Right click graphs to see them full size.
I realized that St. Patrick’s Day happened just before many states started implementing social controls. I searched for some data on the best cities to celebrate St. Patrick’s Day, under the assumption that I might find something by studying the graphs of the respective metro areas. The first yellow bar is when I projected impacts to be seen (3 weeks later) and the second wider one is the projected impact days from Memorial Day weekend.
It seemed like I might be on to something but decided to zoom out to have the entire US data set. I think I found the impact from that day.
One of the obvious cycles in the data follows a seven day pattern. My hunch is that this has to do with increased spread over the weekends, as people go to bars, restaurants, night clubs, beaches, malls, and religious services. That’s why it took some time for that pattern to show up in the data. It took a few generations of spread and amplification on the weekends to become a visible pattern.
The graph below is of the entire US, with the same yellow bars. In this one, I marked what were the peaks seen in the early data green. After the influence of St. Patrick’s Day, they are red.
The first thing to notice is that there is an initial jump (the red lines) 1-3 weeks after, that subsides for a bit, then reemerges 7 weeks after. I’m going to conjecture that the first 3 weeks are individuals who celebrated and became symptomatic. After that, the virus was circulating, but it took about 3-4 generations of spread to show up as the new peak period one day later.
What I can derive from this is that my initial estimate of cases becoming visible in the data set at three weeks seems accurate, but major changes influencing obvious changes because of multiple generations may not come into play until 10 weeks after an event.
Of course, this could simply be the natural way the disease itself works without any impact of human social conditions, but I find the data to be pretty suspicious in support of my hypothesis.