Examining Methods To Visualise The Cancer Population Using Cartograms: 20-Year Cancer Prevalence In The UK

Samuel JONES, Macmillan Cancer Support, United Kingdom
MCCONNELL H. 1 , WHITE C. 2 , HUWS D. 2 , IRVINE L. 3 , MILLER S. 4

1 Evidence Department, Macmillan Cancer Support, London, UK
2 Welsh Cancer Intelligence and Surveillance Unit, Public Health Wales, Cardiff, UK
3 National Cancer Intelligence Network, Public Health England, London, UK
4 Knowledge and Intelligence Team (East), Public Health England, Cambridge, UK

Purpose

An estimated 2.5 million people are living with cancer in the UK, predicted to increase to four million by 2030. The Macmillan-NCIN Cancer Prevalence project aims to provide the most granular understanding of the cancer population in the UK, with outputs produced at sub-national geographies.

A key challenge is how to visualise geographic variations in cancer prevalence, and how to best communicate which areas have the highest number of people living with cancer.


Methods

We use the National Cancer Data Repository (cancer registrations in the UK linked to mortality records) to identify people diagnosed with cancer between 1991 and 2010 and still alive on 31st December 2010.

The sub-national geography data is matched to spatial layers using ESRI ArcGIS software. GIS-based output is produced across different formats including: choropleth/thematic maps, and contiguous and non-contiguous cartograms. The results from each type of output are compared.


Results

There were 1.8 million people in the UK diagnosed between 1991 and 2010 who were matched to a sub-national geographical area. 

Standard choropleth maps, which are often used within public health, result in small-scale variations being masked in small inner city areas such as London boroughs.

Initial cartogram output, based on a density-equalising method, distorts the overall shape of the UK but highlights geographies containing the highest number of people living with cancer by increasing their size, whilst maintaining geographical relationships.

We will explore further comparisons of different visualisations using different cartogram and mapping techniques.
 
 
Conclusions

Cartograms can help form a visual narrative to visualise geographical areas which contain the highest levels of cancer prevalence in absolute terms. This can demonstrate which areas are under the most increasing demand for health services, helping commissioners quickly understand and plan for better service delivery.


Funding Source

Macmillan Cancer Support