Mathematical modelling to accelerate development of critical new Tuberculosis vaccines

Tuberculosis is the leading cause of death from a single infectious disease worldwide. 2015 saw 10.4 million cases-the majority in India, Indonesia, China, Nigeria, Pakistan and South Africa-leading to 1.4 million deaths. HIV/AIDS was associated with a further 0.4 million TB deaths. The emergent TB drug resistance epidemic compounds this picture, with approximately 480,000 new cases of multi-drug resistant TB (MDR-TB) in 2015. The WHO End TB strategy delineates a roadmap from 2015-2035 which aims to eliminate TB as a public health problem by 2050. A new post-infection vaccine targeted at adults and adolescents is likely to be critical to achieve these targets, a view supported by modelling studies and recognised by WHO. Modelling also predicts cost-effectiveness of vaccines in low and middle-income countries. In addition to vaccines, existing interventions are being scaled up and new TB diagnostics and drug treatments have advanced to the later stages of the development pipeline. Four new diagnostic assays will be evaluated in 2017. Nine new drugs are also in advanced clinical trial phases. By reducing the global burden of TB, these new interventions may, paradoxically, reduce
the anticipated cost-effectiveness of new vaccines. Additionally, both drug resistant TB (DR-TB) cases and associated costs are projected to rise, creating a need to estimate the impact and costefficiency of novel vaccines on DR-TB.
These developments have converged to create a critical knowledge gap: what are the preferred characteristics of novel TB vaccines, and their likely impacts on drug sensitive and drug resistant tuberculosis, in the context of the expected roll out of novel drugs and diagnostics?
2 Updated country-level epidemiologic and health economic models estimating these effects are required urgently. This project aims to address these questions, thereby supporting global TB vaccine development strategy and decision making.
This PhD studentship aims to generate a body of epidemiologic and health economic knowledge to support tuberculosis candidate vaccine selection. It will quantitatively model the impact of vaccination on drug sensitive (DS-) and drug resistant (DR-) TB, in the context of the expected rollout of new diagnostic and drug interventions, and the WHO 2035 and 2050 TB targets.
We will extend existing age-structured dynamic mathematical models of Mycobacterium tuberculosis transmission, calibrated to the current and historic epidemiologic characteristics of three divergent contexts (China, India and South Africa), to include DR strata and a health economic evaluation. Initially, we will model select, probable, baseline scenarios, without novel vaccines, but including probable new drugs and diagnostics. Within these, we will simulate the impact of potential TB vaccine candidates with varying characteristics. This will provide estimates of the direct and indirect impact and cost-effectiveness of new potential TB vaccines candidates on DS- and DR-TB.
The outlined project addresses an unmet need among vaccine stakeholders. It aims to inform Target Product Profile development, vaccine candidate selection and deployment beside other TB control measures. It is relevant to the MRC LID programme's "Global Infectious Diseases" theme, and its strategic priorities in vaccine research, mathematical modelling and health policy impact analysis. It applies to all the priority areas of the wider MRC 2014-2019 refreshed strategic plan ("Research Changes Lives"), including aim 1 ("Picking research that delivers") and aim 3 ("Going global"). Further, it strongly aligns with the MRC Skills Priorities of advanced quantitative skills and interdisciplinary working as it entails training in advanced quantitative methods and interdisciplinary approaches, including vaccinology, mathematical modelling, and health economics.