Johns Hopkins University’s Whiting School of Engineering & Gravy Analytics: Location Analytics for COVID-19 Modeling
The Problem: Need for a Public Education Tool on COVID-19
Anton Dahbura, an associate research scientist at JHU’s Whiting School of Engineering, wanted to create a consumer-friendly online simulator that would help the general public to understand the value of coronavirus-related public health interventions.
The Solution: Gravy’s Observations Data for COVID-19 Modeling
To create Anytown USA a platform that would allow any user to simulate the spread of the virus throughout a small town, JHU researchers needed a trusted dataset to model COVID-19 transmission patterns. By using Gravy’s Observations data, they were able to understand how people living in an average American town move around.
“Gravy Analytics’ data has helped us analyze population movement with greater resolution, factoring in devices’ locations and time spent in different areas. Its filtering techniques, like its flags indicating when devices are likely driving or are spoofs, further increase the accuracy of our clusters by removing extraneous datapoints.”
The Findings: COVID-19 Mitigation Strategies for Every Town
The Anytown platform demonstrates that communities shouldn’t rely on a one-size-fits-all approach to the coronavirus pandemic.
Want to learn more?
Download the full case study to learn how JHU researchers used location analytics to simulate the spread of COVID-19 in the Anytown platform.