Category Archives: Social issues ( be civil ! )

Where are the deaths?

Our current model of the pandemic is that if the number of people testing positive for the viral genome increases, deaths will increase.   Could the model be wrong?  We’re about to find out.  The number of cases diagnosed daily has markedly increased recently in Georgia and Florida.

The number of hospitalizations for illness due to the virus (e.g. the old meaning of Covid19)  in Miami Dade county rose from 607 on 15 June to 1,062 on 28 June. https://www.miamiherald.com/news/coronavirus/article243854907.html Certainly deaths are sure to show a similar increase.  Aren’t they?

Well so far deaths are falling as diagnosed cases are rising. https://experience.arcgis.com/experience/96dd742462124fa0b38ddedb9b25e429.  has data through 28 June (a Sunday, where reporting is likely to be slow).

If anyone knows how to get these graphics into a WordPress post, please let me know (just write a comment).  Every time I try my post collapses and nothing shows up.  The WordPress Gods must be angry with me.  The links will get you there however, but even then you’ll have to root around to find what I’m talking about.  Apologies.

There is a new WordPress editor out, and I’ll try it to see if it helps.

Florida is particularly good to study because every Friday they tally the number of cases with a positive antibody test for the virus for the past week.  These are people who have recovered, and who likely have never been very sick.  There would be little reason to test someone hospitalized with COVID19 for antibodies.  Here’s a link — http://ww11.doh.state.fl.us/comm/_partners/action/report_archive/serology/serology_latest.pdf.

It boils down to the fact that about 35% of 51,982 newly diagnosed cases of infection in the two weeks ending 26 June are really positive antibody tests.

Unfortunately Florida doesn’t have available a statewide number for the total hospitalized cases of COVID19 — like Massachusetts– https://www.mass.gov/doc/covid-19-dashboard-june-29-2020/download  — but with a population more (6.9 million) than  Miami Dade metropolitan area (5.5 million), there were only 760 cases statewide.

Now on to Georgia, which I’ve been following because they were one of the first states to lift restrictions.  As of 3PM today 29 June,  the 7 day moving average of daily deaths was 15 (this number is for 16 June, because Georgia doesn’t regard its numbers as solid until two weeks have passed).  On 25 April, the day the lockdown was partially lifted, the 7 day moving average of daily deaths was 41.

The number of cases in Georgia diagnosed (using both antibodies to the virus and the genome) has risen markedly in the past 2 weeks. Unfortunately I’ve been unable to find what percentage of the positive tests in Georgia are due to antibodies to the virus.

Both Florida and Georgia are so typical for what docs face all the time.  The data you have is never quite the data you’d like to have.

Now the time from hospitalization with COVID19 to death is unknown, but it’s unlikely to be greater than a month. However, for both states, given the rise in diagnosed cases, we had better see a rise in deaths, or something is seriously wrong with our model.

Has this ever happened before?  You bet.  The nationwide rise in obesity over the past several decades was predicted to have awful effects on mortality.  Yet life expectancy continued increasing.  For details see a copy of an old post after the ****

So I’ll revisit these states in two weeks or so to see if deaths have risen.  This post is long enough, but it’s worthwhile inserting two pieces of data from family and friends.  Family spies tell me that yuppies in Brooklyn are partying in the street without any protection.  Similarly, a friend from Baltimore notes  “Not many people are wearing masks in Baltimore or Washington, particularly individuals at high risk.”

Although Trump’s medical pronouncements are rightly ridiculed, I find it improbable that the bunch described above take what he says as holy writ and that he’s responsible for their behavior.

We are currently witnessing a massive social and medical experiment which would never get past an institutional review board.

****

https://luysii.wordpress.com/2011/03/20/something-is-still-wrong-with-the-model/

Something is still wrong with the model

We’re getting fatter and fatter as a nation and with fatness comes diabetes, hypertension, elevated lipids, strokes, heart attacks and death.  That’s the model.  There’s something wrong with it however, as people in the USA are living longer and longer, and deaths are dropping. The following is one of the first posts I wrote on the blog and it got a lot of play.

https://luysii.wordpress.com/2009/08/20/something-is-wrong-with-the-model/ (I’ll reproduce it here at the end of this post)

What’s happened since?  The following year the Center for Disease Control (CDC) reported a one month dip in expectancy to 77 years and 11 months.  Last week the CDC announced that because of a computer programming error the dip didn’t happen.   They also announced new data for the most ‘recent’ year available (2009 not 2010) and life expectancy continues to increase (now 78 years and two months for a child born today).  This is probably not a statistical fluke.  The data is based on death certificates. Why in the world we don’t have data for 2010 yet and why it took 14+ months for the CDC to collate the data for 2009 I leave to your imagination.

The absolute number of deaths  dropped by 36,000.  Now docs misdiagnose a lot of things but death isn’t one of them.  So my guess is that life expectancy is even higher, because the CDC is probably using the numbers the census counts rather than the numbers of people who are actually here (e.g. undocumented immigrants etc. etc.).

As noted earlier, one self serving explanation is that medical care is just getting better and better, and certainly it is, but it is very unevenly distributed, which was one of the points in passing ObamaCare.  More likely, in my opinion, is that obesity just isn’t as bad as its cracked up to be.  This goes against years and years of experience as a practicing physician.  Next time you visit a friend in the hospital, look at what’s lying in the beds — you will find the percentage of really heavy people much higher than the people walking the streets.  How many times have I seen an obese diabetic hypertensive, hyperlipidemic patient improve all 3 (and presumably their risk of premature death) by losing weight.   Yet facts must be faced — we’re not dropping like flies even though we’re getting fatter as a nation.  Any thoughts?

 

HERE’s the old post

Back in grad school when a theory came up with a wrong prediction, we all clapped hands because it showed us exactly where a new theory was needed, and just how it failed. No casting about for something to work on. A program that crashes intermittently is very hard to fix. Once you’ve found input that consistently makes it crash the job becomes much easier.

The Center for Disease Control released new data for 2007 (based on 90% of all USA death certificiates) showing that mortality rates dropped again (by over 2%) to 760/100,000 population. It’s been dropping for the past 8 years, and viewed longer term is half of what it was 60 years ago. Interestingly death rates from heart disease dropped a staggering 5% and even cancer dropped 2%.

But the populace is fat and getting fatter. This has been going on for 30 years. You can Google NHANES for the gory details, but the following should be enough. [ Science vol. 299 pp. 853 – 855, 856 – 858 ’03 ] The data from a recent NHANES (’99 – ’00) shows that the percentage of obese (as opposed just overweight) increased from 23% in the surveys from ’88 to ’94 to 31%. This is based on the body mass index (BMI). Someone 6′ 1″ would have to weigh 225 pounds to be obese.

We are told to be prepared for an epidemic of diabetes, high blood pressure, elevated blood lipids because of this. Every doc has seen blood sugar drop, blood pressure lowered, lipids come down in people with any/all of the above when they are able to lose a significant amount of weight. These diseases are significant only if they kill people, which they certainly seem to do in my experience. The next time you’re visiting a friend in the hospital, look at what’s lying in the beds. Very likely, many more than 31% of them are obese.

So why are death rates dropping and people living longer? Something must be wrong with the model — it’s pretty hard to quarrel with the data as being inadequate. Certainly the increased incidence of obesity should have produced something by this time (it started 30 years ago).

Well, the self serving answer for the drug developers is that their drugs are better. MDs would like to think it’s due to better care. Possibly. Here’s some detail.

#1: More people are exercising than they used to. How many joggers and walkers did you see on the streets 20, 30 years ago?

#2: Fewer people are smoking. Forget lung cancer (if you can). The big risk for smokers is premature vascular disease. Normally we all have carbon monoxide in our blood (it comes from the breakdown of hemoglobin). [ Brit. Med. J. vol. 296 pp. 78 – 79 ’88 ] Natural carbon monoxide production would lead to a carboxyhemoglobin level of .4 – .7%, but normal levels in nonsmokers in urban areas are 1 – 2%. Cigarette smoke contains 4% carbon monoxide, so smokers have levels of 5 – 6%. This can’t be good for their blood vessels.

#3: Doctors know more than they did. My brother is a very competent internist. He took over the practice of a similarly competent internist after his very untimely many death years ago. Naturally he got all the medical records on the patients. He found letters (now over 25 years old) from the late MD to his patients informing them of their lab results, and assuring them that their cholesterol was just fine at 250 mg%.

#4: The drugs are better. In addition they may be working in ways that we have yet to fathom. Consider the statins — their effect on vascular disease is far greater than their effect on blood lipids (cholesterol, triglyerides) — particularly when compared to other agents that lower blood lipids to the same extent.

Any further thoughts?

New York City Covid-19 cases spiked today. Stock market futures tank

22 June:  A private testing firm (Legkoverny Testing) today reported 10,000 newly found Covid-19 cases in New York City today. Stock market futures immediately tanked.  They had been going around the Bronx for several weeks offering free antibody testing to anyone wanting it.  Some 30,000 residents took up the offer.

Legkoverny knew where to go to get these results. https://www.6sqft.com/new-york-covid-antibody-test-preliminary-results/ — communities of color in the Bronx where positive tests for the antibody occur in up to  50% of the population.

Fortunately, officials noted that a positive antibody test means that the individual had been infected and recovered, as all 30,000 or so weren’t on respirator in ICUs.  In fact they were walking around the streets of the city, and most had never been sick.

This sort of thing has not been noted by the mainstream press reporting an upsurge in Covid-19 cases.

Increasing the number of tests done daily will increase the number of  positive tests for cases.  Every state in the country has been increasing the number of tests done daily.

Now Covid-19 used to mean, clinical illness with the SARS-CoV-19, the pandemic virus.  It isn’t being reported that way now, just a positive antibody test for the virus appears to be enough

Here’s Florida’s weekly report of positive antibody tests for the week ending 19 June — http://ww11.doh.state.fl.us/comm/_partners/action/report_archive/serology/serology_latest.pdf.  200,000+ people were tested, and 8,627 were found positive which is nearly 1/3 of the total new cases for that week.

So if you want to know if the number of serious cases is increasing (which is  what we all would like to know), forget these these numbers, which are partly due to increased testing.  Concentrate on two statistics (assuming you can get them)

l. The daily death rate from the virus — even better a 7 day moving average as Georgia does

2. The number of cases currently in the hospital.

Not every state gives out this information, but Massachusetts does.

There will be a lot of egg on a lot of faces if easing the lockdown restrictions doesn’t cause an increase in illness and death, which is probably why the pandemic is being reported this way.

Also ignore daily spikes in the number of cases — this can be an artifact of the way cases filter in to state health departments.  For an early example of this please see  — https://luysii.wordpress.com/2020/05/28/data-cherry-picking-101/

Good luck

 

 

 

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.