Overview
Explore spatial data analysis techniques for public health in this 55-minute NAM Claytor-Woodard Lecture delivered by Monica Jackson from American University at the Virtual 2022 Joint Mathematics Meetings. Delve into disease surveillance, data sources, outbreak analysis, and various types of spatial data. Learn about spatial correlation, global patterns, and data collection methodologies. Examine the results, limitations, and future work in this field. Gain insights into research training, choosing topics, and receive valuable advice for students interested in spatial data analysis for public health applications.
Syllabus
Introduction
Outline
Background
Disease Surveillance
Data Sources
Outbreaks
Types of Spatial Data
Interest in Spatial Data
Correlation
Scatter Plots
Spatial Correlation
Global Patterns
Spiral
Data Collection
Methodology
Methods
Results
Limitations
Future Work
Research Training
Sponsors
Questions
Regions
Choosing Topics
Common Mistake
Advice for Students
Taught by
Joint Mathematics Meetings