The course will discuss the use of spatial epidemiology and Geographic Information Systems (GIS) to better understand the spatial distribution of Hepatitis C Virus (HCV) with the goal of informing future public health interventions. The course material draws from existing literature to explore a variety of GIS and spatial analytical methods for HCV research. The course contains 3 lessons, each 2 hours in length. To learn more about the Jurisdictional Vulnerability Assessment project, the toolkit can be accessed here.

Course speakers:

• Thomas Stopka, PhD, MHS, Associate Professor, Tufts University Department of Public Health and Community Medicine
• Shikhar Shrestha, MS, PhD, Postdoctoral fellow, Tufts University Department of Public Health and Community Medicine
• Jennifer Pustz, PhD, MPH, Assistant Researcher, Tufts University Department of Public Health and Community Medicine  

Overall course objectives:

1. Create descriptive, hypothesis-generating HCV maps
2. Calculate spatially-oriented variables in GIS that are HCV-relevant
3. Conduct spatial epidemiological and geostatistical analyses to test hypotheses related to HCV risk

Lesson 1: Using GIS to gain preliminary understanding of spatially-oriented HCV data

This lesson discusses common uses and applications of GIS and spatial epidemiology in public health. This lesson also provides a basic overview of spatial epidemiology as well as a demonstration of GIS software including ArcMAP and ArcGIS Pro.

By the end of the session, participants will be able to:

1. Understand the basics of GIS and spatial epidemiology
2. Discuss applications for GIS to study HCV
3. Discover basic mapping and spatial analysis techniques

Lesson 2: GIS applications to calculate spatially-oriented variables

This lesson discusses calculation of variables including distance from homes to HCV services and small area measures of HCV risk and health disparities, in addition to common interpolation methods. This lesson also includes a demonstration on creating simple heat maps and drive-time buffers in ArcGIS pro.

By the end of the session, participants will be able to:

1. Demonstrate how to calculate and create spatially-oriented variable in GIS applications
2. Discover tools and approaches that facilitate creation of spatial variables

Lesson 3: Spatial epidemiological and geostatistical methods

This lesson discusses geostatistical analysis and spatial epidemiology including: spatial autocorrelation, hot spot cluster analysis, spatial regression, and spatiotemporal cluster analysis. This lesson also includes a demonstration on calculating spatial autocorrelation as well as performing a spatial regression in ArcGIS.

By the end of the session, participants will be able to:

1. Understand more complex GIS and spatial epidemiological approaches that facilitate identification and characterization of hotspot clusters
2. Understand the uses and applications of GIS and spatial epidemiology in HCV surveillance, research, and vulnerability assessments

Acknowledgement statement:

This product was developed by CSTE and Tufts University. The vulnerability assessment project and the associated online technical assistance resources was funded through CDC’s National Center for Injury Prevention and Control, Cooperative Agreement Number 1NU1ROT000018-01-00. The findings are those of the consultants and do not necessarily represent the views of the Centers for Disease Control and Prevention.

 Competencies:

• 1.2 – Data Analytics and Assessment Skills – Describes factors that affect the health of a community
• 1.6 – Data Analytics and Assessment Skills – Manages data
• 1.7 – Data Analytics and Assessment Skills – Analyzes data
• 1.8 – Data Analysis and Assessment Skills – Interprets results from data analysis