Trends in cancer incidence and mortality are going through a time of great change in the UK as individuals and societies adjust to a life post COVID-19. Delays to screening and diagnosis are expected to lead to an increase in the number of avoidable cancer deaths in coming years [4]. The pandemic has also further exposed the inequalities faced by those affected by cancer. Therefore there is need for a greater and more actionable understanding of local cancer inequalities to help decision makers and health practitioners identify local priority interventions and best modes of communication in partnership with the most affected communities. This project aims to address this need and builds on on-going work with Lancaster Medical School, Lancaster University, North West Cancer Research and the NHS.

Aim:
The aim of this project is to design, develop, and evaluate a public-facing on-line system and relevant public-engagement tools and techniques for mapping and understanding cancers distribution and risks associated with environment and socio-economic inequalities. It is envisaged that the on-line system should serve, for example, for the visualisation of different data related to cancer: this may include individual cancers’ stage distribution (early or late diagnosis), how an individual cancer interacts with other cancers (i.e., geographically co-occurrent cancers), and risk factors such as deprivation, demographics, and environmental aspects.

Goal:
The overall goal of this research is twofold: 1) to help local communities to identify, scrutinise and understand the patterns of one or more cancers in their area and 2) to support health practitioners with the planning, provision, and communication of suitable interventions to address priority areas.

Geographical Scope of the Study:
The initial geographical scope of the study will be Morecambe Bay Area, England, UK. One of the strengths of our proposal is the large dataset that has been made available by the University Hospitals of Morecambe Bay NHS Foundation Trust (more than 6,000 records) and which provides a robust way to examine health inequalities in the Morecambe Bay area. The Morecambe Bay area is characterised by great health, demographic, and socioeconomic geographic variation. Our research partner (Lancaster University Medical School) is responsible for applying novel statistical analysis and mapping to this data; the PhD candidate at QUB/EEECS will focus on the development of a platform that can help local communities to utilise, interrogate, and make sense of such findings.

Approach:
Underpinning the project, is a responsible approach to system design and development, information sharing and knowledge building with local communities. For example, sharing data summaries through e.g., visualisations should be mindful of and informed by people potential concerns (e.g., people may become alarmed if found to live in at-risk area) informative (e.g., data may be linked to people’s stories and resources – living in at-risk area does not translate in developing a cancer), and actionable (e.g., it should be linked to signposting to relevant interventions).
The Candidate: given the approach, the candidate must have at a demonstrable interest in methods and techniques drawn from participatory design, action research, design thinking, and rapid prototyping [2], and experience or at least a genuine appreciation for software engineering practice that includes agile & iterative development conducted in close collaboration with stakeholders and communities including the most vulnerable [3][5]. It is desirable that the candidate have a good level of understanding of statistical methods and about uncertainty. This is an exciting opportunity to work in a multidisciplinary team across two countries and across quantitative and qualitative approaches, and to meaningfully engage with oncologists, policy makers, behavioural experts, statisticians and public health and health inequalities scientists [1].

Research Partners:
This research is part of an on-going collaboration with Lancaster University, UK through the Northwest Cancer Research project ‘MapCa’. Mapca is led by Dr Luigi Sedda, Senior Lecturer in Spatial Epidemiology, Lead of the Lancaster Ecology and Epidemiology Group (Lancaster Medical School, Lancaster University), in partnership with NHS. Research partners include John Moores University, and QUB/EEECS.

References:
[1] Cardarelli K, Jackson R, Martin M, Linnear K, Lopez R, Senteio C, et al. Community-based participatory approach to reduce breast cancer disparities in south Dallas. Prog Community Health Partnersh. 2011;5(4):375
[2] Ferrario, M.A., Simm, W., Newman, P., Forshaw, S. and Whittle, J., 2014, Software engineering for 'social good': integrating action research, participatory design, and agile development. In Proceedings of the 36th International Conference on Software Engineering (pp. 520-523).
[3] Tendedez, H., Ferrario, M.A., McNaney, R. and Gradinar, A., 2022. Exploring Human-Data Interaction in Clinical Decision-making Using Scenarios: Co-design Study. JMIR Human Factors, 9(2), p.e32456.
[4] Wells, C.R. and Galvani, A.P., 2022. Impact of the COVID-19 pandemic on cancer incidence and mortality. The Lancet Public Health, 7(6), pp.e490-e491.
[5] Whittle, J., Ferrario, M.A. and Simm, W., 2020. Community-university research: a warts and all account. Into the Wild: Beyond the Design Research Lab, pp.115-147.

Funding Information

*Please note that the deadline for applications from international candidates closed on 28 February*

To be eligible for consideration for a DfE Studentship, a candidate must satisfy all the eligibility criteria based on nationality, residency and academic qualifications. The Studentship is open to UK and ROI nationals, and to EU nationals with settled status in the UK, subject to meeting the specific DfE nationality and residency criteria. Full eligibility information can be viewed via: https://www.economy-ni.gov.uk/publications/student-finance-postgraduate-studentships-terms-and-conditions

The minimum academic requirement for admission is normally an Upper Second Class Honours degree from a UK or ROI Higher Education provider in a relevant discipline, or an equivalent qualification acceptable to the University.

The candidate must have some experience with full stack web app development and a demonstrable appreciation for participatory methods of software system design. A good level of understanding of statistical methods and about uncertainty is desirable.