Timeseries and Patterns

Looking for Patterns

One of my first stories at KRQE News 13 was a deep dive into COVID-19 related data. At the time, the debate over restrictions — requiring masks, social distancing, etc. — was particularly heated. And a lot of people were asking: “Do restrictions really help stop infections?”

The intuitive answer was “yes” because wearing masks and staying apart should clearly reduce transmission. But I had a suspicion that just because a state issues guidance doesn’t mean citizens will follow. In other words, while the science is clear, the social implications were not.

To explore the issue, I combined data from several sources. I used Julia Raifman et al.’s database on what states implemented restrictions throughout the pandemic, combined with case and death data from the U.S. Centers for Disease Control and Prevention (CDC). After processing the data using R Statistical Computing, I was able to visualize patterns.

It’s still hard to tell exactly how restrictions impacted the death count. But it looks like restrictions didn’t always have the direct impact of reducing deaths per capita. In fact, further analysis shows that the politics of a state’s governor (keep in mind that Democratic governors tended to have more/stronger restrictions) didn’t correlate strongly with deaths.