When the COVID-19 stay-at-home orders began, Bradley Baker and Daniel Funk wanted to know how people were adapting their exercise routines to abide by social distancing. Since no single method would accurately estimate the entire population’s exercise, Baker, Funk and their colleagues used three different data sources to piece together a picture. 

Using big data measuring hashtags on social media, search engine query results and smartphone tracking, they found a large spike of in-home workouts and park use following the stay-at-home order. 

In the event of a similar quarantine period, this data can inform the public what times of day parks are most occupied. It can also help supply chain managers of exercise equipment to estimate how much increased demand they can expect for their products.