Archive for the ‘Covid-19 Testing’ Category

COVID Math: So, how accurate are rapid tests?

January 19, 2022

Best guess: If you test negative, the likelihood is very high that you’re not contagious.

If you test positive, the likelihood is high that you are contagious … but there’s about a 1 in 4 chance that you got a false positive, so assume that you are contagious and re-test the next day to be sure.

Keep reading for the math and the underlying assumptions…
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DISCLAIMER: I’m not a medical professional or scientist — just a curious, self-interested guy.  So, don’t take anything that I say or write as medical advice. Get that from your doctor!
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In a prior post, we outlined the logic that CDC Director Walensky laid out regarding antigen rapid tests in a 2O2O paper (i.e. before she started walking the political mine field).

Her fundamental conclusion at the time:

“The antigen rapid tests are ideally suited for surveillance testing (i.e. determining if a person is contagious) since they yield positive results precisely when the infected individual is maximally infectious.”

OK, we’ll take that as our qualitative starting point.

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What exactly is “accuracy”?

Keying off Walensky’s conclusion (above), we’ll focus on the use of antigen rapid tests for surveillance testing (i.e. determining if a person is contagious).

In that context, antigen rapid test accuracy has two components: sensitivity and specificity:

> Sensitivitysometimes called Positive Percent Agreement (PPA) —is the probability that a contagious person’s test result is positive. When it isn’t, it’s called a false negative.

> Specificitysometimes called Negative Percent Agreement (NPA) —is the probability that a a person who is not contagious gets a negative test result. When it doesn’t, it’s called a false positive.

IMPORTANT: Keep in mind that we’re focusing on surveillance testing … whether or not a person is contagious.

For early-on diagnostic testing (i.e. whether a person may need treatment or quarantine), the above criteria would be “infected”, not “contagious” … and the answers are different.

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Now, let’s add some real life parameters and do the math

Johns Hopkins maintains a website that reports sensitivity and specificity for all Emergency Use Approved test kits.

For example, Abbott’s BinaxNOW — one of the most popular — is listed as scoring 84.6% on sensitivity (if contagious, the test result is positive) and  98.5% on specificity (if not contagious, the test result is negative).

That’s testing accuracy, but it’s only part of the story.

What we really care about is the tests’ predictive value.

As JHU puts it…

Positive predictive value (PPV) and negative predictive value (NPV) provide insight into how accurate the positive and negative test results are expected to be in a given population.

Predictive value is based on test accuracy and existing disease prevalence.

OK, so to calibrate predictive value,  let’s assume that Covid prevalence is 5% (i.e. 1 in 20 people that a person runs into is infected) … and plug the Abbott sensitivity and specificity numbers into the below Bayesian table.

For a detailed walk-through of a comparable Bayesian table, see our prior post: If I test positive for COVID, am I infected?     

image

The key numbers — the predictive values — are in the bottom rows of the yellow and orange boxes:

> Less than 1% of the negative test results are false negatives (the orange box)

> But, 25.2% of the positive test results are false positives (the yellow box).

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My take:

If a patient gets a negative test result (based on these parameters), it’s virtually certain that they’re not contagious … but they may have small traces of the virus in their system.

If a patient tests positive, there’s high likelihood (74.8%) that they’re contagious … the likelihood is higher if they are symptomatic.

But, if a person is asymptomatic and tests positive, there’s a 1 in 4 chance that they got a false positive and might not be contagious.

Before going out & about, it would make sense to take a second test to validate (or refute) the positive result.

A second positive test (taken a day or 2 later) reduces the chance of a false positive to essentially zero.

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IMPORTANT: These Bayesian estimates are dependent the sensitivity and specificity of the test …  and on the assumed prevalence of of the virus.

For example, if the prevalence rate jumps from 5% (1 in 20 people are contagious) to 25% (1 in 4 people are contagious) … then the positive predictive vale soars to 95% and the negative predictive value decreases to 95%.

Conversely, likelihood of a false positive drops to 5% and the likelihood of a false negative increases from near-zero to 5%

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RIGHT NOW: Order your “free” at home covid tests

January 18, 2022

The government web site is up and running:

COVIDtests.gov – Free at-home COVID-19 tests

I just ordered our’s … took less than 2 minutes … just enter email address and shipping address … no insurance or ID info required … even get a confirming email — just like the real online guys.

I’m amazed that the site is up & running … and that the process was so simple.

Walenshy on rapid tests … then and now.

January 18, 2022

Last week, we spotlighted a NY Times article “The C.D.C. Is Hoping You’ll Figure Covid Out on Your Own”.

Author Zeynep Tufekci asked:

Why, two years into the pandemic, are people are grasping to know whether they should see a grandparent or an elderly relative or go back to work if they are still testing positive?

Why are we still trying to figure this out on our own?

Of course, the primary root causes are a new, fast-moving, ever-changing virus … and haphazard science, heavily politicized, that can’t seem to converge on a coherent “theory of the case”.

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Now that Biden’s test kit program is about to launch, this part of the article has specific relevance….

Deep in the article, Tufekci  channels CDC Director Walensky to provide a clear explanation of covid testing … and an example of the politicization.

According to Tufekci…

Back in 2020, when Walensky was on the faculty of the Harvard Medical School and chief of the division of infectious diseases at Massachusetts General Hospital, she co-authored a scientific paper titled “Saliva-Based Antigen Testing Is Better Than PCR Swabs”.

Some snippets from that paper:

> PCR tests can detect tiny amounts of the virus, so they do a great job of “diagnostic testing” — determining early-on if you are infected and may require isolation or treatment.

> But, PCR tests can “return positives for as many as 6-12 weeks … long after a person has ceased to need medical care or pose any real risk of transmission to others.”

> Said bluntly: PCR tests do a good job of diagnostic testing but a rotten job of “surveillance testing” that zooms in on whether a person is contagious to others.

> “The antigen tests are ideally suited for surveillance testing since they yield positive results precisely when the infected individual is maximally infectious.”

The reason is that antigen tests respond to the viral load in the sample without biologically amplifying the amount of the virus. PCR tests do amplify the virus in the samples and sometimes detect and report inconsequential “left over” viral fragments.

> A rapid test turns positive if a sample contains high levels of the virus, not nonviable bits or minute amounts — and it’s high viral loads that correlate to higher infectiousness.

With respect to viral transmission: “False negatives” on rapid tests are a benefit since “those are true negatives for disease transmission”

Again, a PCR test is positive if any amplified viral content is detected.

An antigen test may be negative if the virus is present but the viral load is very low … consistent with a low likelihood of viral transmission.

> But, antigen tests may be slower (than PCR tests) to detect the early onset of an infection, especially if symptoms haven’t materialized, since the viral load may be low but building.

> So, confirming a suspected early stage infection is best done with a PCR test or with a series of rapid tests, say, every other day for a week.

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OK, that’s what Walensky said back in fall of 2020, before her shift from “scientist” to “political scientist”.

Now, she’s saying:

“We actually don’t know how our rapid tests perform and how well they predict whether you’re transmissible during the end of disease”

Has the science changed … or, the scientist?

Hmm

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P.S. Walensky’s entire 2020 paper is worth reading.

Here comes the USPS … with 500 million free test kits.

January 17, 2022

Just wondering: What could possibly go wrong?
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OK, as the omicron shockwave is showing some signs of peaking, Biden’s mass ordering of in-home rapid test kits is going to launch this week.

A simple plan: Tens of millions of Americans place online orders for free test kits (maximum 4 per “address”) …  7 to 12 days later, the order gets shipped via the USPS … a couple of days later the kits start hitting mailboxes around the country … and over 100 million sharp-as-tack Americans try to figure out when and how to use the kits.

Might work…

Call me cynical, but I think there may be some potential holes in this plan:

> Web site crashes: According to the AP, “Administration officials say they are cognizant that any launch of a website carries some risks”. You don’t say. Envision Obama’s Healthcare.gov web site getting as many as 100 million front-ended hits.

> The Supply Chain: Since purchase orders have just been placed (or are still in process), who knows when the 500 million will actually hit government warehouses?

> Snail mail: Again, successful online orders “will be shipped in 7 to 12 days” … delivery “a couple of days later” — may be optimistic with 500 million test kits floating around an erratic postal system

> Lost in the mail: Any chance some of the kits fall into some USPS dark hole or get misdirected?

> Hijacked mail: The test kits will be the most valuable “bulk rate” mailing since the 2020 mail-in election ballots. Act surprised when people start reporting that they didn’t get their test kits.

> Black market resales: The kits will have value for people who need them but, for whatever reason, can’t score enough for their household. Watch for “free” government supplied test kits showing up on the internet “not for free”.

> Customer service: What if your kits don’t arrive in your mailbox? Who do you call to resolve the problem? Good luck.

> Counterfeits: Once the internet black market starts up (and it will!), the counterfeit and unregulated kits from China are sure to follow.

> Too Late to Matter: Since the kits won’t be arriving until late January – more likely February – omicron will hopefully be past us. What to do with the kits? Will they be able to detect the omega variant?

Note: Omega is the last of the 24  letters in the Greek alphabet, but not necessarily the last covid variant.

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Bottom line: High likelihood that this rollout will make the Afghan evacuation look like a Swiss watch.

Hope I’m wrong, I’d like to score a couple of kits … especially if my fellow taxpayers are footing the bill.

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P.S. I would have drafted Amazon to do order processing and fulfillment.  They could handle the volume and the 1-per-address rule. Why craft a new government system on-the-fly? Dumb.

MUST READ: How will we know when we’ve turned a COVID-19 corner?

January 6, 2022

Stay focused on the number of Daily New Deaths!
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This is a relevant excerpt from a long ago prior post (May 2020)
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From the begining of the Covid pandemic, I’ve focused on Daily New Deaths (DND) as my key metric.

Why is that?

First, saving lives is our paramount objective, right?  If yes, caused fatalities should be our focus metric.

Second, I think that most other metrics that are being bandied about are quite problematic.

Counting deaths — while a bit macabre — is a more reliable process than counting, say, the number of infected people.

Sure, I’d like to know the number of people infected with COVID-19.

But, unless everybody — or at least a large statistical sample — is tested, the number of confirmed cases is subject to disqualifying statistical issues.

Most notably, who is being tested and who isn’t? What about the asymptomatic “hidden carriers”? What are the criteria for confirming a COVID infection? What about false positives (and false negatives)? How to standardize the reporting processes across states? How to keep governmental units from fudging the numbers?

Importantly, if testing increases, then confirmed cases goes up.

Is that an indication of more virus spread or just a reflection of more testing?

I sure can’t tell … and, I doubt that anybody else can with any degree of reliability.

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Again, counting fatalities is probably the most reliable metric.

Fatalities are discrete events – so they’re countable.

Still, even deaths may have some counting imperfections.

For example, many non-hospitalized people die and are buried without autopsies.  Some may be uncounted COVID victims.

On the other hand, some people may die and be diagnosed with COVID infections. That doesn’t necessarily mean that COVID killed them.  That’s especially true with COVID since it’s most deadly for people with other health problems.

And, as we stated above, the definition of COVID deaths has changed over the course of the pandemic:

COVID-related” means “COVID present”, not necessarily “COVID caused” … and , along the way, “present” was redefined from “confirmed” to “presumed”

Further, COVID deaths are a function of two drivers: the incidence of the virus … and, the nature, level and timing of therapeutic healthcare.

Said differently, more effective therapeutic healthcare will dampen the death toll.

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Bottom line: “Daily New Deaths” is the number we should be watching.

If it shows a consistent downward trend, then we’ll know we’ve turned the corner.

If it stays stable (at a high level) or turns upward, we’ll know that we’re in deep yogurt.

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Next up: So, how are we doing?

So, do rapid tests work … or not?

January 4, 2022

With covid prevalence spiking, as usual, CDC guidance muddies the water.
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A couple of weeks ago, with omicron spreading like wildfire and workforces getting depleted by quarantined workers, Biden finally left his bunker and promised January home-delivery of 500 million hard-to-find antigen rapid tests.

Current reporting is that orders are “in the process” (i..e. they have not yet been officially placed) for 250 million in the last half of January and 250 million in February and March.

That works out to about 1 test per month for every adult.

Biden assured that the testing surge would be another game-changer (akin to getting LA ports to stay open nights & weekends to unclog supply chains) … and that he was, of course, “following the science” …

So, it seems reasonable to conclude that his homeboy scientists advised him that the antigen rapid tests worked.

That is, except for CDC Director Wolensky who told CNN that the CDC doesn’t “actually know how well rapid tests perform and how well they predict transmissible presence of the virus”.

So, do the rapid tests work … or not?

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On that question, Epidemiologist Michael Mina published the most informative piece that I’ve found…

Dr. Mina’s overall conclusion:

Antigen tests are extremely sensitive for very contagious people.

When taken at peak viral load, these tests approach 100% sensitivity.

Here’s his visual recap … click it to enlarge it.

image

My takeaways:

> In the first couple of days after getting infected, neither the PCR nor the antigen tests are sensitive enough to detect the infection.

> Around the 5th day after getting infected, the tests are able to detect the virus.

> PCR tests may be able to detect the virus a day or two sooner than the antigen test … but, since the PCR tests require a day or two for processing & reporting, antigen and PCR tests are practically equivalent for early detection.

> Infectees have the highest viral load (and are most contagious) from day 6 to day 12 after getting infected.

> During days 6 to 12, when infectees are most contagious, both PCR and antigen tests are reliably able to detect the virus.

> After day 12, as the level of viral load quickly diminishes, PCR tests are able to detect the residual, non-contagious levels of the virus … but, the less sensitive antigen tests do not.

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Again, according to Dr. Mina’s research and analysis:

When taken at peak viral load (when infectees are most contagious), antigen tests approach 100% sensitivity.

Accordingly, Dr. Ashish Jha, the dean of Brown’s school of public health, calls antigen tests “contagiousness tests” … and says that they are very good at detecting people who are still infectious to others.

They won’t detect every speck of virus that their PCR counterparts are attuned to do, but they can detect the important part — if someone is producing enough of the virus that they’re likely to spread it.

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Bottom line

If I could get my hands on in-home rapid tests, I would confidently use them…

(1) When I’m exhibiting any symptoms (e.g. fever or sniffles)

(2) After the rare occasions when I’ve attended an indoor gathering with non-family members.

(3) Before visiting my grandkids … for re-assurance that  I’m not contagious.

But, first step is getting my hands on some of the in-home tests!

And, as I like remind readers…

DISCLAIMER: I’m not a medical professional or scientist — just a curious, self-interested guy.  So, don’t take anything that I say or write as medical advice. Get that from your doctor!

Why is the CDC so reactionary, illogical and, uh, unscientific?

January 3, 2022

Their most recent isolation “guidance” is a case in point.
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With covid-omicron spreading like wildfire and seeming to close in on all of us (me included) … and with workforces getting depleted by quarantined workers, the CDC stepped in to save the day by issuing revised isolation guidelines, specifically:

Given what we currently know about COVID-19 and the Omicron variant, CDC is shortening the recommended time for isolation for the public.

People with COVID-19 should isolate for 5 days and if they are asymptomatic or their symptoms are resolving (without fever for 24 hours), then…

People should follow that (isolation period) by 5 days of wearing a mask when around others to minimize the risk of infecting people they encounter. CDC

Let’s unpack that guidance…

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First, when does the clock start running?

For somebody who who develops symptoms, I guess it’s when “the” symptoms first present themselves.

My questions:

(1) Do cold-like sniffles count as “symptoms”? What’s the best indicator that I may have caught it? How indicative is a fever?

(2) What to do if I am officially symptomatic? Isolate, for sure … but, go see a doctor?

Note: At local walk-in clinics, people are waiting 4 to 6 hours in a room filled with 50 to 100 sick-likely people.  Sounds like a recipe for disaster, right?

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What about infectees who are asymptomatic?

For them, I guess that the clock starts for when they test positive.

Let’s pretend that they’re inclined to get tested (say, because other members of their household are symptomatic or have tested positive … or because their employer or airline requires a test).

These folks can’t do-it-themselves now because of the scarcity of in-home rapid tests.

Of course, they have the option of waiting in line for a couple of hours to get a “commercial” PCR test.

Note: Lines are running around the block at local testing sites.  Again, sounds like a recipe for disaster since most of the people in line are symptomatic.

===============

Once the clock starts…

OK, this part of the CDC guidance is pretty clear: isolate for 5 days.

But, things get murky after that isolation period.

The CDC says:

After infectees isolate for 5 days, if they are asymptomatic or their symptoms are resolving (e.g. no fever for 24 hours), then…

They should follow that (isolation period) by 5 days of wearing a mask when around others

The criteria “asymptomatic or symptoms resolving” is most problematic.

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What about rapid tests?

In the UK and several other countries, that free-of-isolation criteria is supplemented by the need for a negative covid test … rapid tests qualify.

So, why isn’t the CDC advising a negative covid test?

Cynics observe that the omission of negative tests in the guidance is simply cover for the Biden Administration’s slow-roll on the development and production of antigen rapid tests.

The official CDC announcement says:

The guidance is motivated by science demonstrating that the majority of transmission occurs early in the course of illness, generally in the 1-2 days prior to onset of symptoms and the 2-3 days after infection. CDC

More specifically, CDC Director Rochelle Walensky told CNN that the CDC chose five days because that’s typically the period when individuals are most infectious.

“Those five days account for somewhere between 85 to 90 percent of all transmission that occurs”

So far,so good.

But then she added:

“We opted not to advise the rapid test for isolation because we actually don’t know how our rapid tests perform and how well they predict whether you’re transmissible during the end of disease. Source

Say, what?

So, if I have this right…

Biden has ordered up 500 million in-home rapid tests … but the CDC doesn’t “actually know how well rapid tests perform and how well they predict transmissible presence of the virus”.

If that isn’t dizziness-inducing enough, Dr. Fauci, Biden’s chief political scientist, was his usual ubiquitous self on Sunday TV hinting that the CDC would soon be adding a testing requirement after all. Source

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My take: It would be a lot easier to “follow the science” if “the science” weren’t so reactionary, illogical, impractical and, well, unscientific.

Vanity Fair: Biden put all his eggs in the vaccination basket …

December 26, 2021

Lacked the imagination for an Operation Warp Speed for testing and therapeutic drugs.
=============

Two must read articles:

Vanity Fair: The Biden Administration Rejected Proposals for “Free Rapid Tests for the Holidays”

WSJ: Big Pharma Success, Government Failure

Here’s a merged extract of the articles … both of which are worth reading in their entirety.

===========

The essence

In January 2021, the incoming Biden Administration was sent a 23-page document outlining a national rapid-testing strategy that would enable the country to reopen safely even before the vaccine rollout was complete.

The document made a case for rapid testing as the most powerful tool to reduce transmission and case counts quickly.

Then, on October 22, a group of COVID-19 testing experts presented the Biden administration with a detailed strategy for overhauling America’s approach to testing.

The plan was to put rapid at-home COVID-19 testing into the hands of average citizens, allowing them to screen themselves in real time and thereby help reduce transmission.

The plan called for “Every American Household to Receive Free Rapid Tests for the Holidays/New Year.”

The big, bold idea for free home tests for all Americans to avoid a holiday surge, was killed by the Biden Administration.

=============

The reasons:

> “The Biden Administration took a vaccine-only approach … and didn’t support the notion of testing as a proper mitigation tool or therapeutic oral antiviral drugs.”

The Administration has had a single-minded fixation on vaccinating Americans left testing and therapeutics on the back burner for so long.

The Administration feared that at home rapid tests and therapeutics might somehow signal to wary Americans that they could skip vaccinations.

Officials failed to foresee how vaccine efficacy would wane over time and demand would plateau. 

> The FDA dragged its feet vetting and approving at home tests … valuing “exquisite sensitivity, rather than “public health utility”.

“If our goal is defined as public health, every test run last year was practically useless.”

While rapid antigen tests are less accurate than PCR tests, they are “extremely sensitive for very contagious people” … when they’re at peak viral load, these tests approach 100 percent sensitivity.” Source

> Many doctors opposed in home testing, viewing patient test results as theirs alone to convey.

Some doctors had even opposed home testing for pregnancy and HIV, arguing that patients who learned on their own about a given condition would not be able to act on the information effectively.

> There wasn’t capacity to manufacture over-the-counter tests at the required scale.”

The plan required an estimated 732 million tests per month.

The capacity problem was twofold: The FDA had authorized only a handful of different home tests, and those it had authorized could not increase manufacturing fast enough.

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Bottom line

> It wasn’t a matter of Biden not having thought ahead about the need for rapid tests (as he told ABC News on TV) … It was a matter of his team considering, and then rejecting, a plan to have hundreds of millions of home tests available now..

> Biden’s recently announced plan is widely regarded by experts (i.e. “the science”) as a totally inadequate “exemplar of too little, too late …

We need several billion tests and have needed them for over a year to help prevent spread.”

Advance government orders like Operation Warp Speed’s for vaccines would have accelerated production of anti-virals.”

> The Biden administration has lacked “the imagination to have an Operation Warp Speed-level programs for testing and therapeutics.”

“The White House, in baseball terms, is playing small ball. When it comes to rapid testing, they’re bunting the players along.”

“Vaccines have saved hundreds of thousands of lives, but many more lives would have been saved if anti-viral oral treatments were available sooner. The drugs represent a huge pharmaceutical success but a missed government opportunity.”

> So, as COVID-19 is exploding again, we’re stuck with “endless lines of desperate Americans clamoring for tests in order to safeguard holiday gatherings” … and, rationing of live-saving anti-viral drugs.

Local example: One of the most expansive urgent care chains in the Maryland-Virginia market restricts testing to symptomatic patients only … and warns patients of 6- hour wait times (in a waiting room with a hundred or so other symptomatic patients)

=============

In Biden’s own words:

Anyone, anyone who needs to be tested should be tested at no charge, at no charge.

Tests should be available to all who need them and the government, the government should stop at nothing to make that happen.

No excuses should be made.

The administration’s failure on testing is colossal and it’s a failure of planning, leadership, and execution.”  

Oh yeah, that was in March 2020 in a blast against Trump.  Transcript

As Forrest Gump would say: “What goes around, comes around”

Vanity Fair: Biden put all his eggs in the vaccination basket …

December 24, 2021

Lacked the imagination for an Operation Warp Speed for testing and therapeutic drugs.
=============

Two must read articles:

Vanity Fair: The Biden Administration Rejected Proposals for “Free Rapid Tests for the Holidays”

WSJ: Big Pharma Success, Government Failure

Here’s a merged extract of the articles … both of which are worth reading in their entirety.

===========

The essence

In January 2021, the incoming Biden Administration was sent a 23-page document outlining a national rapid-testing strategy that would enable the country to reopen safely even before the vaccine rollout was complete.

The document made a case for rapid testing as the most powerful tool to reduce transmission and case counts quickly.

Then, on October 22, a group of COVID-19 testing experts presented the Biden administration with a detailed strategy for overhauling America’s approach to testing.

The plan was to put rapid at-home COVID-19 testing into the hands of average citizens, allowing them to screen themselves in real time and thereby help reduce transmission.

The plan called for “Every American Household to Receive Free Rapid Tests for the Holidays/New Year.”

The big, bold idea for free home tests for all Americans to avoid a holiday surge, was killed by the Biden Administration.

=============

The reasons:

> “The Biden Administration took a vaccine-only approach … and didn’t support the notion of testing as a proper mitigation tool or therapeutic oral antiviral drugs.”

The Administration has had a single-minded fixation on vaccinating Americans left testing and therapeutics on the back burner for so long.

The Administration feared that at home rapid tests and therapeutics might somehow signal to wary Americans that they could skip vaccinations.

Officials failed to foresee how vaccine efficacy would wane over time and demand would plateau. 

> The FDA dragged its feet vetting and approving at home tests … valuing “exquisite sensitivity, rather than “public health utility”.

“If our goal is defined as public health, every test run last year was practically useless.”

While rapid antigen tests are less accurate than PCR tests, they are “extremely sensitive for very contagious people” … when they’re at peak viral load, these tests approach 100 percent sensitivity.” Source

> Many doctors opposed in home testing, viewing patient test results as theirs alone to convey.

Some doctors had even opposed home testing for pregnancy and HIV, arguing that patients who learned on their own about a given condition would not be able to act on the information effectively.

> There wasn’t capacity to manufacture over-the-counter tests at the required scale.”

The plan required an estimated 732 million tests per month.

The capacity problem was twofold: The FDA had authorized only a handful of different home tests, and those it had authorized could not increase manufacturing fast enough.

=============

Bottom line

> It wasn’t a matter of Biden not having thought ahead about the need for rapid tests (as he told ABC News on TV) … It was a matter of his team considering, and then rejecting, a plan to have hundreds of millions of home tests available now..

> Biden’s recently announced plan is widely regarded by experts (i.e. “the science”) as a totally inadequate “exemplar of too little, too late …

We need several billion tests and have needed them for over a year to help prevent spread.”

Advance government orders like Operation Warp Speed’s for vaccines would have accelerated production of anti-virals.”

> The Biden administration has lacked “the imagination to have an Operation Warp Speed-level programs for testing and therapeutics.”

“The White House, in baseball terms, is playing small ball. When it comes to rapid testing, they’re bunting the players along.”

“Vaccines have saved hundreds of thousands of lives, but many more lives would have been saved if anti-viral oral treatments were available sooner. The drugs represent a huge pharmaceutical success but a missed government opportunity.”

> So, as COVID-19 is exploding again, we’re stuck with “endless lines of desperate Americans clamoring for tests in order to safeguard holiday gatherings” … and, rationing of live-saving anti-viral drugs.

Local example: One of the most expansive urgent care chains in the Maryland-Virginia market restricts testing to symptomatic patients only … and warns patients of 6- hour wait times (in a waiting room with a hundred or so other symptomatic patients)

=============

In Biden’s own words:

Anyone, anyone who needs to be tested should be tested at no charge, at no charge.

Tests should be available to all who need them and the government, the government should stop at nothing to make that happen.

No excuses should be made.

The administration’s failure on testing is colossal and it’s a failure of planning, leadership, and execution.”  

Oh yeah, that was in March 2020 in a blast against Trump.  Transcript

As Forrest Gump would say: “What goes around, comes around”

Finally, I agree with Fauci on something…

September 13, 2021

But, it raises a big question: Why isn’t there more emphasis on antibody testing?
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OK, Biden has declared war on the unvaccinated.

Putting aside the constitutional questions, I’m swayed by the opposition’s arguments re: natural immunity.

On CNN (of all places!), Dr. Sanjay Gupta challenged our chief political-scientist Anthony Fauci.

Paraphrasing Gupta’s question: The science (and its data) show that unvaccinated covid survivors have a much higher level of antibodies than previously uninfected vaccinated people.  So, what’s the logic for making those people take a potentially risky vaccination shot?

Watch the 1-minute video posted here to see the exact question and Fauci’s surprising (to me) answer.

image

Fauci’s response: “I don’t have a really firm answer for you on that”.

He then goes on to diminish the referenced Israeli study asserting that it didn’t investigate the “durability” of natural immunity (i.e. whether the protection diminishes over time and, if it does, how quickly).

Wrong, Dr. Fauci.

The Israeli study did test the durability and concluded that natural immunity is at least as durable as vaccine durability.

Which begs a broader question:

Why aren’t we doing more antibody testing to calibrate the level of immunity that people have?

First, that would use “the science and the data”  to determine whether an unvaccinated person really needs to get vaccinated.

Second, it would provide a scientific determination of whether (or when) vaccinated people (like me) might need to get a booster.

Rather than “how many weeks after last shot”, the criteria would be “how many antibodies?”.

Why use time stamped average rate of protection diminution instead of a precise antibody count?

And, why make protected people take a shot?

.

MUST READ: How will we know when we’ve turned a COVID-19 corner?

April 13, 2021

Stay focused on the number of Daily New Deaths!
==============
This is a relevant excerpt from a long ago prior post (May 2020)
==============

Why have I centered on Daily New Deaths (DND)  as my key metric?

First,  saving lives is our paramount objective, right?  If yes, it should be our focus metric.

Second, I think that most other metrics that are being bandied about are quite problematic.

Counting deaths — while a bit macabre — is a more reliable process than counting, say, the number of infected people.

Sure, I’d like to know the number of people infected with COVID-19.

But, unless everybody — or at least a large statistical sample — is tested, the number of confirmed cases is subject to lots of statistical issues.

Most notably, who is being tested and who isn’t? What about the asymptomatic “hidden carriers”? What are the criteria for confirming a COVID infection? What about false positives (and false negatives)? How to standardize the reporting processes across states? How to keep governmental units from fudging the numbers?

Importantly, if testing increases, then confirmed cases goes up.

Is that an indication of more virus spread or just a reflection of more testing?

I sure can’t tell.

=============

Again, counting fatalities is probably the most reliable metric.

Fatalities are discrete events – so they’re countable.

Still, even deaths may have some counting imperfections.

For example, many non-hospitalized people die and are buried without autopsies.  Some may be uncounted COVID victims.

On the other hand, some people may die and be diagnosed with COVID infections. That doesn’t necessarily mean that COVID killed them.  That’s especially true with COVID since it’s  most deadly for people with other health problems.

And, as we stated above, the definition of COVID deaths has changed:

COVID-related” means “COVID present”, not necessarily “COVID caused” … and that, along the way, “present” was redefined from “confirmed” to “presumed”

Further, COVID deaths are a function of two drivers: the incidence of the virus … and, the nature, level and timing of therapeutic healthcare.

Said differently, more effective therapeutic healthcare will dampen the death toll.

==============

Bottom line:  “Daily New Deaths” is the number we should be watching.

If it shows a consistent downward trend, then we’ll know we’ve turned the corner.

If it stays stable (at a high level) or turns upward, we’ll know that we’re in deep yogurt.

NY Times: Positive Covid test results misleading…

March 10, 2021

Up to 90% of people testing positive carry inconsequential amounts of the virus
=============
Originally posted 10/16/2020

When COVID case counts surged in July, most “experts” said that — after a time delay — fatalities would surge, too.

They didn’t, causing a lot of head-scratching.

Now the consensus explanation for a statistically significant decline in the infection-to-fatality rate (IFR)  is that (1) more asymptomatic people (i.e. minimally effected) were being tested (2) those testing positive were skewed to to younger age groups with IFR rates, and (3) more effective medical treatment and therapeutic drugs were saving more seriously effected patients.

image

The New York Times has served up a scientific explanation…

(more…)

If I test positive for COVID, am I infected?

March 10, 2021

The answer may surprise you, and it has big implications for how individuals & organizations respond to positive Covid test results.
=============
Originally posted 05/27/2020; updated January 17, 2022

In a prior post, we reported that “Asymptomatics” are not rushing to get tested and provided some subjective reasons why that might be (e.g. no doctor referral, high hassle factor, privacy concerns).

OK, let’s up our game a notch or two and throw some math & economics at the problem.

==============

I’m a fan of “Freakonomics” … the popular call sign for a discipline called Behavioral Economics … the study of the rationality that underlies many seemingly irrational decisions that people sometimes make.

And, in my strategic business analytics course, I used to teach something called Bayesian Inference … a way to calculate probabilities by combining contextual information (called “base rates” or “priors”) with case-specific observations (think: testing or witnessing).

Today, we’ll connect Freakonomics and Bayesian Inference and apply them to the COVID testing situation…

(more…)

MUST READ: How will we know when we’ve turned a COVID-19 corner?

February 18, 2021

Stay focused on the number of Daily New Deaths!
==============
This is a relevant excerpt from a long ago prior post (May 2020)
==============

Why have I centered on Daily New Deaths (DND)  as my key metric?

First,  saving lives is our paramount objective, right?  If yes, it should be our focus metric.

Second, I think that most other metrics that are being bandied about are quite problematic.

Counting deaths — while a bit macabre — is a more reliable process than counting, say, the number of infected people.

Sure, I’d like to know the number of people infected with COVID-19.

But, unless everybody — or at lest a large statistical sample — is tested, the number of confirmed cases is subject to lots of statistical issues.

Most notably, who is being tested and who isn’t? What about the asymptomatic “hidden carriers”? What are the criteria for confirming a COVID infection? What about false positives (and false negatives)? How to standardize the reporting processes across states? How to keep governmental units from fudging the numbers?

Importantly, if testing increases, then confirmed cases goes up.

Is that an indication of more virus spread or just a reflection of more testing?

I sure can’t tell.

=============

Again, counting fatalities is probably the most reliable metric.

Fatalities are discrete events – so they’re countable.

Still, even deaths may have some counting imperfections.

For example, many non-hospitalized people die and are buried without autopsies.  Some may be uncounted COVID victims.

On the other hand, some people may die and be diagnosed with COVID infections. That doesn’t necessarily mean that COVID killed them.  That’s especially true with COVID since it’s  most deadly for people with other health problems.

And, as we stated above, the definition of COVID deaths has changed:

COVID-related” means “COVID present”, not necessarily “COVID caused” … and that, along the way, “present” was redefined from “confirmed” to “presumed”

Further, COVID deaths are a function of two drivers: the incidence of the virus … and, the nature, level and timing of therapeutic healthcare.

Said differently, more effective therapeutic healthcare will dampen the death toll.

==============

Bottom line:  “Daily New Deaths” is the number we should be watching.

If it shows a consistent downward trend, then we’ll know we’ve turned the corner.

If it stays stable (at a high level) or turns upward, we’ll know that we’re in deep yogurt.

 

NY Times: Positive Covid test results misleading…

October 16, 2020

Up to 90% of people testing positive carry inconsequential amounts of the virus
=============

When COVID case counts surged in July, most “experts” said that — after a time delay — fatalities would surge, too.

They didn’t, causing a lot of head-scratching.

Now the consensus explanation for a statistically significant decline in the infection-to-fatality rate (IFR)  is that (1) more asymptomatic people (i.e. minimally effected) were being tested (2) those testing positive were skewed to to younger age groups with IFR rates, and (3) more effective medical treatment and therapeutic drugs were saving more seriously effected patients.

image

The New York Times has served up a scientific explanation…

(more…)

“COVID tests are almost laughably unreliable”

October 6, 2020

That’s the cut-to-the-chase observation of one pundit … and, the WH outbreak appears to support his conclusion.
==============

Loyal readers know that I’ve been harping from the get-go that the “testing, testing, testing” strategy was haphazard (wrong people being tested) … and potentially problematic (false negatives and false positives).

Well, the chickens have come home to roost … so, maybe the issue will start getting the attention it deserves.

This CNBC headline pretty much sums things up:

image

Specifically, the White House has relied on a COVID screening strategy intended to bubble-wrap Trump from the virus.

Staffers, guests and reporters have all been required to be tested for the coronavirus with Abbott Laboratories’ ID Now test before entering White House grounds.

That test is a rapid molecular test that can produce results in as little as 15 minutes.

So, how did the “bubble” get breached?

(more…)

Flashback: Ohio Gov. DeWine tested negative … after testing positive.

October 2, 2020

Not a surprise according to Bayes’ Theorem
===========

According to the NYT and many other sources…

As part of a screening by the White House, Mr. DeWine first received an antigen test, a newer type of test that provides faster results but is less accurate than traditional laboratory testing.

He tested positive for Covid-19

He was later twice-tested using a more standard procedure known as polymerase chain reaction, or P.C.R., an accurate but time-intensive method that requires samples to be processed at a laboratory.

That test result was negative for the Covid-19.

DeWine’s experience is a classic “false positive” … to be expected based on Bayes’ (Statistical) Theorem.

image

Let me explain…

(more…)

If I test positive for COVID, am I infected?

October 2, 2020

The answer may surprise you, and it has big implications for test & trace.
=============

In a prior post, we reported that “Asymptomatics” are not rushing to get tested and provided some subjective reasons why that might be (e.g. no doctor referral, high hassle factor, privacy concerns).

OK, let’s up our game a notch or two and throw some math & economics at the problem.

==============

I’m a fan of “Freakonomics” … the popular call sign for a discipline called Behavioral Economics … the study of the rationality that underlies many seemingly irrational decisions that people sometimes make.

And, in my strategic business analytics course, I used to teach something called Bayesian Inference … a way to calculate probabilities by combining contextual information (called “base rates” or “priors”) with case-specific observations (think: testing or witnessing).

Today, we’ll connect Freakonomics and Bayesian Inference and apply them to the COVID testing situation…

(more…)

The most incredible COVID statistic…

September 25, 2020

I’ve heard or read this stat several times:

29 large universities including Notre Dame, the University of North Carolina, and Illinois State had reported some 26,000 cases by Sept. 9 yet no hospitalizations.

I used to frequently remind my students that incredible means not credible … and, this stat certainly sounded incredible … so, I largely ignored it.

But, when the statistic was repeated in the WSJ, I decided that it was worth looking into.

Here’s what I found…

(more…)

“Science” takes another u-turn…

August 28, 2020

CDC covid testing guidance goes from haphazard to ass-backwards
==============

Earlier this week, the CDC revised its guidelines for covid testing.

For background, the CDC categorized people into “five populations” for which COVID-19 testing may be appropriate:

  1. Individuals with signs or symptoms consistent with COVID-19 (“aka “symptomatics”)
  2. Asymptomatic individuals with recent known or suspected exposure to COVID-19 (e.g. in close contact for more than 15 minutes with an infected person; living in a high COVID-19 transmission area;  having  attended a public or private gathering of more than 10 people (without widespread mask wearing or physical distancing)
  3. Asymptomatic individuals without known or suspected exposure in special settings (e.g. frontline medical personnel and nursing home caregivers)
  4. Individuals being tested to determine resolution of infection (e.g. to establish a safe return to work after a prior positive test)
  5. Individuals being tested for purposes of public health surveillance (e.g. to determine the prevalence of COVID-19 in a targeted locale such as an apparent hot spot city or campus)

The CDC previously recommended testing for people in categories in the first 3 categories.

Here’s the big change to the CDC guidance … and why it’s wacky.

(more…)

Ohio Gov. DeWine tests negative … after testing positive.

August 11, 2020

Not a surprise according to Bayes’ Theorem
===========

According to the NYT and many other sources…

As part of a screening by the White House, Mr. DeWine first received an antigen test, a newer type of test that provides faster results but is less accurate than traditional laboratory testing.

He tested positive for Covid-19

He was later twice-tested using a more standard procedure known as polymerase chain reaction, or P.C.R., an accurate but time-intensive method that requires samples to be processed at a laboratory.

That test result was negative for the Covid-19.

DeWine’s experience is a classic “false positive” … to be expected based on Bayes’ (Statistical) Theorem.

image

Let me explain…

(more…)

Birx: “Key metric that I watch is the positivity rate”

July 24, 2020

In yesterday’s post, I indicated that I was very disappointed with Dr. Brix’s answers  in a TV interview with Bret Baer.

One particular question & answer still has me scratching my head:

What is the key statistic that you track?

Birx’s answer: Test positivity (i.e. ratio of positive test results to total tests). It’s the most sensitive indicator and best early warning.

With all due respect, I think that Dr. Birx is confusing “positivity” with “prevalence”.

I’m way more interested in the latter prevalence: the percentage of the population that is currently infected with the virus.

Prevalence indicates how widespread the virus is at any point in time in a selected locale.

That gives me a sense of how safe it is to leave my house: How many people am I likely to run into who have the virus and may be contagious.

=============

Determining prevalence requires periodic random sampling of the population.

That’s not what’s being done now.

A representative sample of the local populations is not being tested.

Why is that a problem?

The positivity rate (Birx’s key metric) is a function of who shows up to be tested.

If only people with covid-like symptoms are being tested, then of course, the positivity rate will be high.

If there’s a groundswell of asymptomatic people, the positivity rate will likely be relatively low.

My hunch: The testing “sample” is skewed to people with symptoms.

In a prior post, we reported that “Asymptomatics” are not rushing to get tested and provided some subjective reasons why that might be (e.g. no doctor referral, high hassle factor, privacy concerns).

So, positivity is, at best, a very crude measure of prevalence.

=============

To that point, keep in mind…

(more…)

FDA okays “pooled” testing for COVID-19…

July 20, 2020

A potentially big first step to efficient testing
=============

image

Over the weekend, the FDA issued an emergency use authorization for pooled samples.

The Quest test is the first COVID-19 diagnostic test to be authorized for use with pooled samples.

Her are details from the FDA press release:

(more…)

Why is COVID testing still so haphazard?

July 15, 2020

Test results come too late for therapeutic decisions … and “the science” still can’t answer basic questions.
==============

Based on some back-of-the envelop arithmetic, I estimate that about 13 million Covid tests have been administered in the 3 weeks ending July 13

Note: The time period is strictly arbitrary.  And, since I don’t have all of the daily data series, I just derived rough estimates off the charts. I doubt conclusions would change much with a different time period or more precise numbers 

image

Now, let’s drill down on those numbers….

=================

Of the roughly 13 million tests that were reported, over 12 million (94%) came back covid-negative’.

Note: Practically all headline reporting is “confirmed cases” — the test results that were covid-positive. Total test minus positive results estimates negative results.

image

My 1st question is who the heck are these 12 million people who are testing negative … and why, in the first place, are they even being covid-tested.

Some possibilities:

  • They’re exhibiting flu-like symptoms that might indicate covid.
  • They know (or think) that they’ve been exposed to the virus … via a super-spreader person or at a superspreading event
  • Their employer is making them take the test (e.g. frontline healthcare workers)
  • They’re participating in a medical research project (e.g. a vaccine trial)
  • They’ve been selected to be part of a random surveillance sample
  • They’re trying to be good citizens by participating in the “test, test, test” program
  • They’re just curious as to whether or not they’re infected.

I think the top 5 categories are pretty legit.

The last 2 strike me as a waste of constrained testing capacity.

Regardless, wouldn’t it be nice to know how the 12 million sorts out by those categories?

Apparently, that sort of classification data isn’t captured at the  point-of-testing … or, public health officials just aren’t making the data available.

That’s too bad

===============

Moving on…

Less than 1 million of the 13 million tested Covid-positive … a “positivity rate” of 6%.

Who are these people and how are they treated when they’re tagged as infected?

I’d like to know:

  • How many present with severe, mild or no symptoms?
  • Do they have co-morbidities or not?  If yes, how many? Which ones?
  • What treatment plan is prescribed? Hospitalization? Quarantine? R&R?

Again, it appears that this sort of classification data isn’t captured at the  point-of-testing … or, public health officials just aren’t making the data available.

============

Bottom line: We need to focus constrained testing resources on therapeutic decision incidences … and, we need to gather and analyze more classification so that the testing helps pin down how this virus is acting.

Testing that simply increases the number of tests doesn’t seem to be getting us anywhere.

I made the same mistake that Gov. Cuomo is making …

May 29, 2020

… but, in my defense, I was only 9 years old at the time.
============

Flashback many years to my earliest little league baseball days.

1962 Ken & John - Little League

In our first game, the coach told us that — just like in the big leagues — he’d be  flashing secret signs to us when we were batting:

If he touched his cap, the sign meant “take the next pitch” … don’t swing at it.

If he brushed his chest, it meant “swing away”.

Simple enough…

Here’s what happened…

(more…)

I tested negative, so I’m not infected, right?

May 28, 2020

Yesterday, we reached into our toolkit and pulled out behavioral economics and Bayesian Inference.

Our big conclusion in that post was that if C-19 tests are 90% accurate and 5% of the people in our reference group are walking around infected, then roughly 2/3’s of all people who get positive test results are not infected … they’re so-called false positives.

Now, let’s change one of our assumptions.

In the prior post, we assumed that we were asymptomatic, have been sheltering-in-place (i.e. minimal social contacts outside of our homes) and don’t work in a COVID-prevalent environment … and we used 5% as our base rate (of virus prevalence among our reference group).

Now, let’s assume that the reference group we’re working with is elderly, has a comorbid medical history of respiratory and heart problems and is experiencing COVID-like symptoms (high fever, persistent cough), have had contact with an infected person.  That’s essentially the only group that initially qualified for coronavirus testing.  Lets, assume that 75% of the people in that reference group are, in fact, infected with the virus.

Here’s the Bayesian results chart would look like:

image

The question: what is the likelihood that the people who fit this profile are correctly diagnosed as having the virus (or not)?

(more…)

If I test positive for COVID, am I infected?

May 27, 2020

The answer may surprise you, and it has big implications for test & trace.
=============

In a prior post, we reported that “Asymptomatics” are not rushing to get tested and provided some subjective reasons why that might be (e.g. no doctor referral, high hassle factor, privacy concerns).

OK, let’s up our game a notch or two and throw some math & economics at the problem.

==============

I’m a fan of “Freakonomics” … the popular call sign for a discipline called Behavioral Economics … the study of the rationality that underlies many seemingly irrational decisions that people sometimes make.

And, in my strategic business analytics course, I used to teach something called Bayesian Inference … a way to calculate probabilities by combining contextual information (called “base rates” or “priors”) with case-specific observations (think: testing or witnessing).

Today, we’ll connect Freakonomics and Bayesian Inference and apply them to the COVID testing situation…

(more…)

MUST READ: How will we know when we’ve turned the COVID-19 corner?

May 26, 2020

Stay focused on the number of Daily New Deaths!
==============

Cutting to the chase, I’ve concluded that the most reliable number being reported is the number of COVID-19 related “Daily New Deaths”.

According to Worldometers – the best data aggregation site that I’ve found so far – there have been almost 100,000 COVID-19  related deaths in the U.S. so far.

image

Keep in mind that “COVID-related” means “COVID present”, not necessarily “COVID caused” … and that, along the way, “present” was redefined from “confirmed” to “presumed”

=============

From an analytical perspective, the chart of total deaths will, by definition, never crest and turn down. It’s rate of growth will eventually slow down, though, but that’s hard to read that from a chart.

So, I think it’s more useful to look at “Daily New Deaths” …. if that number keeps going up then, by definition, we haven’t turned the corner.

When Daily New Deaths start trending down then, by definition, we have turned the corner.

Here’s our charting of what Worldometers has reported since the first coronavirus cases were identified.

image

The dotted line is the 7-day moving average which smooths some of the day-to-day “noise” in the data.

Based on the 7-day moving average, it appears that the rate of growth of COVID-19 deaths trended downward since about April 21.

Bottom line: If you want to know if we’re starting to turn the corner, keep your eye on the number of COVID-19 related “Daily New Deaths”.

Choose the level of aggregation based on your specific interest … world, nation or state.

Note: I’ll be focusing on the U.S. national number … and the national number less the 3 state hot spots: NY, NJ, CT

=============

More specifically, why “Daily New Deaths”?

(more…)

Shocker: “Asymptomatics” not rushing to get tested.

May 21, 2020

Quick quiz: If you wanted to get tested for COVID-19, how would go about getting a test? What are your odds of actually getting tested?
==============

The Washington Post ran an obvious-became-evident exposé:  “As coronavirus testing expands, a new problem arises: Not enough people to test.”

These days, COVID testing capacity is said to be exceeding demand in some (many?) locales.

image

So, why aren’t people rushing to get tested?

(more…)

COVID: How about squeezing the data and doing some old-fashioned profiling?

May 12, 2020

Hint: Go back and ask people who have been tested or hospitalized.

=============

Finally, Gov. Cuomo has directed hospitals to ask new coronavirus patients for some demographic and behavioral information such as their occupation, usual transportation mode and neighborhood.

Cuomo says the early results from this info-seeking initiative and the state’s antibody testing have provided  some confirming data and some “shocking” revelations, including:

  • 96% had an underlying health condition (a.k.a. comorbidity factors); new admissions were predominantly minority, predominantly older; 22% came from nursing homes.
  • 66% of NY’s new coronavirus hospitalizations are people who are either retired or unemployed and not commuting to work on a regular basis … only 17% were employed.
  • The majority of recently hospitalized coronavirus patients are people who say that they have followed the precaution of staying home.
  • Only 4% in New York City said they had been taking public transportation.
  • A low percentage of new hospitalizations were essential employees — nurses, doctors, transit workers, grocery store employees — who were getting sick at work.
  • Sources: WSJ   NY Daily News

Of course, these sample sizes are small and the results may or may not be projectably true.

The point is that “they” should have been recording this sort of information from the get-go.

The plan is to start asking a battery of questions when people are tested for the coronavirus (both diagnostic and antibody testing, I assume) and when they’re admitted to the hospital.

That’s fine, but I’ve got a better idea…

(more…)

Do Americans really care about nursing homes?

May 7, 2020

Maybe it’s time for a national gut-check
==============

Earlier this week, there was a heart-wrenching story on TV.

A woman was telling the story of the Massachusetts state-run Holyoke Soldiers’ Home that had suffered over 80 C-19 fatalities. Her elderly father was one of the casualties.

She had been trying for weeks, to no avail, to speak with her father, or at least get a status report on his condition. Her first contact was when he was being wheeled to the coroner’s van.

clip_image002
click to see details

Of course, the daughter was heart-broken and observed “nobody seemed to care … they’re just old people”.

That struck a chord with me

Of course, people who have loved ones in nursing homes are concerned about their level of care.

At a minimum, they want their loved ones kept safe and comfortable.

But, what do we as a nation really think?

(more…)

NY Antibody Test: FINAL RESULTS

May 5, 2020

Over the weekend, Gov. Cuomo reported final results from the NY antibody test program..

Key Data:

12.3% of the NY state sample tested positive for coronavirus antibodies.

Note: The rate in NYC was 19.9%

That extrapolates to 2.4 million New Yorkers.

Given the current number of cases (327,374), 2.1 million (86.3%) of the already infected people were, by definition asymptomatic — having no or mild symptoms.

The implied deaths to infections rate is (1.0%).

image

The implications…

(more…)

Senate may be starting to ask the right questions re: testing.

May 3, 2020

“Why do we have to have symptoms to get tested?”
=============

The Senate (but not the Congress) is scheduled to get back on the job this week.

Roughly half the senators are 65 or older … and, thus, officially in the coronavirus’ “vulnerable” group.

So, it’s understandable that they’re eager that all colleagues have a clean bill of health before returning to the Senate chambers.

clip_image002

Here’s the rub…

(more…)

Help Wanted: Vice President of Contact Tracing & Testing

May 1, 2020

Warning: Read this before you apply for the job.
=============

Contact tracing & testing is front and center as a fundamental component of the Coronavirus Task Force’s plan to go forward.

Dr. Fauci has said (over & over again) that the process worked fine 30 years ago when he was fighting AIDs … and the media says that the test & trace model has been South Korea’s secret sauce fighting the coronavirus.

The essence of the process: Do diagnostic surveillance testing to ID people currently infected with the coronavirus, then trace back to ID the people with whom they’ve been in contact … then notify those people and test them … if they test positive, repeat the process … then again and again.

Sounds easy enough, doesn’t it?

clip_image001

But, it might not be as easy as it sounds.

Let’s run some numbers…

(more…)

Still more about the NY antibody test results…

April 29, 2020

What about the 3% of New Yorkers floating around while infected but asymptomatic?
==============

In a prior post, we squeezed the NY antibody test results pretty hard and estimated that about 600,000 New Yorkers are walking around at any one time infected with the coronavirus but exhibiting no or very mild symptoms. That means that about 3% of NY’s population are asymptomatic “hidden carriers” who may be unknowingly spreading the disease.

To understand their significance …

Most infectious disease epidemiology models are built on the “SEIR” construct: how many people are susceptible to a virus … of them, how many are likely to get exposed to it … of them, how many are likely become infected … and of them, how many are likely to recover, perhaps with some degree of immunity. The modelers then calibrate a virus’s behavior, estimating how long it takes people to move from susceptible to exposed to infected to final resolution (recovery or death).

clip_image001

My former strategy students should recognize the SEIR construct as a basic hierarchy-of-effects model, similar in design to, say, the classic marketing awareness – trial – repurchase model.

And, the spread effects are a classic Bass Diffusion Model application with infected people playing the role of “innovators” and susceptible people playing the role of “imitators”.

Let’s dive a little deeper…

(more…)

NY Antibody Test < UPDATE>

April 27, 2020

Phase 2 Results
===========

Gov. Cuomo reported Phase 2 results today.

Bottom line: Results are virtually identical to the Phase 1 results.

14.9% of the sample tested positive for coronavirus antibodies …  that’s up slightly from the Phase 1 results.

That projects up to 2.80 million New Yorkers.

Given the current number of cases (293,381), 2.6 million (89.8%) of the already infected people were, by definition asymptomatic — having no or mild symptoms.

The deaths to infections rate (.8%) was the same in both phases.

image

Squeezing the NY antibody test results…

April 24, 2020

Estimate: 3% of the NY state population are infected asymptomatics .. in circulation and potentially infecting others.
===========

In my business analytics course, I used to nudge students to “squeeze the rock” .. to get as much possible information out of each test or piece of data.

OK, let’s apply that principle today …

In a prior post, I opined that NY antibody tests were missing an information opportunity.  If they also swabbed the random sample for C-19 diagnostic tests, they’d also have an estimate of the number of infected asymptomatics who are currently in circulation in NY.

OK, it was a missed opportunity.

But, let’s not fret.

We can squeeze the data to get a rough-cut estimate of  the number of infected asymptomatics who are currently in circulation in NY.

Let’s do some arithmetic …

(more…)

NY’s missed testing opportunity

April 24, 2020

NY’s antibody testing program is highly commendable … and, it’’s already generating some very useful data.

But, I wonder..

Why aren’t they swabbing the same people for coronavirus diagnostic tests?

Doing so would tell us how many asymptomatic “hidden carriers” are currently in circulation.

My view: that’s one of the most important pieces of missing information … especially if it’s done on a periodic basis, say, weekly.

Would give us a good sense of how infectious the population is right now.


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