Will Drexler

Research Interests: Food access, epidemiological patterns of infectious diseases, sports analytics, vaccine hesitancy, and geospatial data visualization.

Project Description: Understanding the spread of diseases has become increasingly crucial for saving lives and efficiently utilizing available resources. This GRAPH Lab project, entitled “Exploring Epidemiological Patterns of Tennessee using Interactive Shiny App Analysis Approach,” is the first version of a dashboard designed to investigate and predict influenza and COVID-19 trends in Tennessee. The dashboard was created using an R Shiny App, and it includes multiple tabs with different data visualizations, making it easier for users to navigate and find the specific information. The interactive maps and graphs in the dashboard also enable users to explore the data at different levels of granularity. The tabs contain interactive maps of case rates and case counts, along with vaccination and demographic information for each county. The primary feature is showcased under the first tab, which compares influenza disease patterns to COVID-19 disease patterns over time, with weekly influenza data dating back to the H1N1 outbreak in 2009. The dashboard allows users to explore data and make their own comparisons and analyses rather than being limited to the information presented in the original static PDF documents. This dashboard is a part of a master’s thesis project that aims to examine the spatial cross-correlation of COVID-19 and influenza in Tennessee. It utilizes various data sources, such as publicly-available datasets from the Tennessee Department of Health, Centers for Disease Control and Prevention, and the American Community Survey 5-Year Estimates spanning from 2007-2021. It was created in R, utilizing packages such as shiny, dplyr, TIGRIS, leaflet, and sf. We look forward to enabling other researchers to conduct similar research on disease patterns in the future through the sharing of this project’s methodology and data.