Abstract
Reports of coronavirus disease 2019 (COVID-19) cases began in December 2019. Soon after, the virus had spread around the world and became a pandemic. Social restrictions, quarantines, and other governmental policies in response to the pandemic altered normal operations across the world. One area significantly affected is human mobility. Typical movement patterns have been hindered by the pandemic. But inversely, mobility patterns can influence patterns of the virus. With this in mind, we created an interactive web application to visualize in near-real time the relationship between the COVID-19 pandemic and human mobility, as well as the impact of governmental policies at different spatial scales. The web application allows users to select a country at the global scale or a state or county for the USA and then displays a corresponding plot that compares human mobility to COVID-19 cases across time for the location, as well as to policy data. The application is useful for quickly revealing insightful patterns. First, the initial impact of the COVID-19 pandemic was a rather sudden decrease in mobility. Second, a relationship exists between mobility and COVID-19 offset by a lag, but that lag is not consistent over space or time. Third, spatial autocorrelation of relationship is apparent, meaning locations near each other share similar patterns. Overall, the application is a useful data visualization tool that helps uncover patterns that might otherwise go unnoticed. The application is available at this link:
https://chrischapin7.shinyapps.io/covid19_vs_humanmobility/
