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Chapter 10: Health and GIS
An Introduction to the Geography of Health
Data Source: WorldResources Institute (2010)
Cartography by Peter Anthamatten
2 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
GIS Concepts and Terminology
A GIS is “a computer system that can manipulate, store and analyze data that is referenced by location” (USGS 2007).
3 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
All spatial information in a GIS must be georeferenced to
known features in some way.
In a geographic coordinate system, locations of features are described in terms of their angle from imaginary
planes on earth, most commonly using latitude and longitude coordinates.
Cartography by Peter Anthamatten
4 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
In projected coordinate systems, location is defined by its distance from an established x- or y-axis on
a planar surface.
UTM coordinates
5 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Spatial data in a GIS are stored primarily using one of two spatial models.
Each of these models is designed to represent the complicated nature of reality in a form that can be stored, manipulated, and analyzed in a GIS.
6 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
A vector data model is built from a series of spatial coordinates that define the locations of features on the map.
7 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
In this vector data GIS, country boundaries are represented by a
polygon, which is comprised of points, whose location are specified in the
database by geographic coordinates.
An “attribute table” is connected to each feature and contains data related to that feature. This example contains attribute data on infant mortality rate
and percent overweight.
8 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
The map is comprised of a grid; each cell has a value (an
“attribute”) representing elevation in meters above sea level.
In raster data models cells are used to represent a particular area on earth, in this case one square kilometer; the space represented by each cell defines the resolution of the model. Raster models work
well with continuous data such as elevation and temperature.
9 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Sometimes translating between data models can produce some
novel forms of visualization. In this example of density
analysis, for instance, the brown shading on the map (raster data) represents the density of grocery
stores (vector data).
10 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
One especially useful feature of GIS is its ability to combine multiple layers of data, enabling the discovery and exploration of spatial patterns in different phenomena.
11 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
If we are interested in exploring heart disease mortality patterns in Colorado, we could use a GIS to link a table containing the number
of age-adjusted deaths from heart disease in each county to a file of county boundaries in order to produce a map.
Data Source: Colorado Department of Public Health and the Environment (2010)
12 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Other spatial data can then be overlaid to see if there is any relation between the patterns. The red areas on the
map are urban areas, as defined by the US Census.
Does heart disease appear to bear any relationship to
urban areas?
Data Source: Colorado Department of Public Health and the Environment (2010),Nationalatlas.gov (2010)
13 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Additional layers of data can be added or removed as we consider different ideas. The hatched area on this map shows areas of
elevation greater than 2000 meters above sea level.
What other data might be worth
exploring?
Data Source: Colorado Department of Public Health and the Environment (2010),Nationalatlas.gov (2010), USGSEROS (2010)
14 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
A query is a way to examine a subset of features of a GIS.
In this example, a query has been performed to identify all districts that are within five kilometers of a major airfield in Kenya in order
to estimate the number of people that would be served by clinics
attached to the airfields.
Data Source: WRI (2010)
15 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Remote sensing is the measurement of electromagnetic radiation reflected from the earth’s surface in order to record geographic
information such as vegetation cover, land use, rainfall, or atmospheric conditions.
Why is remote sensing particularly useful for studies
in low-income contexts?Source: NASA/GSFC, MODIS Rapid Response (2006)
This satellite image shows smoke and haze
in northern India.
16 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
GIS Applications in Health Studies
The ability of GIS to link information on the basis of location has enabled or enhanced many geographic studies of health.
GIS has been used in health studies in a variety of ways including:1) Exposure assessment2) Disease surveillance3) Cluster Analysis4) Analyzing accessibility and utilization of healthcare facilities
17 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
GIS can greatly facilitate exposure assessment: estimation of the amount of a toxin that people are
exposed to on the basis of available information such as data from pollution measuring stations.
Photo by Shane Houdek (2009)Pollution in Beijing
1) Exposure Assessment
18 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
In an example of a geographic exposure
assessment, Brown et al. (1984) conducted a case-
control study to determine whether proximity to
industrial facilities was associated with increased
risk for lung cancer.
Reprinted from Environmental Research, vol. 34, Brown, L, Pottern, L., and W. Blot, “Lung cancer in relation to environmental pollutants emitted from industrial sources”, page 251, © 1984, with permission from Elsevier.
19 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
The study area was divided into a grid of one-by-one kilometer
cells. Each cell was then assigned an exposure value based on
proximity to a polluting stack and results from soil samples.
Reprinted from Environmental Research, vol. 34, Brown, L, Pottern, L., and W. Blot, “Lung cancer in relation to environmental pollutants emitted from industrial sources”, page 251, © 1984, with permission from Elsevier.
20 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Basic information on the direction and speed of wind
was also taken into consideration in building the
exposure assessments.The authors concluded that
there was a weak association between cancer risk and
proximity to industrial sources.
Reprinted from Environmental Research, vol. 34, Brown, L, Pottern, L., and W. Blot, “Lung cancer in relation to environmental pollutants emitted from industrial sources”, page 251, © 1984, with permission from Elsevier.
21 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Reprinted from Environmental Research, vol. 103, Dubnov, J., Barchana, M., Rishpon, S., Leventhal, A., Segal, I, Carel R., and Portnov, B., “Estimating the effect of air pollution from a coal-
fired power station on the development of children’s pulmonary function, page 89, © 2007, with permission from Elsevier.
In another study, Dubnov et al. estimated children’s exposure to
nitrogen oxides and sulfur dioxide in Israel by interpolating measurements
from monitoring stations.Interpolation is a method for producing estimates for locations where no data were collected, based on information
collected at other locations
22 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
2) Disease Surveillance
A disease surveillance system uses systematic data collection to monitor for signals that could indicate new outbreaks of
disease or increasing incidence of a disease. GIS has enabled spatial data to be utilized in a more dynamic
and systematic way than is possible with paper maps.
23 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Source: Srivastava et al. (2009)Courtesy of the International Journal of Health Geographics
In this study, researchers identified malaria “hotspots” in Madhya Pradesh,
India, suggesting where government anti-malaria efforts could be focused.
24 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
3) Cluster Analysis
The term disease cluster refers to a group of disease cases or high incidence rates beyond what we would normally expect
to observe in a particular time and place (CDC 1990). The term is generally reserved for unusual groupings of cases
of non-infectious diseases—particularly cancers.
25 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
While it is tempting to visually examine a map of
disease incidence in order to identify clusters, great care
must be taken to distinguish between disease clusters resulting from a specific
cause and those that have occurred randomly.
Source: Goovaerts (2006)Courtesy of the International Journal of Health Geographics
26 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Source: Chi et al. (2009)
In spite of some reservations about cluster studies, careful work can reveal useful findings. This map is from a study of birth defects.
Although high rates of birth defects were found in several villages, only one legitimate disease cluster was identified (circled).
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4) Analyzing Access and Utilization of Healthcare
GIS can inform discussions of healthcare in a variety of ways, including mapping healthcare services,
evaluating access to services, and analyzing utilization patterns (Cromley and McLafferty 2002).
A variety of techniques can be used to assess healthcare access and utilization, e.g.:
1) Density mapping2) Network analysis3) Least cost path analysis
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1) Density mapping uses population and physician data that are collected for administrative units roughly equivalent to
the distance a person could reasonably be expected to travel to visit a certain type of healthcare service in order to produce maps of the number of people per general practice
physician for each administrative unit.
29 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
2) Network analysis analyzes distance between patients and health facilities, taking into account the transportation network.
Paez et al. analyzed accessibility to healthcare by comparing different populations in Montreal, Canada. The map on the left shows the average length of trips to healthcare
facilities for residents without a car and the map on the right shows the average trip length for car-owning residents. Darker shading represents greater trip length.
Source: Paez et al. (2010). Courtesy of the International Journal of Health Geographics
30 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Reprinted from Health Informatics Journal, vol. 12, Brabyn, L. and P. Beere, “Population access to hospital emergency departments and the impacts of health reform in New Zealand”, page 234, © 2008 by SAGE. Reprinted by Permission of SAGE.
The shading on this map of New Zealand represents the
average total time for residents to travel to the nearest hospital emergency department in 1991
and 2001.
3) Least cost path analysis uses information about the transportation network to calculate the shortest distance and travel time required to
go from any point to the nearest healthcare facility.
31 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Public Participant GIS (PPGIS)
The concept behind Public Participation GIS (PPGIS) is using GIS to enable communities that have traditionally assumed the role of subject in studies to become active participants in the
formulation, analysis, and dissemination of data.
32 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Challenges in GIS and Health
Reprinted from Health Policy, vol. 74, Hassan, M., “Arsenic poisoning in Bangladesh: spatial mitigation planning with GIS and public participation”, page 225, © 2005, with permission from Elsevier.
In this example of PPGIS, citizens in Bangladesh were given maps of their local area and asked to discuss suitable locations for tube wells, to explain their reasoning for
their proposed placements, and to plot their proposals on maps.
33 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
While there is much power, utility, and potential of GIS in the study of the geography of health, it should not be viewed as a panacea for all spatial-analytical problems. A number of problems and challenges must be carefully
considered in GIS-based health research.
Challenges in GIS and Health
34 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Access
Challenges in GIS and Health
Despite efforts in participatory GIS, the substantial investment and maintenance costs associated with GIS
technologies continue to put them out of reach of many individuals and organizations.
35 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Access
Challenges in GIS and Health
Data Quality
Despite efforts in participatory GIS, the substantial investment and maintenance costs associated with GIS
technologies continue to put them out of reach of many individuals and organizations.
The error inherent in original sources of data may be amplified when the data are translated into digital format, and further amplified when they are transferred between
different GISs, modeled into different formats, or converted from one data model to another.
36 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Access
Challenges in GIS and Health
Data Quality
Privacy
Despite efforts in participatory GIS, the substantial investment and maintenance costs associated with GIS
technologies continue to put them out of reach of many individuals and organizations.
The error inherent in original sources of data may be amplified when the data are translated into digital format, and further amplified when they are transferred between
different GISs, modeled into different formats, or converted from one data model to another.
While guidelines are in place to protect an individual’s confidentiality in data that are usually stored in a
spreadsheet or database, there are few equivalent rules to protect an individual’s “spatial confidentiality” (Leitner
and Curtis 2006).
37 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Conclusion
GIS has had an important impact on the way that health geographers approach their work, making it possible to store,
display, and analyze huge quantities of spatial data.Health geographers must always bear in mind that GIS is only useful to the study of health as a tool, however. Without an understanding of the biomedical, ecological, demographic,
social, political, and cultural facets of health, GIS may provide answers but offers little insight.
1. We discuss some of the factors that GIS is able to incorporate into exposure assessment, such as wind and weather patterns, residence history, and daytime activity. Assuming that expense is no barrier, what other factors could be incorporated into a GIS-based exposure model to improve its accuracy? For example, what should we model in order to estimate exposure to diesel fumes?
2. Think of a health problem that you have studied. How could a GIS serve to shed light on the problem? What sorts of data would you combine in your analysis?
3. In your opinion, what are the most important GIS applications for health in a low-income context? What are the key applications in a high-income context? In what ways could a GIS contribute to the health problems that are particularly relevant to where you live?
38 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Discussion Questions
4. In some places, spatial data are not available to the public. In other places data are freely available, while in yet other places governments charge people for spatial data. Do you think that spatial data collected by the government should be freely available for the public to use? Why or why not?
5. One criticism of GIS is that it enforces a specific, dominant worldview that is not compatible with some cultural and social contexts. Can you think of examples of health contexts in which GIS is unable to “model reality” in a useful way for a particular group of people?
39 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
Discussion Questions
40 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
References
Brabyn, L. and Beere, P. (2006) ‘Population access to hospital emergency departments and the impacts of health reform in New Zealand’, Health Informatics Journal, 12: 227–37.
Brown, L. M., Pottern, L. M. and Blot, W. J. (1984) ‘Lung cancer in relation to environmental-pollutants emitted from industrial sources’, Environmental Research, 34: 250–61.
[CDC] Centers for Disease Control and Prevention. (1990) Guidelines for Investigating Clusters of Health Events [Online]. Available: <http://www.cdc.gov/mmwr/preview/mmwrhtml/00001797.htm> (Accessed 20 May 2010).
Chi, W. X., Wang, J. F., Li, X. H., Zheng, X. Y. and Liao, Y. L. (2008) ‘Analysis of geographical clustering of birth defects in Heshun county, Shanxi province’, International Journal of Environmental Health Research, 18: 243-52.
Colorado Department of Public Health and Environment. (2010) Colorado Health Information Dataset, Death Statistics [Online]. Available: <http://www.cdphe.state.co.us/cohid/deathmenu.html> (Accessed 03 November 2010).
Cromley, E. K. and McLafferty, S. (2002) GIS and Public Health, New York: Guilford Press.
Dubnov, J., Barchana, M., Rishpon, S., Leventhal, A., Segal, I., Carel, R. and Portnov, B. A. (2007) ‘Estimating the effect of air pollution from a coal-fired power station on the development of children's pulmonary function’, Environmental Research, 103: 87–98.
Goovaerts, P. (2006). ‘Geostatistical analysis of disease data: visualization and propagation of spatial uncertainty in cancer mortality risk using Poisson kriging and p-field simulation’, International Journal of Health Geographics, 5(7). [Online]. Available: <http://www.ij-healthgeographics.com/content/5/1/7> (Accessed 12 January 2011).
41 An Introduction to the Geography of HealthAnthamatten and Hazen Chapter 10
References
Leitner, M. and Curtis, A. (2006) ‘A first step towards a framework for presenting the location of confidential point data on maps - results of an empirical perceptual study’, International Journal of Geographical Information Science, 20: 813–22.
NASA/GSFC, MODIS Rapid Response. (2006). Haze across Northern India. [Online] Available: <http://rapidfire.sci.gsfc.nasa.gov/gallery/?2006036-0205/India.A2006036.0740.2km.jpg > (Accessed 03 January 2011).
National Atlas.gov (2010) Map Layers. [Online]. Available: <http://www.nationalatlas.gov/maplayers.html> (Accessed 21 Nov 2010).
Paez, A., Mercado, R., Farber, S., Morency, C. and M. Roorda. (2010). ‘Accessibility to health care facilities in Montreal Island: an application of relative accessibility indicators from the perspective of senior and non-senior residents. International Journal of Health Geographics, 9. [Online] Available: <http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2987784/figure/F4/> (Accessed 12 January 2011).
Rothman, K. J. (1990) ‘A sobering start for the cluster buster's conference’, American Journal of Epidemiology, 132: S6-S13.
[USGS] United States Geological Survey. (2007) Geographic Information Systems [Online]. Available: <http:// egsc.usgs.gov /isb/pubs/gis_poster/index.html> (Accessed 1 March 2010).
[USGSEROS] United States Geological Survey Earth Resources Observation and Science Center. (2010) Global 30 Arc-Second Elevation (GTOPO30) [Online]. Available: <http://eros.usgs.gov/#/Find_Data/Products_and_Data_Available/GTOPO30> (Accessed 03 November 2010).
[WRI] World Resources Institute. (2010) Download Kenya GIS Data [Online]. Available: <http://www.wri.org/publication/content/9291> (Accessed 7 November 2010).