Thanksgiving and Christmas holiday were both events where many people that were diligent about quarantine protocol for the past year decided to break protocol "just this once" because it involved the two primary holidays for gathering with loved ones.

I think it has been shown that standard corona seasonality shows the same shape of all case loads we have seen?

That is, most of the recovery we saw last year going into summer could potentially be explained by regular cycles of similar viruses in the areas. The impression being that that could also explain or current recovery.

It is not an argument against vaccination. And I haven't seen people pushing we have heard immunity, yet. But the stark drops we are seeing do seen surprisingly sharp.

"the stark drops we are seeing do seen surprisingly sharp"

Surely that suggests an unnatural cause, such as millions of vaccine doses being rolled out, specifically targeting the most vulnerable (LTC residents) and those most likely to catch/spread the virus (medical profession, first responders, front line workers)?

The argument is, if that were the case, it would be sharper than the natural charts of corona viruses otherwise.

To be clear, I first saw this pushed by some epis on Twitter as caution to get to hopeful that we are seeing the vaccines as a resounding success so early in their rollout. It is expected that the vaccines are needed, but the dramatic drop was pushed as likely unrelated.

I will try and dig up the tweets. Could be they have changed their minds with more data.

Also, my first sentence was a question as I am not sure that is what the opening post meant.

Edit: https://twitter.com/jbarro/status/1363866144029949952?s=19 had a recent discussion where this came up. (Looking for epis in this one, but not finding them.:( )

Edit: https://twitter.com/EricTopol/status/1363551912021221377?s=1... is a look at a drop without vaccines

Could it be that there's a strain that results in largely asymptomatic cases and there is not enough data on those people? That could result in a decline now due to competition, or the slope of the line is historically wrong due to invisible statistics.

I know there has been some trouble identifying antibodies in people who were exposed months ago. So if you aren't really sick, you only get counted (maybe) if someone in your circle gets really sick.

For myself? I have no idea. I think this would fall under a general data quality concern.

I can say I have not seen this brought up too much on Twitter. With the caveat that I am not following everyone. :)

I do know that sometimes graphs with weird dog-legs are caused by either graphing the wrong derivative[1], or because there are more populations and someone is either being devious or is unaware.

[1] Developers are by and large flummoxed by S-curves for progress. An S curve for distance maps to a bell curve for velocity. If the sums don't make sense, look at the rates, or the rate of change. Don't keep staring at the S trying to fit trend lines.

Where are we at in mapping genotypes of the most affected and the superspreaders?

Perhaps exposure has reached saturation among certain populations.