Like SO WHAT -- Ain't gonna "get" CoVid

It's like riding a motorcycle or smoking cigarettes.

 

mrs. b and i think we got it in orlando, before there was much talk. but there aren't any anti body tests available yet.

 

...or driving a car, crossing the street...or one of millions of other things we ALL do daily.

 

Plz let us know when you get a chance.

Bob Wilson

 

I don't remember EVER getting a cold or flu except after being too close to someone else who had it or having been on an airplane (probably the same thing). But given the potential for severity with this virus, we take extra precautions when we go out, but we still go out and buy what we need. We wear masks, which is more for the comfort of others than for any benefit to ourselves. If someone with C-19 or a head cold or tuberculosis was to sneeze in your face, the mask wouldn't help anyway. Hence the keeping your distance part. And, we use hand sanitizer when we get back to the car and wash up when we get home. It should not be a big deal.

So far, in our county of about 530,000 people, we have 230 confirmed cases and just had our fourth COVID-19 death a couple days ago. Over the past couple weeks there have only been about 2-4 new cases diagnosed per day. We are far from business as usual, but closer to that than from an actual quarantine. By the time this is over, our immune systems will be completely atrophied and the only surviving infectious diseases will be the ones that are immune to disinfectants.

 

You mean used to.

 

Speak for yourself. Some of us still function and work for a living out there in that bad scary world.

 

Just got back from my daily 2 mile + walk. Getting ready now to go buy some grass seed and some groceries.

 

Except for the infectious disease part, of course....although some people say that second hand smoke and motorcycles represent their own societal hazards.

I’ve probably been asked 3-4 times while wearing a mask if I’m afraid that I’ll get the Covids, and so far I’ve managed only polite answers indicating that the masks only help keep the virus from spreading, and my beloved company “encourages” their use when we’re in public.

Would I personally go out for pork rinds and cheap domestic beer right now?

No.
But only because I don’t use those products,

 

I am also "essential personnel" ensuring that what we make keeps farmers production up so the next wave of suffering isn't lack of food.

But most of the things we used to do in a day are not the same.

Like wearing facial coverings, when is the last time you wore those in public, or in any setting for most?

Social distancing is another change, but allows for activities to continue .

Do your part and don't operate "business as usual". Protect the essential workers and stay home.

 

One of the highlights of social distancing is that I talk to idiots very rarely.

 

i can fix that for you

 

Regardless of the details while getting there, you're still dead in the end.

 

WAIT...WHAT! They told me if I live in a perfect bubble...I would live forever.

 

John Paling has this neat way of putting risks in perspective (taken from here, used with permission):



Copyright date on that thing is 2000, but that's ok; most of those diamonds have probably pretty much stayed put over the last 20 years. (They must have forgotten to update the copyright date when they added "Pre 9-11" for the crashing airplane.)

We had 30 confirmed COVID-19 cases on March 1st (according to JHU's US dashboard), out of a population of 330-ish million people, which would put COVID-19 roughly here:



Something to notice about Paling's chart is that it is logarithmic. Every risk column moving across is ten times the risk of the one to its left, and one tenth the risk of the one to its right.

That's handy, because pandemic spread is (until something limits it) exponential, and when you plot something exponential on a scale that's logarithmic, it all works out to a nice steady march.

We had 83,800 confirmed cases on March 26th, again according to JHU:



Relative to the 30 cases on March 1st, that's a number that was roughly doubling every couple days. That's something a non-math-geek can easily spot just eyeballing the numbers:

Code:

2020-03-26 83.8k
2020-03-23 43.7k
2020-03-21 25.7k
2020-03-19 14.1k
2020-03-17  6.1k
2020-03-15  2.9k

Shows rough doubling over gaps of sometimes two, sometimes three days. So doubling every two-and-some-change days. Good enough for a napkin. A geek could go further and give an overall doubling rate of "every 2.18 days" for that period, March 1st to March 26th.

I picked March 26th as an endpoint because that was the date by which about half the US population was covered by stay-at-homes:

Code:

millions
staying
home
  3.2   mar 15   pr                 3.2
 42.8   mar 19   ca                 39.6
 64.4   mar 21   il nj              12.7 8.9
 83.9   mar 22   ny                 19.5
115.5   mar 23   ct la oh or wa     3.6 4.6 11.7 4.2 7.5
143.97  mar 24   de in ma mi nm wv  0.97 6.7 6.9 10.0 2.1 1.8
153.6   mar 25   hi id vt wi        1.4 1.8 0.63 5.8
163.8   mar 26   co ky              5.7 4.5
170.8   mar 27   mn nh              5.6 1.4
173.74  mar 28   ak mt ri           0.74 1.1 1.1
201.54  mar 30   ks md nc va        2.9 6.0 10.4 8.5
215.54  mar 31   az tn              7.2 6.8
232.14  apr  1   dc nv pa           0.70 3.1 12.8
262.44  apr  2   me tx              1.3 29.0
297.54  apr  3   fl ga ms           21.5 10.6 3.0
302.44  apr  4   al                 4.9
308.54  apr  6   mo                 6.1
313.64  apr  7   sc                 5.1

(data from here)

After that major an intervention, of course we expect to see the spread slowing. So what I'm showing here is essentially the spread rate we had before that intervention.

To a lot of people, that plot looks like something "changed" around mid-March or so. That is, it looks kinda flat, and then suddenly commentators are saying "whoa! cases surged!" or "spiked!" or "took off!".

That's just the illusion you get any time you try to plot exponential growth on a plain scale. The scaling you need to keep the right side on the page will always squash the left side down to look flat. If you just look at the numbers, you can keep following the doubling rate right on back:

Code:

2020-03-15  2.9k
2020-03-12  1.6k
2020-03-10   708
2020-03-07   336
2020-03-05   172
2020-03-03    73
2020-03-01    30
2020-02-27    16

That's what exponential growth does. It doubles at a steady rate.

I've been starting to think that a lot of the difference in response I've been seeing and reading from different players and commentators doesn't necessarily come down to red/blue, urban/rural, or the like, but just to who is or isn't familiar with how exponential things behave. The flat-looking left side of a plot has legitimately fooled probably every person in history who looked at one without knowing better. News stories today that still talk about cases "surging" or "spiking" have just been written by people who don't know better, but should.

Now, before February 27th, the 'confirmed' number was kind of stuck at 15 for a while, doesn't hit 8 going backward until February 2nd. Back to two cases on January 25th and just the first confirmed case on the 22nd.

That's going to make the growth look slower (doubling period longer). I think that period has more to do with trying to get testing up to speed and the numbers not yet being big enough for the systematic behavior to show up above random details of who got tests on what day. But, fine, let's work out what the doubling rate appears to have been for that whole period, from the first case on January 22nd up to March 26th.

Comes to 3.91 days. We could call that a nice, conservative, outside number. Yes, it is better than doubling every 2.18 days. But for the practical impact of something doubling every n days, n being 2.18 or 3.91 doesn't paint a drastically different picture.

But the Paling risk chart isn't laid out in powers of two, it's in powers of ten. That's easy. Something that is doubling every n days is also getting another zero every n✕log(10)÷log(2) days.

log(10)÷log(2) is about 3.322, so using 2.18 or 3.91 days for the doubling time, we have 7.25 days or maybe up to 13 days for the time to cross each column of the Paling risk chart. Let's just use both:



And that right there is why this kind of isn't just like millions of other things we all do daily.

This is all done-on-a-napkin stuff. I'm plotting number-of-people-who've-caught-it (per capita) as an estimate of likelihood of catching it (which it pretty much is), but the likelihood of you catching it is probably some fraction less than one times the prevalence in people around you. It doesn't seem to be hugely less than one though, and another thing about exponential functions is any constant factor eventually stops being very significant in the big picture.

Also keep in mind that most of the other risks Paling showed on the chart are over the course of a full year. Everyone who has caught COVID-19 so far has caught it through far less than a year of sharing space with other covidians.

 

What.....no mirrors in your house ??
(Sorry, couldn't resist.)

 

or a bad strain of flu?
.

 

Seem to recall there was one of those, long about 102 years ago.

 

I'm OK. I've been drinking a glass of Clorox every morning.