I don’t trust models and Governor Cuomo doesn’t either

“I’m out of that business because we all failed at that business. Right? All the early national experts. Here’s my projection model. Here’s my projection model. They were all wrong. They were all wrong.”

That’s New York State Governor Cuomo speaking on Memorial Day.  Welcome to the club.  I’ve been watching models fail for 50 years.

Cuomo has a right to be bitter.  The models told him he’d need 30,000 respirators, but Trump only gave him 4,000 prompting him to ask Trump to pick the 26,000 people he wanted to die.   Later he shipped his excess ventilators to other states. The faith he showed in the models he was fed would put a medieval theologian to shame.

Hopefully, in the future,  those in power will be more cynical about the models presented to them.

So here’s a ‘greatest hits list’  of a few models which failed.  Let’s start with

l. The population bomb (Paul Ehrlich) — ”

The battle to feed all of humanity is over. In the 1970s hundreds of millions of people will starve to death in spite of any crash programs embarked upon now. At this late date nothing can prevent a substantial increase in the world death rate.

2. The Club of Rome released the following broadside in 1974, “The Limits to Growth”Here is a direct quote from the jacket flap.

“Will this be the world that your grandchildren with thank you for? A world where industrial production has sunk to zero. Where population has suffered a catastrophic decline. Where the air, sea and land are polluted beyond redemption. Where civilization is a distant memory. This is the world that the computer forecasts. What is even more alarming, the collapse will not come gradually, but with awesome suddenness, with no way of stopping it”

You can read more about these two in the following post — https://luysii.wordpress.com/2018/04/11/an-unhappy-anniversary/

3.  My cousin runs an advisory service for institutional investors (hedge funds, retirement funds, stock market funds etc. etc.)  Here is the beginning of his latest post 16 June ’17

There were 3 great reads yesterday. First was Neil Irwin’s article in the NY Times “Janet Yellen, the Fed and the Case of the Missing Inflation.”  He points out that Yellen is a labor market scholar who anticipated the sharp decline in the unemployment rate. However the models on which the Fed has relied anticipate higher levels of inflation. Yet every inflation measure that the Fed uses has fallen well short of the Fed’s 2% stability rate. If they continue raising short-term rates in the face of low inflation, then “real” rates could restrain future economic growth.Second was Greg Ip’s article “Lousy Raise? It Might Not Get Better.” Greg makes the point that tight labor markets are a global phenomenon in many industrialized countries, yet wage inflation remains muted. Writes Greg “If a labor market this tight can’t generate better pay, quite possibly it never will in Germany & Japan.”

Third was an article by Glenn Hubbard (Dean of Columbia Business School & former chairman of the Council of Economic Advisors under George W. Bush). His Wall Street Journal op-ed was titled “How to Keep the Fed from Following its Models off a Cliff.”  Hubbard suggests that Fed officials should interact more with market participants and business people. And Fed governors should be selected because of their varied life experiences, and they should encourage a healthy skepticism of prevailing economic models.

Serious money was spent developing these models.  Do you think that climate is in some way simpler than the US economy, so that they are more likely to be accurate?  I do not.

4.  Americans are getting fatter yet living longer, contradicting the model that being mildly overweight is bad for you.  It is far too long to go into so here’s the link — https://luysii.wordpress.com/2013/05/30/something-is-wrong-with-the-model-take-2/.

The first part is particularly fascinating, in that data showed that overweight (not obese) people tended to live longer.  The article describes how people who had spent their research careers telling the public that being overweight was bad, tried to discount the data. The best quote in the article is the following ““We’re scientists. We pay attention to data, we don’t try to un-explain them.”,

4. The economic predictions of the Congressional Budget Office on just about anything –inflation, gross national product, economic growth, the deficit — are consistently wrong — http://www.ncpa.org/sub/dpd/?Article_ID=21516.

Addendum 28 June “White house economists overestimated annual economic growth by about 80 percent on average for a six year stretch during Barack Obama’s presidency, according to Freedom Works economic consultant Stephen Moore.

Economists predicted growth between 3.2 to 4.6 percent for the years 2010 through 2015. Actual economic growth never hit above 2.6 percent.”

5.  Animal models of stroke:  There were at least 60, in which some therapy or other was of benefit.  None of them worked in people. It got so bad I stopped reading the literature about it.  We still have no useful treatment for garden variety strokes

6: Live by the model, die by the model. A fascinating book “Shattered” about the Hillary Clinton campaign, explains why the campaign did no polling in the final 3 weeks of the campaign. The man running the ‘data analytics’ (translation: model) Robby Mook, thought the analytics were better and more accurate (p. 367).

I might add that I have no special mistrust of climate models, I just mistrust all models of complex systems.   For some thoughts on climate models please see — https://luysii.wordpress.com/2015/12/13/a-climate-treaty-based-on-a-failed-model-a-victory-for-the-political-class/

Data Cherry Picking 101

A friend sent me the following link — https://www.voanews.com/covid-19-pandemic/wisconsin-reports-its-highest-daily-increase-covid-19-cases.

It starts off like this — dates in parentheses added by me.

“Health officials in the midwestern U.S. state of Wisconsin reported a record number of new COVID-19 cases Thursday, (28 May) two weeks after the state Supreme Court struck down a state-wide stay-at-home order issued by the governor and enacted by the state health department.

The Wisconsin Department of Health Services reported 599 new known COVID-19 cases Wednesday, (27 May) with 22 known deaths, the highest recorded daily rise since the pandemic began. The department reports the state had more than 16,460 known cases and 539 known deaths as of Wednesday.”

Well that proves it, doesn’t it?   Removing restrictions has clearly  been a disaster.

No it doesn’t.  This is data cherry picking par excellence — one day’s cases — after a long holiday (Memorial Day)  weekend means nothing.  The ‘spike’ is an artifact of how cases are reported.

Here are the daily new COVID-19 cases from Massachusetts (which has relaxed nothing so far)
24 May 382
25 May 281
26 May 197
27 May 688 
 
QED

Do not forget that there are huge agendas at stake in how data is reported after loosening of the restrictions.  It shouldn’t be that way but it is.

Here are a few apocalyptic predictions about what would happen after Georgia lifted its restrictions 25 April.  Future predictions and definitive statements from these sources should be taken with a grain or more of salt.

From The Atlantic — “Georgia’s Experiment in Human Sacrifice — The state is about to find out how many people need to lose their lives to shore up the economy.” — https://www.theatlantic.com/health/archive/2020/04/why-georgia-reopening-coronavirus-pandemic/610882/

A way to end the pandemic — an update

Back on 5 April I wrote a post suggesting that we might be able to end the current coronavirus pandemic by infecting people with a cocktail of the 4 coronaviruses known to cause the common cold.  That post appears verbatim after the *** , along with a comment from a follower and my reply.

In the most recent Science (https://science.sciencemag.org/content/368/6493/809) — Science  22 May 2020: Vol. 368, Issue 6493, pp. 809-810 the following appeared

” The La Jolla team studied stored blood samples collected between 2015 and 2018, well before the current pandemic began, and detected these cross-reactive helper T cells in about half of them. The researchers think these cells were likely triggered by past infection with one of the four human coronaviruses that cause colds; proteins in these viruses resemble those of SARS-CoV-2.”

This is exactly what I was hoping for by giving the cocktail.  So there is cross reactivity. The quoted material  was tantalizingly brief, so I’ve written the people in La Jolla for more information, but it’s Memorial Day tomorrow.

A degree of immunity, however small, may explain some of the confounding aspects of the epidemic. First off, based on the presence of antibodies to the pandemic coronavirus (SARS-CoV-19), well over 90% of people with them simply aren’t sick. Second, given that 33% of the people in the Bronx have these antibodies, why doesn’t everyone?  Surely the 67% of the Bronx population lacking the antibodies have come in contact with someone who was infected, yet in some way they were immune.  Third, given enough exposure for a long enough time just about everyone gets infected — see some of the horrible examples in the excellent website — https://www.erinbromage.com/post/the-risks-know-them-avoid-them.

Susceptibility to clinical illness due to SARS-CoV-19 might be analogous to susceptibility to epilepsy.  We know that given enough electrical stimulation, every brain will convulse (see electroconvulsive therapy — ECT). 2% of children and 1% of adults do have spontaneous convulsions (epilepsy). Differential susceptibility to electrically induced convuslions is exactly how Dilantin (phenytoin), one of the first anticonvulsants was discovered in 1938.  All sorts of compounds were thrown at hapless experimental animals, and the amount of electricity needed to convulse them was measured.  An animal given Dilantin required more.

It’s important to note that the Science article wasn’t talking about antibodies, but something else called cellular immunity.  Hopefully the folks in La Jolla will write back and I’ll have more for you on these points in the near future.

Shane Crotty and Alessandro Sette, immunologists at the La Jolla Institute for Immunology

 

 

****

A way to end the pandemic

Could infecting people with the four or so coronaviruses that cause the common cold protect them against the new coronavirus causing the pandemic?   The official name for the new virus is SARS-CoV-2, the name for the disease is COVID-19.

“According to Marie-Louise Landry, MD, an infectious disease expert at Yale Medical School and the Director of the Yale Clinical Virology Laboratory, four common human coronaviruses cause 15-30% of common colds”

https://www.health.com/condition/infectious-diseases/coronavirus/coronavirus-symptoms-vs-cold

Now ask yourself how she could make a statement like this.  I’m going to try to get in touch with her tomorrow, but it is very likely that these cold causing coronaviruses are detected by measuring antibodies to them, carried in the blood of people who have been infected by them in the past.

Could one coronavirus (even a benign one) give partial immunity to others?  It’s possible and it’s time to find out.  We could know  in a few weeks.

Assume the test to measure the antibodies to cold coronaviruses exists.  Then measure them in our real, honest to God, modern day heroes on the front lines  — the nurses, docs, EMTs, orderlies, housekeeping, cops, etc. etc.  who are exposed every day to COVID-19.

Every hospital in the country could at least draw blood on them, look to see if antibodies are present and wait.   I doubt that many would refuse the test.

Sadly, it wouldn’t be long before some of them became infected with SARS-CoV-2.  Then investigators couldlook to see if those with the antibodies to the cold causing coronaviruses were protected.

If so, then make a cocktail of the 4 or so coronaviruses and give it to everyone.   It would be Edward Jenner and the cowpox all over again — https://en.wikipedia.org/wiki/Edward_Jenner

Even if the protection was only partial, decreasing the number of susceptible individuals would be enough to slow the pandemic and possibly even stop it.

  • loupgarous On April 18, 2020 at 12:32 am

    Not afraid of a dengue fever-type antibody-dependent enhancement problem?

Loupgarous: I’m not worried about this with the coronaviruses causing colds. People are worried about immune enhancement with vaccine development for dengue, SARS and RSV and now SARS-CoV-2 [ Proc. Natl. Acad. Sci. vol. 1176 pp. 8218 – 8221 ’20 ]. Immune enhancement definitely happens with clinical dengue (http://www.denguevirusnet.com/antibody-dependent-enhancement.html).

Why no worries? Because we’ve all had colds, lots of them, probably multiple ones with coronaviruses and no one has seen immune enhancement with colds (of any type). Naturally occurring cold causing coronaviruses are what I’d use if the experiment described in the post showed protection.

However, it is possible that such has happening with coronavirus caused colds, and we’ve been misdiagnosing it as influenza (which does kill a lot of people every year). This seems pretty remote.

Thanks for commenting. I really hadn’t considered this.

A Tale of Two States (with apologies to Dickens), the denouemont

Two days I posted the following puzzle — here is the answer and a bit more

A friend in med school, a classic University of Chicago graduate, was fond of saying “that’s how it works in practice, but how does it work in theory?”

Well, this country is currently in the midst of an immense social experiment (lockdowns) essentially based on theory (models).

We’re about to find out how it worked in practice.

Here are some recent statistics from two states.

State 1

3 day moving average of new cases of COVID19 ending 25 April — 2778

3 day moving average of new cases of COVID19 ending 13 May — 901

3 day moving average of daily deaths from COVID19 ending 25 April — 177

3 day moving average of daily deaths from COVID19 ending 13 May9 — 96

 

State 2

7 day moving average of new cases of COVID19 ending 25 April — 740

7 day moving average of new cases of COVID19 ending 13 May — 525 (the state allows 14 days for all the data to roll in, so the last date they regard as having secure numbers is the 7th of May and here the number is 539)

7 day moving averages of deaths from COVID19 ending 25 April — 35

7 day moving average of deaths from COVID19 ending 13 May — 24 (the state allows 14 days for all the data to roll in, so the last date they regard as having secure numbers is the 7th of May and here the number is 27).

One state loosened its lockdown restrictions 25 April, the other had them in effect through 13 May.  Your job is to figure out which one did and which one didn’t.

The denouement — State 1 is Massachusetts (which kept the lockdown) and State 2 is Georgia which loosened them on the 25th of April.

As usual, actual data answers some questions but raises new ones.  Contrary to the disasters predicted (see later), in Georgia the new cases of symptomatic pandemic flu declined by 29% and the number of deaths declined by 22%.  The 13th of May is way past the longest possible incubation period for cases beginning prior to 1 May.  So from this, the conclusion one might draw is that the lockdown was ineffective.

But hold on. Massachusetts also showed declines in new cases and deaths, and by greater amounts 68% and 46% than Georgia (29 and 22%)  implying the lockdown was of some use (in accelerating the decline in cases and death).

Pandemics and epidemics have a natural history of peak and decline, in the USA our pandemic is on the decline.

People who assumed (on purely correlative evidence) that lockdowns prevented new cases, and that lifting them would cause a marked increase in new cases and deaths, are clearly wrong.  It’s possible that cases will spike in the future proving them right, but pretty unlikely.  It’s only fair to give the doomsayers a sporting chance and followup is planned in a month.

Here are a few predictions of doom.  Future predictions and definitive statements from these sources should be taken with a grain or more of salt.

From The Atlantic — “Georgia’s Experiment in Human Sacrifice — The state is about to find out how many people need to lose their lives to shore up the economy.” — https://www.theatlantic.com/health/archive/2020/04/why-georgia-reopening-coronavirus-pandemic/610882/

A Tale of Two States (with apologies to Dickens)

A friend in med school, a classic University of Chicago graduate, was fond of saying “that’s how it works in practice, but how does it work in theory?”

Well, this country is currently in the midst of an immense social experiment (lockdowns) essentially based on theory (models).

We’re about to find out how it worked in practice.

Here are some recent statistics from two states.

State 1

3 day moving average of new cases of COVID19 ending 25 April — 2778

3 day moving average of new cases of COVID19 ending 13 May — 901

3 day moving average of daily deaths from COVID19 ending 25 April — 177

3 day moving average of daily deaths from COVID19 ending 13 May9 — 96

 

State 2

7 day moving average of new cases of COVID19 ending 25 April — 740

7 day moving average of new cases of COVID19 ending 13 May — 525 (the state allows 14 days for all the data to roll in, so the last date they regard as having secure numbers is the 7th of May and here the number is 539)

7 day moving averages of deaths from COVID19 ending 25 April — 35

7 day moving average of deaths from COVID19 ending 13 May — 24 (the state allows 14 days for all the data to roll in, so the last date they regard as having secure numbers is the 7th of May and here the number is 27).

One state loosened its lockdown restrictions 25 April, the other had them in effect through 13 May.  Your job is to figure out which one did and which one didn’t.

Answers tomorrow, with a lot more.

 

 

Georgia is the canary in the coal mine

The decision of the Georgia governor to relax some restrictions on activity and commerce 25 April was not met with universal acclaim.  In fact here’s how an article in the usually rather stolid The Atlantic puts it

       “Georgia’s Experiment in Human Sacrifice

The state is about to find out how many people need to lose their lives to shore up the economy.”

The presidential election will be decided in the next month — revision for clarity

Apologies to all for the previous post which was far murkier than it could have been.  The problem was that a ‘case’ of the pandemic coronavirus can mean 3 very different things.  These distinctions are tedious but crucial.

Meaning #1 — COVID19 — People who are clinically ill with the virus (official name SARS-CoV-2).  These are the people that  may die of the illness, although most do not.

Meaning #2 — The viral genome has been found in your saliva.

Meaning #3 — You have antibodies to the virus in your blood.

Here is the distinction between #2 and #3 — Antibodies (proteins) and genomes (RNA) are completely different chemically. Finding the actual genome (RNA in this case) of a virus in an individual  is like seeing a real bear up close and personal.  This can do you some damage.  In contrast, antibodies to the virus are made by an individual who has been infected by the virus in the past.       Antibodies are like seeing the tracks of the bear without the bear itself. You can’t see tracks without the bear having been present at some point in the past.  Antibodies mean you were infected at some point whether you knew it or not.

OK, so here’s another shot at what was I saying in the previous post.

I find it very sad that loosening the restrictions on activity has become so political. The left says that it will be a disaster and that cases and deaths will spike (meaning #1). As far as I’ve seen, they never say they hope they’re wrong.  The right says that deaths will continue, but the rate won’t increase.  There is evidence for both sides, but in the coming months we’ll actually have data one way or the other.

One thing is certain.  The number of cases of positive viral culture (meaning #2) will increase.  It has to because more people will be tested. So far, we’ve only studied around 1/1,000 of the population.  No one has ever said the lockdown will prevent new infection.  It hasn’t, but it has slowed things down.

I’m hoping that cases of COVID19 and death will not explode.  Not because I want Trump to win, but because getting people back to work  would be good for the country.  Should that happen, the anger of those who lost their jobs or businesses during the shutdown will be formidable.  Trump will win.

Should deaths from COVID19 explode (meaning #1) as restrictions are lifted, Trump is toast.

We should also get some idea of the percentage of the population who have been infected (manifest by antibodies to the pandemic virus meaning #3).  It almost certainly will increase, unless those already showing the antibodies lose them (which is unheard of happening this fast inFor  the antibodies we’ve studied in the past).

I’m cautiously optimistic that not much will happen when restrictions are eased. Here’s why.  All the studies on antibodies (meaning #3) done so far show they are 10 – 100 times more prevalent than cases where the virus is cultured (meaning #2).  For example 20% of Manhattan sampled population have the antibodies.  This implies that most infections with the pandemic coronavirus are asymptomatic.  

Another viral disease with a high prevalence of antibodies is infectious mononucleosis.  90% of adults in the USA have antibodies to mono, but far fewer than 90% were ever sick.

So the number of cases with positive culture (meaning #2)  isn’t what’s important.  It’s how many of them get sick with COVID19 (meaning # 1).  I think we have very good past statistics on the number of deaths and cases of COVID19   It will be clear if there is a spike in COVID19.

However be careful not to read too much into the first week’s statistics after restrictions are lifted, as there is a lag period of 2 – 11 days between infection and clinical illness.  Also try to understand which of the 3 meanings of “case” the article you are reading is talking about — this won’t always be possible.

 

The presidential election will be decided in the next month

I find it very sad that loosening the restrictions on activity has become so political. The left says that it will be a disaster and that cases and deaths will spike. As far as I’ve seen, they never say they hope they’re wrong.  The right says that deaths will continue, but the rate won’t increase.  There is evidence for both sides, but in the coming months we’ll actually have data one way or the other.

One thing is certain.  The number of cases of positive viral culture will increase.  It has to.  We’ve only studied around 1/1,000 of the population.  No one has ever said the lockdown will prevent new infection.  It hasn’t, but it has slowed things down.

I’m hoping that things stay pretty much the same.  Not because I want Trump to win, but because getting people back to work  would be good for the country.  Should that happen, the anger of those losing jobs, businesses will be formidable.  Trump will win.

Should deaths from COVID19 explode, Trump is toast.

We should also get some idea of the percentage of the population who have been infected (manifest by antibodies to the pandemic virus).  It almost certainly will increase, unless those already showing the antibody lose them (something unheard of this fast given the antibodies we’ve studied in the past).

I’m cautiously optimistic that not much will happen when restrictions are eased. Here’s why.  All the studies on antibodies done so far show they are 10 – 100 times more prevalent than cases where the virus is cultured.  20% of Manhattan for example.  This implies that most infections are asymptomatic.  So the number of cases with positive culture isn’t what’s important.  It’s how many of them get sick with COVID19 (which is the clinical illness produced by the pandemic coronavirus).  I think we have very good past statistics on the number of deaths and cases of COVID19   It will be clear if there is a spike in COVID19.  Be careful not to read too much into first week’s statistics after restrictions are lifted, as there is a lag period of 2 – 11 days between infection and clinical illness.

If you are uncertain about the difference between virus culture and antibodies to the virus — have a look at this.

Finding the actual genome (RNA in this case) of a virus in an individual  is like seeing a real bear up close and personal.  This can do you some damage.  In contrast, antibodies to the virus are made by an individual who has been infected by the virus in the past.  Antibodies (proteins) and genomes (RNA) are completely different chemically.      Antibodies are like seeing the tracks of the bear without the bear itself. You can’t see tracks without the bear having been present at some point in the past.

The pleasures of reading Feynman on Physics — III

The more I read volume III of the Feynman Lectures on Physics about Quantum Mechanics the better I like it.  Even having taken two courses in it 60 and 10 years ago, Feynman takes a completely different tack, plunging directly into what makes quantum mechanics different than anything else.

He starts by saying “Traditionally, all courses in quantum mechanics have begun in the same way, retracing the path followed in the historical development of the subject.  One first learns a great deal about classical mechanics so that he will be able to understand how to solve the Schrodinger equation.  Then he spends a long time working out various solutions.  Only after a detailed study of this equation does he get to the advanced subject of the electron’s spin.”

Not to worry, he gets to the Hamiltonian on p. 85 and  the Schrodinger equation p. 224.   But he is blunt about it “We do not intend to have you think we have derived the Schrodinger equation but only wish to show you one way of thinking abut it.  When Schrodinger first wrote it down, he gave a kind of derivation based on some heuristic arguments and some brilliant intuitive guesses.  Some of the arguments he used were even false, but that does not matter. “

When he gives the law correct of physics for a particle moving freely in space with no forces, no disturbances (basically the Hamiltonian), he says “Where did we get that from”  Nowhere. It’s not possible to derive it from anything you know.  It came out of the mind of Schrodinger, invented in his struggle to find an understanding of the experimental observations of the real world.”  How can you not love a book written like this?

Among the gems are the way the conservation laws of physics arise in a very deep sense from symmetry (although he doesn’t mention Noether’s name).   He shows that atoms radiate photons because of entropy (p. 69).

Then there is his blazing honesty “when philosophical ideas associated with science are dragged into another field, they are usually completely distorted.”  

He spends a lot of time on the Stern Gerlach experiment and its various modifications and how they put you face to face with the bizarrities of quantum mechanics.

He doesn’t shy away from dealing with ‘spooky action at a distance’ although he calls it the Einstein Podolsky Rosen paradox.  He shows why if you accept the way quantum mechanics works, it isn’t a paradox at all (this takes a lot of convincing).

He ends up with “Do you think that it is not a paradox, but that it is still very peculiar?  On that we can all agree. It is what makes physics fascinating”

There are tons more but I hope this whets your appetite

The death of amateur chamber music playing

Compared to the death, bereavement and economic pain of the pandemic the end of music making by amateur chamber musicians is a small thing.

Why do I say this?  You can hardly do better than the following link —

https://erinbromage.wixsite.com/covid19/post/the-risks-know-them-avoid-them

Here is a quote from it — “Indoor spaces, with limited air exchange or recycled air and lots of people, are concerning from a transmission standpoint. We know that 60 people in a volleyball court-sized room (choir) results in massive infections. Same situation with the restaurant and the call center. Social distancing guidelines don’t hold in indoor spaces where you spend a lot of time, as people on the opposite side of the room were infected.

The principle is viral exposure over an extended period of time. In all these cases, people were exposed to the virus in the air for a prolonged period (hours). Even if they were 50 feet away (choir or call center), even a low dose of the virus in the air reaching them, over a sustained period, was enough to cause infection and in some cases, death.”

Does this sound like amateur chamber music to you?  Particularly at summer festivals where hordes of the most vulnerable age  groups get together, eat together, play together, socialize together.

Is there hope that this will be transient?  Yes.  Here’s why.

First some background.

I’m sorry to keep putting this in, but I don’t want to leave anyone behind. Finding the actual genome (RNA in this case) of a virus in an individual  is like seeing a real bear up close and personal.  This can do you some damage.  In contrast, antibodies to the virus are made by an individual who has been infected by the virus in the past.  Antibodies (proteins) and genomes (RNA) are completely different chemically.      Antibodies are like seeing the tracks of the bear without the bear itself. You can’t see tracks without the bear having been present at some point in the past.

Well we’re in that situation in the USA.  Based on many studies now (California, New York State, Prison systems) the number of people who’ve been exposed to the virus enough to develop their own antibodies to it, is anywhere from 10 – 100 times greater than the number of people in whom the viral genome has been found.  This means that the vast majority of infections with the new coronavirus are asymptomatic.

So that’s the good news (but only if 3 things are true)

l. The antibody tests are accurate

2. Having the antibody means you won’t get sick if exposed to the virus

3. Having the antibody means you are free of the virus and can’t possibly transmit it to other people.

As of 10 May none of these are known with any degree of certainty, but if antibodies to the pandemic flu are like all the antibodies we’ve studied in the past they very likely are true.   It will take several months before this is all sorted out.

Things to watch out for in press accounts.

The number of known infections is certain to rise.  Officially we have currently tested around 500,000 people for the virus — way less than 1% of the population.  As more people are tested more cases will be found.

The important figure to watch is how many people have been made sick by the virus, not the number of people in whom the virus has been found– the technical term for the disease (not the virus) is COVID19.

Fortunately, I’m an amateur pianist with a huge literature for solo piano to explore (48 Bach Preludes and Fugues, 32 Beethoven sonatas, 60+ Haydn sonatas, 500+ Scarlatti sonatas, 16 Mozart sonatas).  My string  and wind instrument  playing friends aren’t so lucky.  But I miss them.