An Introduction to the Geography of Health
Chapter 9: Cartography and Visualization of Health Data
Photo by Peter Anthamatten
While data tables provide much
information, it is difficult to identify
patterns in the data.
For visualizing and interpreting patterns,
a graphic representation of the data
such as a map can be very useful.
This table shows data on heart
disease in Colorado.
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Anthamatten and Hazen
Source: Colorado Department of Public Health and Environment (2010)
An Introduction to the Geography of Health
Chapter 9
A “map” can be defined as a
“graphic representation of the
cultural and physical
environment” (Dent 1999).
Maps can communicate
information that is practically
incomprehensible in other
formats, illustrating spatial
patterns and connections
between locations.
Data source: Colorado Department of Public Health and Environment (2010);
Cartography by Peter Anthamatten and Devon Williford
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Origins of Health Mapping
While human beings have made
maps for millennia, it was not until
the nineteenth century that maps
played a major role in the study of
health.
This “Babylonian Map of the
World” is from around 600 BC.
Image courtesy of the British Museum
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Maps can be used for more than just
visualization of data. We can also use
maps to analyze spatial patterns in order
to confirm their significance or generate
additional hypotheses to explain them.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In order to explore his theory that
cholera is waterborne, Snow
mapped the locations of all the
deaths that occurred in the days
following the beginning of a cholera
outbreak in London in 1854.
Source: Snow (1855)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In this modern reworking of Snow’s
original map, Thiessen polygons
have been drawn to demarcate the
area closest to each pump. The total
number of cholera cases within each
polygon is reported.
What can we learn
from this analysis?
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Following World War II, health mapping
burgeoned as atlases of disease were
produced around the world.
This wall map was used
by the Costa Rica Ministry
of Health, circa 2000.
Photo by Peter Anthamatten
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In recent decades, advances in computing power and the
rise of the Internet have enabled a new era in mapping.
Maps are easier to produce than before and the Internet
has made health maps available to the general public.
Geographic information systems (GIS) are now commonly
used for mapping and analyzing health data.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Reading Maps
Reference maps show a general set of features on
the earth’s surface for navigation or reference.
This world map is an example
of a reference map.
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Anthamatten and Hazen
Courtesy of the University of Texas Libraries, The University of Texas at Austin.
An Introduction to the Geography of Health
Chapter 9
Thematic maps are used to convey spatial patterns in data, such as
incidence of a particular disease or healthcare expenditure.
This world map showing
healthcare expenditure is an
example of a thematic map.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Source:
WHO (2010)
Chapter 9
Cartographers must make gross simplifications in order to present
the information that they deem relevant, interesting, and
reportable to the audience. In this way, mapmaking is a highly
subjective process, involving hundreds of cartographic decisions.
Can you explain what cartographer Mark
Monmonier might have meant when he
stated, “not only is it easy to lie with
maps, it’s essential” (Monmonier 1999:1)?
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
What patterns
do you see on
this map? What
information is
presented?
Source: Pickle and National Center
for Health Statistics (1996)
This map from the US Atlas of Mortality shows the age-adjusted death
rates for white males in the United States by Health Service Area.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Can you identify
the different
cartographic
decisions made
in this and the
previous map?
Data Source:
National Atlas.gov (2010)
This map was made from the same data as the map on the previous slide. By
altering the way that we display the data, and guiding the reader with text in
the title and legend, the map conveys a different story.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Cartographic Concepts
Cartographic scale (usually
simply called “scale”) is the
relation between a unit of
distance on a map to a larger
distance in the real world.
The graphical scale on this
map shows how much
distance on the map is
equivalent to 100 km.
Source: Smallman-Raynor and Cliff, “Civil war and the
spread of AIDS in Central Africa”, Epidemiology and
Infection, vol. 107, issue 01, pages 73 and 74, 2009 ©
Cambridge Journals, reproduced with permission.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Mapped data can be divided into two
basic types. Continuous data are data
that exist at all points on the earth. For
example, every location on the planet has
a temperature at any given time. Other
examples of continuous data include
elevation and annual precipitation.
Source:
Legates and
Willmott (1990)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Discrete data exist in specific
locations but not in others. People,
roads, hospitals, and airports are
examples of discrete data.
Discrete data are best depicted using
symbols positioned to represent the
location of each feature.
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.
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Anthamatten and Hazen
This map is from a report on
research that investigated the
relationship between living near
industrial sources and lung cancer.
An Introduction to the Geography of Health
Chapter 9
Nominal data, such as “language” or “type of
healthcare system,” differ in kind but not in degree.
Cartography by Peter Anthamatten
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Ordinal data can be put into a meaningful order, but cannot be
precisely quantified. For instance, we can divide countries into
high, medium, and low spenders on healthcare, even if we do not
know the precise value of their healthcare budget.
Cartography by Peter Anthamatten
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Ratio data have specific numeric values, and so
can be added, subtracted, divided or multiplied.
Data from PRB (2009)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Mapmakers may choose to aggregate
data over time or space. Which level of
aggregation is used depends on the
purpose of the map and can affect the
kinds of patterns revealed.
These maps indicate the percentage of
adults in Alameda County, California,
US, who have a physical disability. The
data are categorized the same way in
all three maps, but different units of
aggregation have been used.
Data from
US Census Bureau (2009)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Maps as a Tool for Displaying Data
Map symbols are the points, lines, and areas that
make up a map. Different map symbols may be more
or less appropriate, depending on the scale of the map
and the information the mapmaker wishes to relay
about particular phenomena.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
This figure shows some
examples of map symbols
that are appropriate for
different kinds of data.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Point distribution maps, or point maps, are used to
show how something is distributed across space.
Reprinted by generous
permission of Healthmap (2010)
Reports of disease outbreaks in October 2010
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In a dot density map, points visually
depict the density of a phenomenon
in a specified area.
It is important to note that the dots
do not represent the actual locations
of the phenomenon depicted.
Reprinted by generous permission of United Nations Sudan Gateway (2006)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Graduated symbol maps can incorporate
additional information by scaling symbols
according to a particular value related to the
phenomenon being represented.
Data from WHO (2010)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In health mapping, flow maps
are often used to symbolize the
path and rate of transmission of
a disease or for illustrating the
diffusion of medical technologies
or people across space.
Smallman-Raynor and Cliff
investigated links between patterns
in the distribution of HIV/AIDS and
civil war in Uganda.
The principal routeways and truck
routes shown on the map are
hypothesized paths of transmission.
Source: Smallman-Raynor and Cliff, “Civil war and the spread of AIDS in Central
Africa”, Epidemiology and Infection, vol. 107, issue 01, pages 73 and 74, 2009 ©
Cambridge Journals, reproduced with permission.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Migration flows may also have had an
impact on the spread of HIV/AIDS.
Notice that the lines in this map are
scaled according to the volume of
migrant flows.
Source: Smallman-Raynor and Cliff, “Civil war and the spread of AIDS in Central
Africa”, Epidemiology and Infection, vol. 107, issue 01, pages 73 and 74, 2009 ©
Cambridge Journals, reproduced with permission.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Line symbols are also found
on contour maps, which use
isolines to connect points of
equal value in an area.
Contour lines represent exposure to
nitrogen dioxides and sulfur dioxide.
The authors were investigating the
relation between these exposures
and asthma among children.
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 coalfired power station on the development of children’s pulmonary
function, page 89, © 2007, with permission from Elsevier.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Data from: US Cancer Statistics
Working Group, U.S.
Department of Health and
Human Services, Centers for
Disease Control and
Prevention and National
Cancer Institute. (2010)
Choropleth maps display information about administrative units
according to the intensity of the disease or phenomenon being mapped.
Because statistical and administrative units typically have different
population sizes, the data must be reported as rates so that patterns do
not merely reflect the distribution of the underlying population.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Crude death rates from
cancer in the US, 2006
What is misleading
in a map of crude
death rates?
Data from: US Cancer Statistics Working Group, U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention and National Cancer Institute. (2010)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Notice the differences
between these two maps. The
top map shows the crude rate
for cancer and the bottom
map shows age-adjusted rates
for the same data.
What are we doing when
we age-adjust data?
Data from: US Cancer Statistics Working Group,
U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention and
National Cancer Institute. (2010)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Florida
In the first map, death rates
will be influenced by the age
structure of the population. A
popular retirement
destination, like Florida,
therefore shows high rates in
the first map.
After age adjustment, the
influence of age structure has
been removed from the data.
We can now see that Florida
actually has relatively positive
cancer statistics.
Data from: US Cancer Statistics Working Group,
U.S. Department of Health and Human Services,
Centers for Disease Control and Prevention and
National Cancer Institute. (2010)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Modern computer technology has made animated maps
possible, which can display changes over both time and space.
Banks et al. 2000. Courtesy of the Center for International
Earth Science Information Network – Columbia University.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Maps as a Tool for Exploring Spatial Patterns
Maps have been recognized as a key tool for monitoring the
distribution of disease, as a means of better understanding
disease patterns and the factors that influence disease diffusion.
Source: Guerra et al. (2008: 303)
The shading represents areas that have been determined to present a
stable (dark red) or unstable (pink) risk for P. falciparum malaria.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In this study, the authors mapped suicide rates in the UK by
administrative unit in order to highlight spatial patterns.
Standard rates
Smoothed rates
Source: Reprinted from Health and Place, Vol. 14, issue 3, Middleton, N., Sterne, J., and D. Gunnell, “An atlas of
suicide mortality: England and Wales, 1988 – 1994”, page 497, © 2008, with permission from Elsevier.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
To better visualize the patterns, the authors used data smoothing, a technique
that removes local variations by averaging values for a larger area of the map.
Standard rates
Smoothed rates
Source: Reprinted from Health and Place, Vol. 14, issue 3, Middleton, N., Sterne, J., and D. Gunnell, “An atlas of
suicide mortality: England and Wales, 1988 – 1994”, page 497, © 2008, with permission from Elsevier.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Mapping as an Analytical Tool
While mapping is an excellent tool for visualizing and
communicating patterns in health and disease, it can also
facilitate the exploration of data, generating questions that
merit additional investigation. Maps may also ultimately
facilitate analysis of spatial patterns.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Kim et al. created a neighborhoodscale map of risk for infection with
Shigella bacteria in Vietnam.
The authors were able to determine
that geographic risk factors such as
proximity to rivers, proximity to
hospitals, and religious practices
were associated with risk of
contracting shigellosis.
Source: Reprinted from Health and Place, Vol. 14, issue 3,
Kim, D., Ali, M., Thiem, D., Park, J, von Seidlein, L., and J.
Clemens, “Geographic analysis of shigellosis in Vietnam”,
page 763, © 2008, with permission from Elsevier.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Mapping Challenges
Analytical mapping efforts must avoid certain pitfalls,
such as the modifiable areal unit problem (MAUP), the
“geographic manifestation of the ecological fallacy in
which conclusions based on data aggregated at a
particular set of districts may change if one aggregates
the same underlying data to a different set of districts”
(Waller and Gotway 2004: 104).
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
In this demonstration of the MAUP, John Snow’s
cholera data have been aggregated using two
different neighborhood classifications.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Visualizing Health Patterns:
The Atlas of United States Mortality
In the 1990s, several government agencies collaborated to
produce a comprehensive atlas of disease mortality across
the US, including maps on the 18 leading causes of death.
This atlas was produced with a great deal of care and
attention to cartographic decisions, with the explicit goal of
making maps to communicate both specific rates and
general patterns to a highly-educated audience.
Some maps from the atlas are on the next slides.
What information did the authors include?
Can you identify some of the cartographic
decisions that the authors made?
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Source: Pickle and National Center for Health Statistics (1996)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Source: Pickle and National Center for Health Statistics (1996)
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Conclusion
Health geographers use maps to communicate, explore, and
analyze relationships between health and space. From map
analysis, we can begin to consider risk factors for disease, seek
connections between health and environments, and investigate
equity of healthcare provision. Gaining a critical understanding
of the language of maps is important for effectively interpreting
maps and considering how maps can distort reality.
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Anthamatten and Hazen
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Chapter 9
Discussion Questions
1.
2.
46
Can you find a map that demonstrates how health indicators in your
area compare with other places? What information can you glean from
this map? How accurate do you believe this map to be?
Discuss which type of map you would recommend to illustrate the
following health issues. What kinds of symbols do you think would best
communicate these topics?
a. the location of hospitals in a particular country
b. the diffusion of plague across Europe in the Middle Ages
c. infant mortality rates in Central America
Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
Discussion Questions
3.
4.
47
Find an example of a map that is being used to intentionally make a
political point about the connection between an exposure and a
particular health problem. Discuss how this map makes this political
point explicit.
In the text, we discussed examples of health data that are subject to
bias if self-reported. What other kinds of data quality issues do you
think are important in health mapping? How might these issues lead to
biases in research findings?
Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
References
Banks, B., Cote, T., Golden, M., Lake, R., Meij, H., Rodgers, R. P. C. and Rosenberg, P. (2000) AIDS Mortality in U.S.
Counties: small count counties aggregate. AIDS Data Animation Project, Animations for Weekly AIDS Mortality in the
United States Jan 1981 -- Dec 1992. Center for International Earth Science Information Network (CIESIN), Columbia
University. Available: <http://www.ciesin.columbia.edu/datasets/cdc-nci/continental.html> (Accessed 14 Nov 2010).
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.
Colorado Department of Public Health and Environment. (2010) Colorado Health Information Dataset, Death Statistics
[Online]. Colorado Department of Public Health and Environment. [Online]. Available:
<http://www.cdphe.state.co.us/cohid/deathmenu.html> (Accessed 03 November 2010).
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.
Guerra, C. A., Gikandi, P. W., Tatem, A. J., Noor, A. M., Smith, D. L., Hay, S. I. and Snow, R. W. (2008) ‘The limits and
intensity of Plasmodium falciparum transmission: Implications for malaria control and elimination worldwide’, Plos
Medicine, 5: 300–11.
Health Map. (2010) Latest Alerts [Online]. Available: <http://www.healthmap.org/en/> (Accessed 30 October 2010).
Kim, D. R., Ali, M., Thiem, V. D., Park, J. K., von Seidlein, L. and Clemens, J. (2008) ‘Geographic analysis of shigellosis in
Vietnam’, Health & Place, 14: 755–67.
Legates, D. R. and Willmott, C. J. (1990) ‘Mean seasonal and spatial variability in gauge-corrected, global precipitation’,
International Journal of Climatology, 10: 111–27.
Middleton, N., Sterne, J. A. C. and Gunnell, D. J. (2008) ‘An atlas of suicide mortality: England and Wales, 1988-1994’,
Health & Place, 14: 492–506.
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Anthamatten and Hazen
An Introduction to the Geography of Health
Chapter 9
References
National Atlas.gov (2010) Map Layers. [Online]. Available: <http://www.nationalatlas.gov/maplayers.html> (Accessed 21
Nov 2010).
Pickle, L. W. and National Center for Health Statistics. (1996) Atlas of United States Mortality. Hyattsville, MD.: National
Center for Health Statistics, Centers for Disease Control and Prevention, U.S. Dept. of Health and Human Services.
PRB [Population Reference Bureau]. (2009) 2009 World Population Data Sheet. Washington DC: Population Reference
Bureau.
Smallman-Raynor, M. R. and Cliff, A. D. (1991) "Civil War and the Spread of AIDS in Central Africa", Epidemiology and
Infection, 107: 69–80.
Snow, J. (1855) On the Mode of Communication of Cholera, London: John Churchill.
United Nations Sudan Gateway. (2006). Acute Watery Diarrhoea Outbreak in Northern Sudan: Distribution of Cases
Reported from Different States 21/4/2006 to 09/12/2006. [Online]. Available:
<http://www.unsudanig.org/library/mapcatalogue/sudan/data/health/Map%20906%20AWD%20Cases%20per%20StateDot%20Density-%20February%202007.pdf> (Accessed 15 October 2010).
US Cancer Statistics Working Group, U.S. Department of Health and Human Services, Centers for Disease Control and
Prevention and National Cancer Institute. (2010) United States Cancer Statistics: 1999–2006 Incidence and Mortality
Web-based Report. [Online]. Available: <www.cdc.gov/uscs> (Accessed 31 October 2010).
US Census Bureau. (2009) The 2000 United States Census [Online]. Available:
<http://www.census.gov/main/www/access.html> (Accessed 30 January 2010).
Waller, L. A. and Gotway, C. A. (2004) Applied Spatial Statistics for Public Health Data, Hoboken, N.J.: John Wiley & Sons.
[WHO] World Health Organization(2010) WHO Global Health Observatory [Online]. Available:
<http://apps.who.int/ghodata/> (Accessed 29 October 2010).
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