Morteza Karimzadeh: "Alright, hello! my name is Morteza Karimzadeh, I'm an assistant professor of geography here at CU Boulder. We do a lot of research using open geospatial data [and] I'll show you an example of research on the mitigation policies implemented during COVID-19 with increased social distancing.
"So the big research question we're asking is that "Are localities in the U.S. mitigating local outbreaks with (temporary) increased social distancing?" Specifically, we are looking at the counties in the U.S. and for that we need a lot of data, all of it for free and openly. The case rates for COVID-19, we can get that from public health departments across the country. Then we also need mobility data, aggregated cell phone data that shows how many people in this or that county moved or increased or decreased their movement.
"We also need to look at some controlling variables, including unemployment and median household income. Well, if people are not going out as much, is it because they're unemployed or is it because they tend to occupy jobs that allow them to work from home. We get this data from the Bureau of Labor Statistics and the U.S. Census Bureau on the American Community Survey.
"As an example, we're looking at social distancing in May of 2020, we see the Pacific Northwest, the Bay Area, the eastern Tri-states staying at home more rigorously than, let's say, some of the Midwestern counties. But is that a function of unemployment or unemployment or local infection rates? For that, we actually divided our data into the regional pacts and alliances that were formed as a result of the COVID-19 pandemic.
"We can see the eastern pact states stayed at home, way more compared to, let's say, the Midwestern pacts or the unaffiliated states. But the Sunbelt pact states that were also not affiliated did not go out as much as the Midwestern pacts. However, how did that compare to local infection rates? Well, if we actually plot our data, the movement data as a function of local infection rates, we see that there is a huge increase in social distancing in the Eastern pact states compared to, let's say, the Sunbelt states even though they, in fact, did not stay at home. It was not as much as it would be as a response to local COVID-19 infection rates. As a result, we saw a huge outbreak in the months of July and August in the Sunbelt states.
"So this is just an example of how we use open data in our research. It helps us with responsive research. We and a bunch of other researchers were able to get our hands on this data really fast and help influence policy to mitigate the pandemic. It's also replicable--other researchers can confirm the veracity of our findings. It helps us foster collaboration without having to worry about data share agreements and institutional boundaries, the data is open and out there for free. That really also helps us be teaching. We've been using these data sets in our teaching for predictive modeling of COVID-19 in class and students really enjoy working with up-to-date data that is readily available.
"That was my presentation today. I hope students if they occupy jobs in the future, they can advocate for making the data available openly to the public. Good luck!"
