures and b) the extent to which model predictions differ between stratifications, to assess the importance of including different aspects of realism within models of STI control. Further, the candidate will explore whether different STI control measures reduce or exacerbate inequalities in STI incidence (considering measures such as vaccination, which do not depend on network structure, alongside measures which utilise network structure, such as partner notification) |
| Expected Outputs | The project is anticipated to lead to three publications in reputable journals, corresponding to the three aforementioned aims. |
| Training Opportunities | Training in statistical methods, programming, and epidemiological modelling will be delivered through the Health Data Science MSc programme taught at Lancaster. Knowledge of epidemiological modelling and it’s applications will be reinforced through engagement with research group meetings and seminars delivered by Lancaster’s active Centre for Health Informatics, Computing, and Statistics (CHICAS) and Lancaster University’s Research Group for Infectious disease Epidemiology (LURGIE) . Further training opportunities may be explored at IDDconf conference workshops or similar, and through links with other institutions as part of the JUNIPER consortium. |
| Skills Required | The project would be suitable for a candidate from a mathematical or biomedical background who is looking to learn skills in epidemic modelling. The candidate should have sufficient mathematical ability to learn mathematical modelling and Bayesian model calibration. |
| Subject Areas | Health Policy and Health Systems Research |
| Key Publications associated with this project |
Fenton, Kevin A., et al. "Ethnic variations in sexual behaviour in Great Britain and risk of sexually transmitted infections: a probability survey." The Lancet 365.9466 (2005): 1246-1255. Wayal, Sonali, et al. "Ethnic variations in sexual behaviours and sexual health markers: findings from the third British National Survey of Sexual Attitudes and Lifestyles (Natsal-3)." The Lancet Public Health 2.10 (2017): e458-e472. Aicken, Catherine RH, et al. "Ethnic variations in sexual partnerships and mixing, and their association with STI diagnosis: findings from a cross-sectional biobehavioural survey of attendees of sexual health clinics across England." Sexually transmitted infections 96.4 (2020): 283-292. Turner, Katy ME, et al. "Investigating ethnic inequalities in the incidence of sexually transmitted infections: mathematical modelling study." Sexually transmitted infections 80.5 (2004): 379-385. |