2025-26 Project (Sumner & Clark)

Assessing tuberculosis vaccine efficacy using subclinical disease outcomes

SUPERVISORY TEAM

Supervisor

Dr Tom Sumner at LSHTM
Email: tom.sumner@lshtm.ac.uk

Co-Supervisor

Dr Rebecca Clark at LSHTM
Email: rebecca.clark@lshtm.ac.uk

PROJECT SUMMARY

Project Summary

Tuberculosis is an infectious disease responsible for an estimated 1.6 million deaths globally in 2022. Several new TB vaccines are in development and are likely to be crucial to reducing the global burden of TB.    

Current vaccine trials are designed to evaluate the efficacy of vaccines against clinical TB disease outcomes. There is increasing evidence that asymptomatic subclinical TB is a major contributor to the continued spread of TB.    

This project will use data analysis and mathematical modelling to explore the design and feasibility of vaccine trials that include subclinical disease outcomes and to assess the potential impact of new TB vaccines that prevent the development of subclinical disease.

Project Key Words

Tuberculosis, vaccines, simulation, subclinical

MRC LID Themes

  1. Infectious Disease
  2. Health Data Science
  3. Global Health

Skills

MRC Core Skills

  1. Quantitative skills
  2. Interdisciplinary skills

Skills we expect a student to develop/acquire whilst pursuing this project

Data analysis   
Mathematical modelling including model design, parameterisation and fitting using Bayesian methods.    
Programming, including but not limited to R.   
Familiarity with high performance computing.   
Contribution to vaccine development and implementation policy.

Routes

Which route/s are available with this project?

  • 1+4 = Yes
  • +4 = Yes

Possible Master’s programme options identified by supervisory team for 1+4 applicants:

  • LSHTM – MSc Epidemiology
  • LSHTM – MSc Health Data Science
  • LSHTM – MSc Medical Statistics

Full-time/Part-time Study

Is this project available for full-time study? Yes
Is this project available for part-time study? Yes

Location & Travel

Students funded through MRC LID are expected to work on site at their primary institution, meeting – at the minimum – the institutional research degree regulations and expectations. Students may also be required to travel for conferences (up to 3 over the duration of the studentship), and for any required training (for research degree study). Other travel expectations and opportunities highlighted by the supervisory team are noted below.

Primary location for duration of this research degree: LSHTM, London

Travel requirements for this project: No essential travel. The student will be encouraged to attend international conferences, and potentially visit international collaborators

Eligibility/Requirements

Particular prior educational requirements for a student undertaking this project

  • Minimum LSHTM institutional eligibility criteria for doctoral study.
  • The student should have a background in quantitative data analysis (e.g. an MSc in Epidemiology, stats, economics), or a mathematical background (e.g. degree in mathematics, physics, engineering).   
  • Some experience of mathematical modelling is desirable, but not essential.   
  • Prior experience in programming, specifically in R would be highly advantageous but not essential.

Other useful information

  • Potential Industrial CASE (iCASE) conversion? = No

PROJECT IN MORE DETAIL

Scientific description of this research project

Rationale   
Tuberculosis is an infectious disease responsible for an estimated 1.6 million deaths globally in 2022. Several new TB vaccines are in development and are likely to be crucial to reducing the global burden of TB.    

Current TB vaccine trials are designed to evaluate the efficacy of vaccines against clinical TB disease outcomes. However, national TB prevalence surveys have shown that there is a large undiagnosed burden of asymptomatic, subclinical, TB. There is increasing evidence that subclinical disease is a major contributor to the continued spread of TB and that individuals with subclinical TB may progress to clinical disease.   

The potential role of subclinical TB raises questions about the design of vaccine trials and the impact that new vaccines may have at a population level.    

Aim   
This PhD studentship aims to explore the interaction between subclinical tuberculosis (TB) and new TB vaccines using data analysis and mathematical modelling.    

Objectives    
The proposed high level objectives for the project are:   
What is the feasibility and added value of including subclinical TB outcomes in TB vaccine trials?   
• What are the key considerations for trial designs that include subclinical disease endpoints? How should data on subclinical TB be collected? How would results from such trials compare to designs that only include clinical TB?   

What is the potential population level impact of a vaccine which prevents subclinical TB disease?   
• How might a vaccine that prevents subclinical TB reduce the burden of TB? How does this depend on assumptions about vaccine efficacy and the natural history of TB?   

Techniques
The project will use a variety of data analysis and mathematical modelling methods. The project will involve the development of clinical trial simulation models and the adaptation of existing dynamic transmission models of TB. The latter will utilize an XML-based modelling framework developed by the LSHTM TB Modelling group. The project will involve the use model fitting methods including approximate bayesian computation and history matching with emulation.   

Datasets and materials   
The project will primarily use existing data sources that are publicly available. Additional data from ongoing clinical trials will become available during the course of the PhD.   

Access to high performance computing resources will be available via LSHTM (if required).   

Risks and mitigation
As the overall aim of the project will be achievable with existing data there are no significant risks to the project.

Further reading

Relevant preprints and/or open access articles:
(DOI = Digital Object Identifier)

Additional information from the supervisory team

The supervisory team has provided a recording for prospective applicants who are interested in their project. This recording should be watched before any discussions begin with the supervisory team.

Sumner-Clark recording

MRC LID LINKS

Comments are closed.