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Using GIS for Substance Abuse Research and Intervention

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Research Methods in the Study of Substance Abuse

Abstract

This chapter explores the use of Geographic Information Systems (GIS) and Geospatial Technology (GT) to assess patterns of substance abuse. While geospatial techniques encompass a range of approaches for data collection, analysis and visualization, GIS is the platform through which data are organized and managed, analyzed for relationships across space and time, and visualized in the form of a map. Differences between vector and raster data are discussed, with vector data noted as the most common form of data used in substance abuse research. Mechanisms of data input are also discussed, including secondary sources of spatial data, geocoding, digitizing, and use of GPS receivers to collect original data. Varying geographic scales are considered, including challenges associated with working with aggregated space. Data models for spatial analysis are also explored. Lastly, a review of the extant research on geospatial approaches to understand substance abuse is presented, including exploration of emergent geospatial approaches to understanding substance use and abuse.

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Notes

  1. 1.

    The call to understand context is not new in substance abuse research (Dembo et al. 1985), however, systematically collecting and analyzing contextual data in a way that is replicable and extensible has been difficult. It is in these areas that GIS and other geospatial technologies contribute to contextual understanding.

  2. 2.

    A number of texts provide in-depth discussion of mapping and spatial analysis techniques and issues. See, for example, texts by Dent et al. (2009) and Maguire et al. (2008).

  3. 3.

    Most universities with a geography department offer GIS courses. However, GIS can also be taught in other departments as well. Check your local university or community college for GIS course availability. In addition, GIS manuals are useful to novices and experienced users alike. Finally, all makers and users of maps are advised to read Monmonier’s (1996) classic text, “How to Lie with Maps” for insight on the use and abuse of maps, including how to evaluate maps critically.

  4. 4.

    Some examples of these sources include: Atlas—The Louisiana Statewide GIS (http://atlas.lsu.edu/), Cal-Atlas (http://www.atlas.ca.gov/download.html), SanGIS (http://www.sangis.org/).

  5. 5.

    Go to http://factfinder.census.gov/faces/nav/jsf/pages/index.xhtml and then use the “Download Center” to access data tables with geographic identifiers such as tract, block group, and block.

  6. 6.

    Positional accuracy refers to the degree to which a feature’s location on the map matches its real-world location.

  7. 7.

    See, for example, article by Mazumdar et al. (2008).

  8. 8.

    A growing body of research is emerging on this approach to understand the environment–behavior nexus. See the following sources for a complete list of references and discussions of the prospects and problems of integrating sketch maps with geographic information systems to understand environmental perception: Curtis (2012), Curtis et al. (2014), and Curtis (2016).

  9. 9.

    Many websites and texts are devoted to helping users understand GPS and use it appropriately. The U.S. government has a good overview of the technological aspects of GPS: http://www.gps.gov/.

  10. 10.

    For a complete discussion of these issues, see Longley and Batty (1996) and Openshaw (1996).

  11. 11.

    For a more in-depth discussion of these issues, see Coulton et al. (2001) or Curtis et al. (2015a, b).

  12. 12.

    Through advances in tools such as ArcGIS Network Analyst (ArcGIS 10.2. ESRI. Redlands, CA), line data are increasingly being analyzed in public health research, for example with ambulance response times, or even travel patterns of the homeless.

  13. 13.

    For a more detailed discussion of KDE for public health applications, see Carlos et al. (2010).

  14. 14.

    Spatial filtering, SpaceStat; In addition, space-time clusters can be identified through SatScan; see Fotheringham (1997).

  15. 15.

    See Anselin (1995) and/or Getis and Ord (1992).

  16. 16.

    See Fotheringham et al. (2002).

  17. 17.

    See Boulos et al. (2009) for a more detailed discussion.

  18. 18.

    See Curtis et al. (2006).

  19. 19.

    Please see the following link for an overview of this process: https://www.e-education.psu.edu/geog160/node/1882.

  20. 20.

    See Mills (2009).

  21. 21.

    See Curtis et al. (2012). Google Earth, in particular, is increasing the accessibility of map use for decision-making across the sciences and by the public.

  22. 22.

    The search was conducted in June and July 2016. These databases were selected based on their representation of the most general (Google Scholar) to the most specific (PubMed) sources for this subject. Google Scholar search terms were “GIS” and “substance abuse”. However, as PubMed and Web of Science enable greater specificity in designing searches, these queries were structured differently from the Google Scholar search. In PubMed, the titles/abstracts of articles were searched for “GIS” or “Geographic Information System*” and “substance abuse”. Similarly, the following search terms were used for topic queries in Web of Science: “GIS” or “Geographic Information System*” and “substance abuse”.

  23. 23.

    It should be noted that as in all literature searches, these results are unlikely to be completely exhaustive of the subject due to limitations in the search terms. However, the number of results is appropriate for the subject area and provides a representative set for review.

  24. 24.

    One area that has received considerable attention over the years, especially from criminologists and planners, is the relationship between alcohol outlets and crime. Note that this chapter only identifies articles of this type where alcohol abuse is investigated in relation to outlet density and crime. In addition, the understanding that geography matters for substance abuse is not new, but articles were not included unless they explicitly use GIS/GT. This inclusion criterion means that studies which use maps, but without explicit mention of GIS/GT in their methods were excluded (e.g., Fortney et al. 1995, Rockwell et al. 1999).

  25. 25.

    See, for example, work by Mills et al. (2010), Curtis et al. (2010, 2013), and Curtis and Mills (2011).

  26. 26.

    See Curtis et al. (2015a, b, 2016).

  27. 27.

    ibid.

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Acknowledgements

National Institute of Justice, Office of Justice Programs. Part of this chapter was supported by Award No. 2013-R2-CX-0004, awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice. The opinions, findings, and conclusions or recommendations expressed in this presentation are those of the authors and do not necessarily reflect those of the Department of Justice.

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  1. GIS Health & Hazards Laboratory, Department of Geography, Kent State University, 325. S. Lincoln St, Kent, OH, 44242-0001, USA

    Jacqueline W. Curtis & Andrew Curtis

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  1. Jacqueline W. Curtis
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  2. Andrew Curtis
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Correspondence to Jacqueline W. Curtis .

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Editors and Affiliations

  1. Department of Health Policy and Management, College of Public Health, Kent State University, Kent, Ohio, USA

    Jonathan B. VanGeest

  2. Survey Research Laboratory, Department of Public Administration, College of Urban Planning and Public Affairs, University of Illinois at Chicago, Chicago, Illinois, USA

    Timothy P. Johnson

  3. Department of Health Policy and Management, College of Public Health, Kent State University, Kent, Ohio, USA

    Sonia A. Alemagno

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Curtis, J.W., Curtis, A. (2017). Using GIS for Substance Abuse Research and Intervention. In: VanGeest, J., Johnson, T., Alemagno, S. (eds) Research Methods in the Study of Substance Abuse. Springer, Cham. https://doi.org/10.1007/978-3-319-55980-3_9

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