Cancer screening is a critical component of our armamentarium against cancer, facilitating identification of citizens at risk of developing the disease at the earliest stage, thus informing effective health management of the newly identified patient when cancer treatment may be more effective, avoiding significant ill health and in some cases premature death. However, cost-effectiveness analysis (CEA) must be included in any screening model, to ensure the best use of often-limited resources and deliver sustainable solutions. Striving for optimal health resource utilisation is particularly relevant in the context of the coronavirus pandemic, with COVID-19-repurposing of our health service leading to unintended de-prioritisation of non-COVID-related healthcare activities, including cancer screening. Developing robust and resilient COVID-era cancer screening programme configurations requires new, more precise data-enabled modelling approaches, which will have relevance locally, nationally and globally.
Embedded within an interdisciplinary intersectoral team comprising researchers from Schools of Mathematics and Physics (Lamrock), Medicine, Dentistry and Biomedical Sciences (Lawler, McFerran), the Northern Ireland Public Health Agency (Owen), regional clinical pathology network (Loughrey) and involving collaborators in London (Turnbull), Dublin (O’Mahony) and Rotterdam (Lansdorp-Vogelaar), the doctoral student will employ advanced machine/deep learning and CEA methodologies to develop a new precision modelling approach to cancer screening.
The project provides unrivalled opportunities for an ambitious student to thrive in an interdisciplinary, intersectoral milieu by drawing on the proven expertise of the individual team members in big data analytics, cancer systems/cancer screening research (McFerran & Lawler, BMJ 2020), health economics analysis and health-service planning. The student will have a placement during the project on the premises of the Public Health Agency whereby they will be able to more clearly understand the wider impact, importance, and understanding of cancer screening and its application not just for the Northern Irish population, but on an international level. They will receive specialist training regarding data acquisition and understanding. An additional placement opportunity with Dr Maurice Loughrey, who leads the Northern Ireland Bowel Screening Programme will enhance the knowledge and expertise of the PhD student.
This nurturing environment will empower the student to build/apply innovative robust models that investigate the complex interplay between cancer development, cancer screening methodologies, health economics and health service implementation, evaluated within several scenarios that mimic different degrees of the adverse impact of COVID-19 on cancer screening. This iterative research will permit the derivation of the most optimal robust model for cost-effective cancer screening, both during and after the COVID-19 pandemic.
Quantitative training such as mathematics or statistics is required for this project. An interest in the area of medical statistics or data analytics and experience of either (computational and application based) will be considered an advantage.
Further information:
Please contact Dr Felicity Lamrock ([Email Address Removed])
Supervisory team:
Dr Felicity Lamrock
Professor Mark Lawler
Dr Tracy Owen
Eligibility and how to apply
- Application deadline: 26th February 2021
- Please apply online at https://dap.qub.ac.uk/portal/user/u_login.php after contacting the supervisor. When applying, please choose 'MATHEMATICS AND PHYSICS' as your subject area/School.
- This project is funded by the Department for the Economy (DfE) and awarded on a competitive basis. Please check their website for further information on eligibility.
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