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Innovative Uses of Geographic Information Systems. Lance A. Waller Department of Biostatistics Rollins School of Public Health Emory University [email protected] Outline. Why does the geography of immunization matter? What is GIS? What does GIS do? What data do I have?

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innovative uses of geographic information systems

Innovative Uses of Geographic Information Systems

Lance A. Waller

Department of Biostatistics

Rollins School of Public Health

Emory University

[email protected]

  • Why does the geography of immunization matter?
  • What is GIS?
  • What does GIS do?
  • What data do I have?
  • What questions can I answer with my data?
why geography
Why geography?
  • Is immunization coverage constant?
  • If you know where coverage is low, can you do something?
  • If you know where coverage is high, can you learn something?
what is gis
What is GIS?
  • A “geographic information system” (GIS) links:
    • Geographic features
      • Houses
      • Census tracts
    • Attribute measurements
      • Immunized (yes/no)
      • Age
      • Sociodemographics
think of
Think of…

Each cell contains an attribute value

linked with

Map (locations)

Table (attributes)

Objects on the map are features.

What does a GIS do?

Basic GIS operation #1:

  • Layering


Health center



Basic GIS operation # 2:
  • Buffering
    • Find areas within a user-specified distance of:
      • points
      • lines
      • areas
famous public health map
Famous public health map


Snow, J. (1949) Snow on Cholera.

Oxford University Press: London.

wow can we do that
Wow! Can we do that?
  • Many introductions to GIS and public health essentially say:
  • “If John Snow could do it with shoe leather, ink, and paper, just imagine what we can do with a computer!”
basic take home figure
Basic take-home figure
  • The Whirling Vortex of GIS analysis

The question

you want to


The question

you can

answer with

those data


The data you

need to answer

that question

The data you

can get

Original source: Toxicologist EPA Region IV

what kind of questions
What kind of questions?
  • Where is coverage the lowest?
  • Where is coverage the highest?
  • Outbreak size starting in high coverage area?
  • Outbreak size starting in low coverage area?
  • How could coverages impact the course of an outbreak?
  • Best response to current outbreak?
what kind of attributes
What kind of attributes?
  • Compliers
    • Residence location
    • Census region counts
  • Sociodemographic data
    • Census summaries on age, race, sex, income of census region residents
    • Some information on compliers’ sociodemographics
additional attributes
Additional attributes
  • Noncompliers
    • Residence location
    • Regional counts
  • School data
    • School district
  • Health plan data
    • Billing provides residence address
    • ZIP codes?
basic location types
Basic location types
  • Point data
    • Latitude and longitude
    • (Seems) precise
    • Distance calculations
  • Regional data
    • Counts (cases/controls) from census regions
any complications
Any complications?
  • Maxcy (1926): Endemic typhus fever in Montgomery, AL
  • Where is “where”?
  • Which location for each case?

Maxcy, K.F. (1926) “An epidemiological study of endemic typhus (Brill’s

disease) in the Southeastern United States with special reference to its

mode of transmition.” Public Health Reports41, 2967-2995.



Lilienfeld, D.E. and Stolley, P.D. (1994) Foundations of Epidemiology,

Third Edition. Oxford University Press: New York, pp. 136-140.

complications with regions






Complications with regions
  • Counts lose some resolution...
Modifiable Areal Unit Problem
  • Different aggregations can lead to different results.




















MAUP example: John Snow


Monmonier, M (1991) How to Lie with Maps. University of Chicago Press: Chicago. p. 142.

what questions can i ask
What questions can I ask?
  • Point locations
    • Interesting/uninteresting clusters
    • Interesting: clusters of non-compliers away from clusters of compliers
  • Regional counts
    • Interesting/uninteresting raised counts
    • Interesting: Less coverage than “expected”
point locations
Point locations
  • Treat locations as spatial point process
  • Spatial “intensity” (average number of events per unit area)
  • Think of intensity as a surface
  • Compare intensity of compliers to intensity of non-compliers.
  • Peaks and valleys in same places?
monte carlo simulation
Monte Carlo simulation
  • Simulate data sets under null hypothesis (e.g., constant coverage rate).
  • See if observed data (actual compliers) appear “unusual”.
  • To compare intensities, split all locations into compliers and non-compliers at random, find out how high peaks, how low valleys can get.
  • Most GIS packages will not do this, but it is a very handy tool in spatial statistics.
  • Compare observed counts to “expected” counts.
  • Some basic point process results extend to counts (counts of points in regions).
  • Constant coverage rate (perhaps age-adjusted) again a common way of obtaining “expected” counts.
  • Monte Carlo simulation for significance.
related work
Related work
  • Cancer registries: North American Association of Central Cancer Registries (NAACCR) report on GIS (Wiggins 2002)
  • Birth outcome registries
  • Public Health/Bioterrorism/Syndromic Surveillance
  • Similarities:
    • Registry data
  • Differences:
    • Infectious vs. chronic outcome
    • Urgency of temporality
  • Best work a collaboration between
    • Geographers
    • GISers
    • Epidemiologists
    • Statisticians
  • Get the best data you can to answer the questions you want.
handy references
Handy references
  • Wiggins L (Ed). Using Geographic Information Systems Technology in the Collection, Analysis, and Presentation of Cancer Registry Data: A Handbook of Basic Practices. Springfield (IL): North American Association of Central Cancer Registries, October 2002, 68 pp.
  • Cromley, E.K. and McLafferty, S.L. (2002) GIS and Public Health. The Guilford Press.
  • Bailey and Gatrell (1995) Interactive Spatial Data Analysis. Longman.
  • Waller and Crawford (2004) Applied Spatial Statistics for Public Health Data. Wiley.
what kind of software
What kind of software?

Statistical Software(SAS, S+ Spatial Stats)Spatially and/or visually challenged


GS+ClusterSeerWinBUGS/GeoBUGSXGOBI/XGvisR (many nice spatial modules,

must write code, quality

control?)Link to GIS S+/ArcView 3.x SAS Bridge to ArcGIS 8.x

Commercial GIS Software(ArcView, Mapinfo)

Statistically challengedExtensions (Analysts)$$$, limited capability Packages by scientific user good, but basic Scripts and MacrosUser-contributedOften do not give numerical output