Exploratory Analysis of Disease Data & Introduction to UNC’s GIS Reference Library Prepared originally by Kristen Hampton Updated and maintained by Ben Allshouse and others

Types of Investigations Disease mapping Disease mapping –Summation of spatial and spatio-temporal variation in disease risk Geographical Correlation Analysis Geographical Correlation Analysis –Relationship between heath outcomes and environmental risk factors Disease clustering Disease clustering –Raised incidence of disease in an area –Non-random spatial pattern of disease relative to non-cases

Disease Mapping (Zucker, J.R. Changing Patterns of Autochthonous Malaria Transmission in the United States: A Review of Recent Outbreaks. Emerging Infectious Diseases. 1996;2(1):37-43.)

Geographical Correlation Analysis (Glass, G.E. et al. Infectious Disease Epidemiology and GIS: A Case Study of Lyme Disease. Geo Info Systems. 1992;2(10):65-69.)

Disease Clustering GCA – Point Source Study Hypothesis of disease etiology Hypothesis of disease etiology Layers Layers –Roads –Pumps –Case event data John Snow’s 1854 Map of Cholera and the Broad Street Pump (McLeod, K.S. Our sense of Snow: the myth of John Snow in medical geography. Social Science & Medicine. 2000;50: )

ID Application of GIS “Continuum of diseases” “Continuum of diseases” –Highly applicable to ‘environmental’ diseases, such as malaria and other vector-borne diseases –Limited applicability to non-communicable diseases, such as MS, with weak or non-existent environmental components –In between are HIV and other STDs with moderately strong links to the environment (Tanser, F.C. et al. The application of geographical information systems to important public health problems in Africa. Int. J Health Geographics. 2002;1:4.)

I-95 Syphilis Study (Cook et al. What’s driving an epidemic? The Spread of Syphilis Along an Interstate Highway in Rural North Carolina. Am. J of Public Health Mar;89(3): )

I-95 Syphilis Study (Cook et al. What’s driving an epidemic? The Spread of Syphilis Along an Interstate Highway in Rural North Carolina. Am. J of Public Health Mar;89(3): )

Issues Confounding Confounding Resolution / Aggregation level Resolution / Aggregation level –Patient confidentiality –Spatial accuracy –Ecological Fallacy (individual v. group) Temporal relationship between exposure and disease Temporal relationship between exposure and disease

Exploratory Analysis of HIV in North Carolina Screening and Tracing for Acute HIV Transmission (STAT) Screening and Tracing for Acute HIV Transmission (STAT) –Collaboration between UNC-CH CFAR and NC DHHS –Developed a system using HIV biomarkers to determine the time of transmission (incident cases) –All HIV test samples sent to state labs are staged with the STAT protocol Records are mapped according to self-reported zip code of residence Records are mapped according to self-reported zip code of residence –Sample data for 1 year: 110,000 mappable records 500 prevalent cases 500 prevalent cases 100 incident cases 100 incident cases

Goal Given a table of patient records with disease X in North Carolina, create choropleth maps of Given a table of patient records with disease X in North Carolina, create choropleth maps of i. case count, ii.density of cases per square mile, and iii.population density (persons per square mile) by zip code, shown with major highways.

Road Classification Major Highway No. of Cases

Information Needed Tabular Disease Data (Given*) Tabular Disease Data (Given*) –*.dbf (dbase) or *.txt (text) file formats GIS Data GIS Data –Polygon shapefile of NC zip codes –Line shapefile of NC roads Attribute Data Attribute Data –Zip code area and population * All disease data introduced in this exercise is fictional and for demonstration purposes only.

Resources Amanda Henley Amanda Henley GIS Reference Librarian, Davis Library ArcGIS desktop Help ArcGIS desktop Help

Data Confidentiality Health data is confidential Health data is confidential –Issue of privacy for health data –As a researcher you must seek training about, and proactively protect data confidentiality Environmental data is confidential as well Environmental data is confidential as well –Privacy issue also applies to any environmental data that can be associated with an individual How will you protect data confidentiality in this course? How will you protect data confidentiality in this course? –Identify data that might be confidential (address, etc.) –Take action to protect it (do not send it to others, do not discuss it or use it in a way that would allow others to identify/target individuals, erase the data after you use it, always ask yourself what else you can do)

Exercise Handout Handout –Searching UNC’s GIS Database Additional Exercises Additional Exercises –Adding X,Y Coordinates of Polygon Centroids –Creating Raster Density Maps from Point Layers –Geocoding a Table of Addresses