Mending…

Diet: closer to normal; salad with yogurt at dinner was probably unwise (some ab pain)

Workout: reduced: 5, 5, 10 lousy pullups, 5 better ones, 5 chins

abs…chest taps from knees.
push ups: 20, 20 (feet on porch, on stool)

downstairs: 3 sets of 10 x 27 shoulder presses

deadlifts: 10 x 134, 10 x 184, 3 x 224 (pain free, but was starting to labor)

I am not back yet.

COVID

I remember saying last year, “if I were 40, I’d mask up and make some games”. Well, it turns out that now that I am vaccinated, my death risk is like an non-vaccinated 40 year old! 80 year old who is vaccinated has the death risk of a non-vaccinated 50 year old. You still need to be careful.

In non-log scale form:

As far as going to the game, this is what the experts say (and I agree with most: mask up and go)

Back to vaccine efficacy WRT hospitalization: I showed the non-age adjusted calculations which gives 70-77 percent according to the various data I saw. Now if one adjusts for age:

Umisef (Twitter handle) did the crunching.

Some videos

On the verge of getting going…I’ll have to make some progress on my two papers. This will require some weekend/evening work, I think.

Vaccines:

I used the fact that our area is 50 percent vaccinated to do some efficacy calculation: efficacy with respect to hospitalization is about 77 percent..not taking into account risk groups.

So, no, “breakthrough hospitalizations are not “rare.”

Workout notes: kind of sore glutes so no cycling or walking today; (though forgetting my keys did help me make the campus trip and 4 flights a 3’rd time)

Pull ups (60 reps, 3 sets of 10, 1 set of 10 singles, 4 sets of 5), push ups (25, 25, 20 with legs up), rehab, curls (3 sets of 10), rows (3 sets of 10..lighter weight), seated presses (10 x 44, 8 x 66..pathetic)

COVID update: how I see it

This was posted on my FB:

My updated COVID post: (thoughtful, respectful responses are welcome, even if you wish to disagree with some of these points)

1. Vaccines: cases. We are seeing some interesting data about how well vaccines prevent infection, hospitalizations and deaths. Some of the stats are misleading. “The reported share of COVID-19 cases among those not fully vaccinated ranged from 94.1% in Arizona to 99.85% Connecticut.”(reference in comment 1) The problem here is that this just reports “total unvaccinated who got infected”/total who got infected” and this includes cases that occurred when vaccines were just getting going.

A more useful stat would be “infection rate of unvaccinated” vs. “infection rate of vaccinated” IN THE SAME location (don’t compare Vermont to Arkansas” and the first figure I show does that in San Diego County. It appears that in a similar situation, an unvaccinated person is about 9 times more likely than a vaccinated person to get infected.This area: 18 cases per 100,000 in a week for unvaccinated vs. 2 per 100,000 vaccinated. In an area with 100000 people, and say, 60 percent vaccinated, this would be a case rate of (.6)(2) + .4(18) = 8.4 per 100000, with 23.8 percent of cases coming from vaccinated people.

2. However, vaccines are even much better at preventing hospitalizations and deaths. Example: of the 125000 breakthrough infections recently recorded, there were 1400 deaths. That is 1.12 percent. But given that one has a much lower chance of even being infected to begin with, that is outstanding protection against death. The US ratio is 1.74 percent for all cases (vaxxed and unvaxxed)

3. Masks and spread (see reference in second comment)It turns out that the spread is primarily aerosol. It was first thought to be droplets because the “droplet” spread model fit well for reasonably ventilated spaces. But for poorly ventilated spaces, it appears to be aerosol, which means that one can get infected even if one is well away from the infected individual.But the big deal is that, formerly, it was though that aerosol droplets were 5 microns in size or less; it turns out that it is about 100 microns or less.So, as before, masks work to keep the infected from spreading it AND a good mask does provide extra protection for the non-infected as well, even in this aerosol type situation.

4. Delta is much more infectious; a brief encounter can induce an infection (not as true with the previous variants) So it isn’t surprising to see cases go up so rapidly.5. A vaccinated person who gets infected carries about the same load as an unvaccinated person. Vaccines reduce the spread as a vaccinated person is less likely to get infected. My own practices:1. I mask outdoors (2 layer fabric or better) if I will be around people (say at a game concourse, or if some are sitting somewhat close to me..often not the case 2. I use a special 3 layer mask indoors for the gym (my two gyms have good ventilation, high ceilings, and are often not crowded3. I use KN 95 for other indoor things where I am around people I don’t know.4. I avoid excessively crowded things (Chiefs games are not a problem)

5. I don’t mask for small gatherings of known, trusted, vaccinated people who are asymptomatic. I do isolate from infected people.

Hope: we ARE starting too see more people getting vaccinated.

Division, mistrust and difficult to deal with data

Sadly, COVID measures have become part of politics and that is deeply unfortunate.

Yes, smart, informed people can disagree on cost-benefit analysis; after all, I take just that sort of analysis when I decide on whether to go to a yoga class, ball game, or even when I decided to go to “in person” teaching last year (following the vaccination of my higher risk wife).

But some things really are black and white.

The trouble is, “black and white” doesn’t mean “easy to understand.” For example, take the issue of how effective masks are at “preventing infecting the user” of said masks. There was debate over “droplet spread” vs. “aerosol spread”, with the latter having much smaller droplets. But, as we see:


“According to them, particles bigger than 100 microns sank within seconds. Smaller particles stayed in the air. Randall paused at the curve they’d drawn. To her, it seemed to foreshadow the idea of a droplet-aerosol dichotomy, but one that should have pivoted around 100 microns, not 5. “

What this means: yes, aerosol transmission of COVID is real..it is airborne and can easily defeat the 6 feet distance in poorly ventilated spaces. But the droplets are still big enough for a mask to be useful in mitigation effects.

Then there is the issue of vaccines, and what does it mean if there are a large number of breakthrough infections?

This article looks at data from states that measures breakthrough infections:

Almost all (more than 9 in 10) COVID-19 cases, hospitalizations, and deaths have occurred among people who are unvaccinated or not yet fully vaccinated, in those states reporting breakthrough data (see Figure 2).

BUT…how far back does this data go? Remember that vaccines started in mass in January, often with priority to those in certain groups. So of course, the “vaccinated vs unvaccinated” numbers would be lopsided during this time. And delta has just arrived here. That is, what would “cases in the last 1-2 weeks of July” look like? Remember this:

“Nearly three out of four people (346 of 469) who tested positive for COVID-19 in a Massachusetts outbreak were fully vaccinated, according to data released by the CDC Friday.

This is post-delta and includes a population with high vaccination rates.

I hasten to point out this was a mass gathering event, and that vaccines almost certainly kept the total number of who would become infected much lower (I’ve heard 5 times lower) than they otherwise might have been. And few of these ended up in the hospital..that too is important.

Evidence: in San Diego County, the unvaccinated COVID rate is 18 per 100,000 whereas it is 2 per 100,000 for the vaccinated.

I am “Mr. Get the Damned Shot”..make no mistake about it. But honestly and accurately interpreting the data is not that easy.

Protecting against what might be unlikely to happen

I remember the 2010 midterm elections; the Democrats took a beating. Some of it was some districts that were won in 2006 “coming back home” to the Republicans. But some of the losses were due to the ACA being passed.

So, what exactly did the ACA do? Who really benefited from it?

Here is a simple list.

Roughly, Medicaid was expanded and there was now coverage for preexisting conditions; in the past, you could be denied coverage or, if you got really sick, your coverage could be rescinded. Insurance companies claimed that happened only to a small percentage of policies (0.5 percent) but was reasonably likely if the bill reached 30,000 or more (50 percent chance).

The ACA did not allow junk plans to qualify and it did end the practice on setting limits for covering chronic conditions.

And yet, members of Congress who supported the ACA paid a big political price.

Why?

Here is my opinion: most people don’t need Medicaid and most people will NOT get extremely sick, at least not before Medicare starts. Things like cancer, on the average, tend to be old people’s diseases. (Yes, I know all to well non-elderly people die from this too, but the percentages tend to be small)

Junk policies: you tend to find out they are junk when you really need them.

So, it appeared to many that the ACA raised premiums for no additional benefit; you only saw the benefit when something went really wrong.

I think we are seeing a similar dynamic with respect to the COVID response. Yes, our hospitals are filling up and our health care workers are way overextended. But that is invisible to many of us..because:
1. Many who get COVID recover after a while; only a relatively small percentage die

2. Those who get very sick and suffer from longer term effects are still on the order of 10-20 percent of all who get it (and yes, I know one of these: healthy fitness buff female in her early 40’s; she is STILL struggling with the after effects after several weeks)

3. You can engage in non-recommended behavior and still be unlikely to get it, on the first few episodes. Think of it this way: if a type of behavior carries a 1 percent chance of getting you infected, the average number of times it takes to get infected is about 100 ; so you’ll probably get away with it several times. (I just made these numbers up for demonstration purposes)

Bottom line: taking precautions vs. COVID is really guarding against a low probability event (low in any given situations) and that is difficult for people to wrap their heads around.

Here are some handy charts and risk assessors. Note these are from October and November 2020; the risks have gone up since then.

Covid: our sorry response.

There is plenty of blame to go around. One is our tepid government response:

“The truth, as Covid-19 has shown us, is this individualistic approach doesn’t work well for public health (even if it does serve us well in other areas). The alternative to not taking collective action is more death. The countries that have done the best against Covid-19 — including Australia, New Zealand, South Korea, and, to a now lesser degree, Germany — all approached the issue collectively, leveraging government aid and public health systems to let people stay home without losing as much income or health insurance, to test and trace infections, and, when necessary, to close down to stop the spread.”

Individual response? Sure, we were pretty bad here but:

“Despite that, officials across the country have by and large resisted shutting down again. Many of them, instead, have cited another culprit for Covid-19 spread: private gatherings. New York, for example, put out a PSA to stop “living room spread,” and the state published data suggesting households and private gatherings are driving 74 percent of coronavirus spread.

It’s true private gatherings and households are driving some transmission. Most experts agree Thanksgiving dinners likely led to a surge on top of a surge, and similar Christmas and New Year’s events likely will too.

But that’s why at least some experts believe there’s a need for more focus on systemic action, not the individualistic approach. “People, in general, are horrendous risk assessors — we’re awful at assessing risk,” Daniel Goldberg, a medical historian and public health ethicist at the University of Colorado, told me. “I hate to say people can’t be trusted, but.”

There are other problems with this framing. For one, the New York data doesn’t separate within-household transmissions from social gatherings — so the 74 percent figure includes someone spreading Covid-19 to the husband he lives with (not as avoidable) and someone spreading the virus to someone he invited over for drinks one night (very avoidable). This also only includes the cases that New York could actually contact trace, and it’s much easier to trace transmission between family and friends in a household than strangers in a bar.

The big problem, though, is that there’s nothing unusual about Covid-19 spreading among people who live together. It’s typical for the bulk, even the majority, of the transmission of any disease to happen within households. If you’re infected, the people you live with or come into close contact with at home are simply likely to get it too. That’s how pathogens work. What matters most, though, is where that virus originated from in the first place.

To put it another way: People couldn’t infect others in their homes if they hadn’t picked up the coronavirus in bars, restaurants, or other public spaces. So if these places weren’t open, individual choices to gather — including over Thanksgiving and Christmas — would be of far less concern. There would simply be much less virus out there jumping from person to person.”

Yes, the onus is on us when the government is so weak, but then again, people aren’t going to follow directions, though it might be easier to do so if the government, well, plaid businesses to stay closed and payed people to stay home.

Of course, too many “leaders” set dreadful examples.

And, this kind of thing sickens and kills remotely. If you need a spreadsheet to see it, your emotional response won’t be as strong.

But the vaccines are on the way. That is great news, but we’ll still need to social distance and wear masks for a while. Why? Well, if a vaccine is 95 percent effective, it means that one is far LESS likely to get sick with an exposure. But if exposure goes up, that increases the chances of getting sick. The idea is that we need BOTH less vulnerability to getting sick once exposed AND less exposure.

Too many Americans have this idea that measures such as masks and vaccines are perfect instead of risk mitigators. (witness the stupid “why do you care if I am not wearing a mask if you are wearing one” remarks).

There is good news though: fewer new cases today than in the past few months; hopefully this is not mere “statistical noise.”

Trying to figure it out

Ok, the glute pain sort of came back around mile 3-ish..some tingles..yes, this was the day after deadlifts (2 sets) but I didn’t do the “deadlift stretch” either that I did on Tuesday. But it wasn’t bad; just annoying.

I did 3 loops of my course (about 1:31:30 at the end of 3 loops; 30:20, 30:20, 30:50 for each 2.1 mile loop; last mile was a slacker 15:17 mile as I was tired and was just ready to go through the motions.

Still, my virtual FANS 24 hour walk: 7 hours, 3 minutes for 27.3 miles. Yeah, that is pretty bad for a race but what the heck..this is really a participation thing.

COVID19: nah, our country isn’t taking it seriously enough:

Exponential growth is tough for people to wrap their heads’ around:

No, young people will NOT do “social distancing” (not enough of them anyway)

And in Ohio, one person going to church spread it to 91 others. And given a 1 percent mortality rate and a 20 percent hospitalization rate..you do the math. He probably killed someone.

Garmin vs. Strava distance

My workout, which I was pleased with, is at the end.
But with Garmin being down due to a ransomware attack I got a chance to see what Strava would do with the same data points that Garmin connect uses.

This is the course in question. On Thursday, I did this course 3 times then a bit extra. The Garmin measured it as 6.3 miles and Strava got this at 6.4 with the same data points that the Garmin used.
Here is the Strava output, which includes the extra partial loop.

The time before, Garmin measured these two loops as follows:

Strava gave me 4.3 on the same data:

Now look at today’s walk, where the Garmin and Strava got the same mileage with the same data points:

6.22 (which is what the Garmin showed).

So, why the difference?

(yes, this is based on only a few outputs)

First note that there was a time when the outputs were all but identical. That tells me it is NOT “round off” error (e. g. one program carrying more digits than another).

But note when I had a different number: the lines are all “wiggly.” Reason: the two that were different were weekday morning walks; there was much more traffic. I made course corrections to avoid other runners, pedestrians and vehicles on the road.

Today’s trek was on a less crowded day: note the lack of “wiggles” in my path.

My inference: the difference is in how the algorithm connects the dots. First of all, each “dot” is really just an intersection of lines from different satellite signals and those lines of intersection form a polygon rather than an exact point.

The centers of these “polygons” formed by the signal lines determine your position points. So, what to do with these position points?

The crudest way is to draw a straight line path between these points (black). One can select the points in batches and fit different sorts of curves by either a spline or by a least squares principle.

Here, I approximated paths by cubic splines between each group of 3 points and one that uses all 5 points (but doesn’t quite cut through all of them.)

But one gets different distances when one uses a different “curve fitting” algorithm, and it is my guess that Strava algorithm fits curves through more of the points than the Garmin algorithm. And the difference is less when the curve has less “wiggle” to it (in math terms: smaller magnitudes for the second derivative).

Anyway, that is my guess.

My workout: I warmed up my glutes and back..(15 minutes)

Deadlifts (low handles, trap bar): 10 x 134, 10 x 184, 5 x 228, 3 x 250, 5 x 233 NO BOUNCED REPS. Note: this might not seem like much but at this time last year, I couldn’t get 225 for a single rep.
Then the walk:

It was 81 F at the start, 84 F at the end, 69 percent humidity. That is warm for us.

No glute pain. Not much knee pain either.

Ok, about this COVID-19: what is the strategy?

Our stated strategy is to take “social distancing” measures to as to “flatten the curve” (that is, to delay when the peak occurs and to make the peak lower than our health system capacity.

How it works.

Evidence from past outbreaks of other pandemics.

How to effect social distancing.

However, the UK is taking a somewhat different approach. While they are attempting to shield the most vulnerable, they are actually hoping enough people get it to establish “herd immunity” (60 percent getting it)

They’ll institute more stringent isolation measures in time (so they hope) to NOT overwhelm their health care system. But they want to avoid a “second peak” when the measures go away..which Japan might be experiencing right now:

March 12. We were supposed to be traveling to Britain next week to look around universities with Molly, but this is not the best time to travel. Vacation canceled. At least the hotels are all refundable.

March 13. On hold to Expedia for three hours to cancel flights — the line goes dead. Repeat two more times. I try calling All Nippon Airlines. On hold for one hour — success. Flight fully refunded.

March 15. The sun is shining and people are outside. Chinatown is as busy as I have seen it in two months. The chestnut seller and fortune tellers are back. It feels good. Until I consult the NHK website: Japan just set a record daily high in new infections, with 63 fresh cases.

Are people relaxing too soon?

The mathematics of the model:

And the standard “SIR” (Susceptible, Infected, Recovered) model.

Where does Illinois football go from here (and the Bayesian reaction of the old fans)

One of the things I love about football is having something fun, but inconsequential to think about and to predict. And yes, Illinois upset Wisconsin last week..by 1 point by a field goal…at the end of the game. Illinois lead for only the final play..the one that counted.

How Illinois did it:

Fan reaction
Yes, many of the fans stormed the field:

But the reaction of the older fans around me was kind of like mine: stunned silence….not knowing HOW to process it. Reason: if you are older and have followed the Illini for 10 years or more…you probably never believed that the Illini were going to win…you just knew that they’d fumble on that last drive, miss the field goal, bad snap, etc.

The disinterested football fan would have guessed that the team in gray was making the plays needed to win the game on that day….but the experienced Illini fan was waiting for the “other shoe to drop”; this time it never did.

So what now?
Let me make this clear: that while the Illini were outgained 420 to 315, Illinois deserved to win this game. Why?
1. Red zone defense: 4 times the Badgers had to settle for a field goal attempt (and they made 3), and once they turned it over.
2. Offense: the Illini found seams in the tough Badger defense; the line does a decent job of run blocking. And in passing: they burned the Badger secondary in one and one coverage.

Mind you, the Illini missed a field goal, surrendered one touchdown on a fumble, and had a touchdown called back on an inconsequential “lineman downfield” penalty; it was a deep sideline route and an interior lineman lunged at an interior linebacker who was 30-40 yards away from the play. It was a correct call, but it was also an unforced error which did not contribute to the touchdown.

So it wasn’t as if the Illini were “lucky”; they did NOT get every bounce or every break..far from it. They made the plays to win the game.

But that game is over and now we move forward. What now?

1. The defense still gives up a lot of yards. After a 2-0 start, they’ve given up:
480 yards, 34 points to Eastern Michigan (got 464 themselves)
674 yards, 42 points to Nebraska (to 299)
487 yards, 40 points to Minnesota (to 248)
489 yards, 42 points to Michigan (to 256)
420 yards, 23 points to Wisconsin (to 315)

You aren’t going to win many games if you keep getting outgained by such massive amounts.

2. Yep, look at the offense..some neat slashing runs but not a lot of sustained drives.

3. Human emotion. Examples: last year, the Illini followed a blowout win against Minnesota by a blowout loss at Nebraska and a 63-0 loss to Iowa at home. Two years ago: Iowa destroyed top 5 Ohio State by 31 points. They promptly went on the road and got blown out by Wisconsin, and then lost a home game to Purdue. And I still remember the 1980 Notre Dame team; they came in ranked no. 1 and played Georgia Tech..who went 1-9-1 …and got tied 3-3. Next week: ND went to Alabama and got a shutout win. Georgia Tech hosted Navy and lost 19-8…and ND had blanked Navy 33-0 in a game I saw in person.

I wouldn’t be surprised to see Illinois lay a couple of eggs.

BUT…sometimes a signature win CAN help a team turn a corner. It works both ways.

We shall see, and that is what makes it fun.