GIS in Human Health Studies

  • Joseph E. Bunnell
  • Alexander W. Karlsen
  • Robert B. Finkelman
  • Timothy M. Shields


Databases used in the field of medical geology are generally comprised of geospatial and/or temporal elements. Although these are not requirements for all medical geology research projects, much of the discussion in this chapter will be focused on databases incorporated into geographic information systems (GIS). GIS are computer-based (or manual) methods that allow a user to input, store, retrieve, manipulate, analyze, and output spatial data (Aronoff 1989). There are four major systems of GIS: engineering mapping systems (computer-aided design/computer-assisted mapping; CAD/CAM), geographic base file systems, image processing systems, and generalized thematic mapping systems. Various software packages are available that perform one or more of these systems, and the relative ability to move data back and forth between them can be critical to the needs and success of a particular GIS. Relational databases are the most commonly used types of databases in GIS (Cromley and McLafferty 2002). Relational database management models are convenient for linking formerly disparate databases together in a GIS. The databases to be joined must share one common attribute, usually an identifier such as coded patient number, sample site, or latitude/longitude. Other database management structures, such as hierarchical and network systems, are not as well suited to health GIS applications, although they may be useful for extremely large databases.


Global Position System Geographic Information System Lyme Disease Geospatial Data Dental Fluorosis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Further Reading

  1. Ando M, Tadano M, Asanuma S, Matsushima S, Wanatabe T, Kondo T, Sakuai S, Ji R, Liang C, Cao S (1998) Health effects of indoor fluoride pollution from coal burning in China. Environ Health Perspect 106:239–244CrossRefGoogle Scholar
  2. Aronoff S (1989) Geographic information systems: a management perspective. WDL Publications, OttawaGoogle Scholar
  3. Belkin HE, Finkelman RB, Zheng BS (1999) Geochemistry of fluoride-rich coal related to endemic fluorosis in Guizhou Province, China, Pan-Asia Pacific conference on fluoride and arsenic research, Abstract 45, p 47Google Scholar
  4. Ben K, Hua L, Hongchao H (2000) The current state of epidemic tea-induced fluorosis and its control countermeasures in Urumqi County, Xinjiang. In: Centeno JA, Collery P, Vernet G, Finkelman RB, Gibb H, Etienne J-C (eds) Metal ions in biology and medicine, vol 6. John Libby Eurotext, Paris, pp 303–305Google Scholar
  5. Bunnell JE, Price SD, Lele SR, Das A, Shields TM, Glass GE (2003) Geographic information systems and spatial analysis of Ixodes scapularis (Acari: Ixodidae) in the middle Atlantic region of the U. S. A. J Med Entomol 40:570–576CrossRefGoogle Scholar
  6. Cameron D, Jones IG (1983) John snow, the broad street pump and modern epidemiology. Int J Epidemiol 12:393–396CrossRefGoogle Scholar
  7. Centers for Disease Control and Prevention (2001) Lyme disease–united states, 1999. MMWR 50(10):181–185Google Scholar
  8. Cromley EK, McLafferty SL (2002) GIS and public health. The Guilford Press, New York, p 340Google Scholar
  9. Das A, Lele SR, Glass GE, Shields TM, Patz JA (2002) Modeling a discrete spatial response using generalized linear mixed models: application to Lyme disease vectors. Int J Geog Inform Sci 16:151–166CrossRefGoogle Scholar
  10. Glass GE, Schwartz BS, Morgan JM III, Johnson DT, Noy PM, Israel E (1995) Environmental risk factors for Lyme disease identified with geographic information systems. Am J Public Health 85:944–948CrossRefGoogle Scholar
  11. Haining R (1998) Spatial statistics and the analysis of health data. In: Gatrell AC, Löytönen M (eds) GIS and health, GIS data VI. Taylor & Francis, London, pp 29–47Google Scholar
  12. Hock R (2001) The extreme searcher’s guide to web search engines, 2nd edn. CyberAge Books/Information Today, Inc., Medford, p 241Google Scholar
  13. Jensen PM, Hansen H, Frandsen F (2000) Spatial risk assessment for Lyme borreliosis in Denmark. Scand J Infect Dis 32:545–550CrossRefGoogle Scholar
  14. Jianan T (ed) (1989) The atlas of endemic diseases and their environments in the People’s Republic of China. Science Press, BeijingGoogle Scholar
  15. Karlsen AW, Schultz AC, Warwick PD, Podwysocki SM, Lovern VS (2001) Coal geology, land use, and human health in the People’s Republic of China, U. S. Geological Survey open file report 01–318 (CD-ROM)Google Scholar
  16. Kennedy H (ed) (2001) Dictionary of GIS terminology. ESRI Press, RedlandsGoogle Scholar
  17. Kitron U, Kazmierczak JJ (1997) Spatial analysis of the distribution of Lyme disease in Wisconsin. Am J Epidemiol 145:558–566CrossRefGoogle Scholar
  18. Kulldorff M (1998) Statistical methods for spatial epidemiology: tests for randomness. In: Gatrell AC, Löytönen M (eds) GIS and health, GIS data VI. Taylor & Francis, London, pp 49–62Google Scholar
  19. Ostfeld RS, Hazler KR, Cepeda OM (1996) Temporal and spatial dynamics of Ixodes scapularis (Acari: Ixodidae) in a rural landscape. J Med Entomol 33:90–95Google Scholar
  20. PAHO (Panamerican Health Organization) (2000) Geographic information systems in health, special program for health analysis. PAHO, Washington, DCGoogle Scholar
  21. Robinson TP (2000) Spatial statistics and geographical information systems in epidemiology and public health. In: Hay SI, Randolph SE, Rogers DJ (eds) Remote sensing and geographical information systems in epidemiology, advances in parasitology 47. Academic, San Diego, pp 81–128CrossRefGoogle Scholar
  22. Rogers DJ (2000) Satellites, space, time and the African trypanosomiases. In: Hay SI, Randolph SE, Rogers DJ (eds) Remote sensing and geographical information systems in epidemiology, advances in parasitology 47. Academic, San Diego, pp 129–171CrossRefGoogle Scholar
  23. Ruiling L, Tianyu H, Jianping W (Compilers) (1996) Coalfield prediction map of China. Surveying and mapping institute of Jilin Province, Publishing house of surveying and mapping, 9 map sheets, scale 1:2,500,000Google Scholar
  24. SHA (Special Program for Health Analysis) (2000) Incidence of malaria and land use in Chiapas, Mexico and Peten, Guatemala, PAHO, Scientific paper No. 104Google Scholar
  25. Sherman C, Price G (2001) The invisible web. CyberAge Books/Information Today, Inc., MedfordGoogle Scholar
  26. Stein A, Staritsky I, Bouma J, van Groenigen JW (1995) Interactive GIS for environmental risk assessment. Int J Geogr Inf Syst 9(5):509–525CrossRefGoogle Scholar
  27. Zeiler M (1999) Modeling our world. ESRI Press, RedlandsGoogle Scholar
  28. Zhang Y, Cao SR (1996) Coal burning induced endemic fluorosis in China. Fluoride 29(4):207–211Google Scholar
  29. Zheng B, Huang R (1989) Human fluorosis and environmental geochemistry in Southwest China. In: Developments in geoscience, contributions to 28th international geologic congress, Science Press, Washington, DC/Beijing, pp 171–176Google Scholar

Suggested Reading

  1. Bernhardsen T (1999) Geographic information systems: an introduction. Wiley, New YorkGoogle Scholar
  2. Beyer KMM, Comstock S, Seagren R (2010) Disease maps as context for community mapping: a methodological approach for linking confidential health information with local geographical knowledge for community health research. J Community Health 35(6):635–644CrossRefGoogle Scholar
  3. Briggs DJ, Elliott P (1995) The use of geographical information systems in studies on environment and health. World Health Stat Q 48:85–94Google Scholar
  4. Burrough PA, McDonnell R (1998) Principles of geographic information systems. Oxford University Press, OxfordGoogle Scholar
  5. Christakos G (2000) Modern spatiotemporal geostatistics. Oxford University Press, OxfordGoogle Scholar
  6. Clarke KC (1998) Getting started with geographic information systems, 3rd edn. Prentice Hall, Upper Saddle RiverGoogle Scholar
  7. DeMers MN (2000) Fundamentals of geographic information systems, 2nd edn. Wiley, New YorkGoogle Scholar
  8. de Savigny D, Wijeyaratne P (eds) (1995) GIS for health and environment. International Development Research Centre, OttawaGoogle Scholar
  9. Glass GE (2000) Spatial aspects of epidemiology: the interface with medical geography. Epidemiol Rev 22(1):136–139CrossRefGoogle Scholar
  10. Goovaerts P (2008) Spatial uncertainty in medical geography: a geostatistical perspective. In: Shekhar S, Xiong H (eds) Encyclopedia of GIS. Springer, Berlin, pp 1106–1112CrossRefGoogle Scholar
  11. Green K (1992) Spatial imagery and GIS: integrated data for natural resource management. J For 90:32–36Google Scholar
  12. Henshaw S, Curriero F, Shields T, Glass G, Strickland P, Breysse P (2004) Geostatistics and GIS: tools for characterizing environmental contamination. J Med Syst 28(4):335–348CrossRefGoogle Scholar
  13. Lang L (2000) GIS for health organizations, ESRI Press, Redlands, p 100 plus CD-ROMGoogle Scholar
  14. Li S, Xiao T, Zheng B (2012) Medical geology of arsenic, selenium and thallium in China. Sci Total Environ 421–422:31–40CrossRefGoogle Scholar
  15. Longley PA, Goodchild MF, Maguire DJ, Rhind DW (eds) (1999) Geographical information systems, 2nd edn. Wiley, New York, p 1101, 2 volumesGoogle Scholar
  16. Meade MS, Earickson RJ (2000) Medical geography, 2nd edn. The Guilford Press, New YorkGoogle Scholar
  17. Melnick AL (2002) Introduction to geographic information systems in public health. Aspen Publishers, GaithersburgGoogle Scholar
  18. Moore GS (2002) Living with the earth: concepts in environmental health science, 2nd edn. Lewis Publishers, Boca RatonGoogle Scholar
  19. Reisen WK (2010) Landscape epidemiology of vector-borne diseases. Annu Rev Entomol 55:461–483CrossRefGoogle Scholar
  20. Tabasi S, Abedi A (2012) A medical geology study of an arsenic-contaminated area in Kouhsorkh, NE Iran. Environ Geochem Health 34(2):171–179CrossRefGoogle Scholar
  21. Vine MF, Degnan D, Hanchette C (1997) Geographic information systems: their use in environmental epidemiological research. Environ Health Perspect 105:598–605CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Joseph E. Bunnell
    • 1
  • Alexander W. Karlsen
    • 1
  • Robert B. Finkelman
    • 2
  • Timothy M. Shields
    • 3
  1. 1.United States Department of the InteriorUnited States Geological SurveyTexasUSA
  2. 2.Department of GeosciencesUniversity of TexasDallas, RichardsonUSA
  3. 3.Bloomberg School of Public HealthThe Johns Hopkins UniversityBaltimoreUSA

Personalised recommendations