If you look at the graphs from an epidemiologist’s perspective, you’d conclude that the epidemic has about run its course. We had two earlier small spikes, where we took massive, unprecedented measures to try and reduce the spread. That eventually failed and we got the huge peak this winter. Now the numbers are plummeting, and the curve looks like the plot of almost any generic epidemic that’s waning because herd immunity is setting in.

And the same basic shape shows up in all the hard-hit countries. But I suppose the remaining question is whether we’re looking at different subsets of the populations of those countries (urban vs rural, or service workers vs retirees, etc). Spain had three distinct spikes, so is this spike the last one, and what was responsible for the first two?

I’m honestly perplexed by the epidemic’s behavior. I assumed (and I was massively wrong) that once a significant percentage of the population (say, over 10%) had immunity (such as via having had the virus) that later waves would be a bit smaller, not a lot larger.

If I read the CDC page right, we have not yet hit 10% of the population in the U.S.: 28M total cases out 331M people. (We’ve administered 65M doses, but the last big wave happened before that.) I’m not sure how that compares to worldwide: Worldometers says there have been 112M cases worldwide; if we assume those are just diagnosed cases then maybe the true number is 1.1B (pulling a factor out my hat?), which would be about 15%.

My take is that Covid-19 is just more of a problem in the winter, just like everything it’s similar to. When it showed up last winter, we locked everything down, forcing it to bide its time until we became exhausted, but by then it was spring or even summer.

But the hiatus gave it time to mutate a lot. If the vaccines are effective against the new variants, this last wave should really be the last. If they aren’t, expect another big wave in the spring.

The problem with relying on CDC stats is that (And even the CDC has said so) they only count tests, and per serological antibody studies the real number of infected is between 2x and 3x that (for the US). So, conservatively, we’re well over 10% based on positive tests plus the extrapolation.

That’s how I came to my conclusion that the “third wave” would not reach the scale of the prior ones; taking 10% of the population out of the equation should have lowered the R0 (transmission rate) by more than 10%.

Very clearly, I was wrong. I’m just trying to figure out why.

My guess is you’re right on the mutation issue. Several of the variants seem to have higher R0 (sometimes listed as Rt) so, that could have done it.

If you look at the graphs from an epidemiologist’s perspective, you’d conclude that the epidemic has about run its course. We had two earlier small spikes, where we took massive, unprecedented measures to try and reduce the spread. That eventually failed and we got the huge peak this winter. Now the numbers are plummeting, and the curve looks like the plot of almost any generic epidemic that’s waning because herd immunity is setting in.

And the same basic shape shows up in all the hard-hit countries. But I suppose the remaining question is whether we’re looking at different subsets of the populations of those countries (urban vs rural, or service workers vs retirees, etc). Spain had three distinct spikes, so is this spike the last one, and what was responsible for the first two?

I’m honestly perplexed by the epidemic’s behavior. I assumed (and I was massively wrong) that once a significant percentage of the population (say, over 10%) had immunity (such as via having had the virus) that later waves would be a bit smaller, not a lot larger.

If I read the CDC page right, we have not yet hit 10% of the population in the U.S.: 28M total cases out 331M people. (We’ve administered 65M doses, but the last big wave happened before that.) I’m not sure how that compares to worldwide: Worldometers says there have been 112M cases worldwide; if we assume those are just diagnosed cases then maybe the true number is 1.1B (pulling a factor out my hat?), which would be about 15%.

My take is that Covid-19 is just more of a problem in the winter, just like everything it’s similar to. When it showed up last winter, we locked everything down, forcing it to bide its time until we became exhausted, but by then it was spring or even summer.

But the hiatus gave it time to mutate a lot. If the vaccines are effective against the new variants, this last wave should really be the last. If they aren’t, expect another big wave in the spring.

The problem with relying on CDC stats is that (And even the CDC has said so) they only count tests, and per serological antibody studies the real number of infected is between 2x and 3x that (for the US). So, conservatively, we’re well over 10% based on positive tests plus the extrapolation.

That’s how I came to my conclusion that the “third wave” would not reach the scale of the prior ones; taking 10% of the population out of the equation should have lowered the R0 (transmission rate) by more than 10%.

Very clearly, I was wrong. I’m just trying to figure out why.

My guess is you’re right on the mutation issue. Several of the variants seem to have higher R0 (sometimes listed as Rt) so, that could have done it.

You’re trying to make sense of garbage data.