COVID-19: Elephant Tracks

Getting a post mentioned on Reddit causes a traffic spike:

Elephant Sighting - Reddit traffic spike
Elephant Sighting – Reddit traffic spike

It’s nothing like the bedbug impulse, though …

The bulk of the subsequent increase comes from the Fu Mask Templates, although I suspect folks aren’t looking for 3D printed stuff.

As far as my original predictions go, I’m pleased to be somewhat wrong, as the most recent data shows the effect of handwashing, distancing, and general paranoia:

COVID-19 - USA Total Cases and Total Deaths - 2020-04-08
COVID-19 – USA Total Cases and Total Deaths – 2020-04-08

The lowered slope in the Total Cases curve means the cases now increase by a factor of ten every 20 days, rather than every eight, which is a major improvement. Still, it implies whatever seems bad right now will be only 10% of the badness in three weeks.

Folks with better models than my ruler make better predictions:

They assume “full social distancing through May 2020” and, apparently, the virus vanishing thereafter.

The colored area represents the 95% uncertainty range. Among other things, we don’t know what will happen when the (unknown number of) currently infected people need (far) more medical care / equipment / resources than we have available (“open image in new tab” for more dots):

Hospital Resources - projection - 2020-04-09
Hospital Resources – projection – 2020-04-09

Given our somewhat … erratic … national leadership, keeping everybody tucked in and the economy turned off for any substantial duration seems unlikely, but there’s no other way to reduce the death toll. The vast majority of the population will not have been exposed to COVID-19 and will, therefore, remain vulnerable to any (infected-but-asymptomatic, thus untested) people arriving from other counties / states / countries.

You know what to do: stay home and wash your hands. You’re buying time for the medical folks to catch up with the situation.

4 thoughts on “COVID-19: Elephant Tracks

  1. The models I’ve seen assume two populations: infected and seriously afflicted, and asymptomatic (but infectious). This study (not going to try the original in German, summarized here with links to more detailed information: indicate that it’s not binary, but a spectrum; people who had the infection, beat it, and never saw the inside of a hospital. There have been plenty of anecdotes (is the plural of anecdote ==> data?) that a “weird flu” was going around the country, with symptoms compatible with a mild case of COVID-19).

    I’ve also seen a hypothesis that the severity of the case depends on the amount of virii encountered by the body. The asparagus farm in the NYC subways (and elevators, and tight dwellings) would be likely to maximize that viral load. Sigh.

    If the study results hold up, the likely CFR is more line 0.4%. Antibody tests are just now starting to get deployed.

    1. We’re banking heavily on the “dose makes the poison” principle, because it’s straight-up impossible to maintain perfect isolation for the next two years. Or during the waves of mass re-infection after we prematurely end the shelter-in-place regimen.

      I recall reading recently that somebody reputable looked up a generous sample of the folks who had “weird flu” symptoms early this year, tested them for the appropriate antibodies, and came up with exactly zero COVID-19 cases. It might be Littlewood’s Law at work: given a sufficiently large population, anything will happen in surprising numbers.

  2. There are also two strains of SARS-CoV-2 now, a (presumably original) Asian one, and a European one. I have read one report, not a journal and not peer-reviewed, that the European one is more virulent. (I just checked LitCovid and could not find an article supporting that. Perhaps it is in peer review.) In any case, there are 2-5 strains (, If there is differentiation in virulence, the concern is what are the implications of that for immune response and vaccines? Corona viruses don’t mutate much in the classical sense of permanent errors in transcription, but they do readily recombine: If two strains infect the same cell, there’s a mechanism where their RNA can get mixed up and produced a third.

    Prof Marc Lipsitch has a great article today discussing the complexities of immunity.

    1. Indeed, the whole recombination thing got us here in the first place: take a virus from this animal, slam into one from that critter, inhale into a third, warm gently, and shazam: epidemic!

      I fear successive waves of re-infection as “social distancing” becomes less effective with each iteration. Things could go the other way, though, if the next wave kills as many people as this one and “distant” becomes normal.

      AFAICT, getting our herd immunity up to speed will kill only 1% of the population, but we must pace the reinfection waves slowly enough to avoid clogging the hospitals as they are now; burials using front-end loaders should not become the norm.

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