GIScience and cancer: State of the art and trends for cancer surveillance and epidemiology

Abstract

Maps are well recognized as an effective means of presenting and communicating health data, such as cancer incidence and mortality rates. These data can be linked to geographic features like counties or census tracts and their associated attributes for mapping and analysis. Such visualization and analysis provide insights regarding the geographic distribution of cancer and can be important for advancing effective cancer prevention and control programs. Applying a spatial approach allows users to identify location-based patterns and trends related to risk factors, health outcomes, and population health. Geographic information science (GIScience) is the discipline that applies Geographic Information Systems (GIS) and other spatial concepts and methods in research. This review explores the current state and evolution of GIScience in cancer research by addressing fundamental topics and issues regarding spatial data and analysis that need to be considered. GIScience, along with its health-specific application in the spatial epidemiology of cancer, incorporates multiple geographic perspectives pertaining to the individual, the health care infrastructure, and the environment. Challenges addressing these perspectives and the synergies among them can be explored through GIScience methods and associated technologies as integral parts of epidemiologic research, analysis efforts, and solutions. The authors suggest GIScience is a powerful tool for cancer research, bringing additional context to cancer data analysis and potentially informing decision-making and policy, ultimately aimed at reducing the burden of cancer.

Keywords: Geographic Information Systems (GIS); cancer surveillance; geographic information science (GIScience); mapping and visualization; spatial epidemiology; spatial statistics.

Figure 1.

This is a generalized schematic of the geocoding process.

Figure 2.

Radon levels are illustrated according to 1982 US county of residence from the Cancer Prevention Study-II. EPA indicates Environmental Protection Agency; GIS, geographic information systems; NHGIS, National Historical Geographic Information Systems; SEC, Statistics and Evaluation Center. Reprinted from: Teras LR, Diver WR, Turner MC, et al. Residential radon exposure and risk of incident hematologic malignancies in the Cancer Prevention Study-II nutrition cohort. Environ Res. 2016;148:46–54, with permission from Elsevier.

Figure 3.

Qualitative versus quantitative data are displayed. On the right, the top 3 maps (qualitative) depict facilities by type, and the bottom 3 maps (quantitative) depict the number of facilities by county. Source: Centers for Disease Control and Prevention Cartographic Guidelines for Public Health.

Figure 4.

Color schemes are depicted on a choropleth map of county lung cancer rates. Note that readers with deuteranopia cannot easily differentiate the red-green scheme.

Figure 5.

Age-adjusted smoking rates and estimates of radon-attributable lung cancer mortality are illustrated. The darker purple counties represent the areas with the lowest smoking rates yet the highest estimated radon-attributable lung cancer deaths. The dark green counties are those areas with the highest smoking rates and the highest radon-attributable lung cancer mortality. The map was created by Andrew S. Berens at the Geospatial Research Analysis and Services Program (GRASP), Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA.

Figure 6.

This series of micromaps illustrates changes in breast cancer mortality rates in New Jersey (10-year aggregated rates) over 20 years. Maps 1 and 3 depict the percent change (%change) in blacks and whites over the 2 time periods, and maps 2 and 4 depict the actual change in rates. N/A indicates not applicable. Data source: National Center for Health Statistics, CDC.

Figure 7.

Combined results from Poisson and Bernoulli cluster detection are depicted. Circled areas were identified for colorectal cancer screening prevention based on the overall risk of colorectal cancer and the risk of late-stage disease.

Figure 8.

Colorectal cancer (CRC) mortality rate hotspots are illustrated with a Federally Qualified Health Center (FQHC) location overlay. ACS indicates American Cancer Society; FOIA, Freedom of Information Act; GIS, Geographic Information System; HRSA, Health Resources and Services Administration.

Figure 9.

Results of focused cluster detection of bladder cancers around industrial sites are illustrated. Q_it P value refers to the significance of the local space and time Q-statistics. Adapted from: Jacquez GM, Shi C, Meliker JR. Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility. PLoS One. 2015;10:e0124516.