My data comes from Bing's COVID tracker. I prefer to focus on active cases, since you can't be infected by people who have recovered. However, I noted earlier that the recovery data is not very reliable. First, not every county's recovery data is reflected in Bing's tracker. The data that is reported appears to be cumulative recoveries rather than daily recoveries. That's fine, but on some days, the cumulative total of recoveries goes down - which should be impossible. It can't be daily recoveries because the sum of them all eclipses the total number of cases - also impossible.
Instead, I focus on total confirmed cases. Since the virus spreads exponentially, it's best to take logs (see my explanation in an earlier post). In the graph below, "logC" is the log of confirmed cases and "t" is time. The rapid growth slowed around late March and early April. It continued to slow for a while until the very end of the graph. It's hard to see, but that's why we rely upon statistical tests rather than just eyeballing pictures.
The tests found that there were 6 different periods. In each period, the slope is significantly different from the previous period. For the first 5 periods, the slopes were getting closer and closer to 0. That's a good thing. It means that the disease's spread is slowing down. Unfortunately, Period 6 (June 21 - present) is different. The slopes for Periods 5 and 6 are circled in the picture below.
The slope is about the same as it was in Period 4, which was mid May. It's true that testing has expanded. This means that we are detecting more cases than before. However, it does not entirely explain the increase. The expansion in testing started well before June 21. I don't know if new lockdowns are justified. The benefits of flattening the curve have to be weighed against the economic costs. I'm working on a research project to address this, but progress has stalled. In the meantime, I hope you're staying safe and healthy.
Thanks Matt
ReplyDeleteI enjoyed reading about the slope changes.
ReplyDeleteFang