How deadly is the coronavirus?

[Leongsam]

How deadly is the coronavirus?

By Lisa Boothe, opinion contributor — 04/04/20 09:00 AM EDT 1,838
The views expressed by contributors are their own and not the view of The Hill



How deadly is the coronavirus? It is a simple but vital question that we don’t know the answer to right now. With American lives and livelihoods on the line, we need a science-based baseline from which to make public policy decisions. Hopefully those answers come sooner than later as the White House looks to do random sampling, something I recently reported.

To be clear, every single life has value, and the overburdening of hospitals in places such as New York City is real and devastating. The toll on our doctors and nurses, many of whom have contracted the coronavirus by selflessly putting their own lives on the line to save others, is also real. We mourn the loss of each precious life and are in debt to the heroes on the front line.

The economic toll of shutting down nonessential businesses across the country is also real. A record-shattering 10 million Americans filing for unemployment in just two weeks and the largest bailout in United States history — $2.2 trillion — are sobering numbers that reflect the economic calamity we are facing. As government and public health officials make decisions of enormous magnitude, shouldn’t we know how infectious and lethal the coronavirus is?

That is why random sampling is important. John Ioannidis, a Stanford epidemiologist who is famous for debunking bad research, has been pushing for it. He told me that random sampling is needed and could be done with a couple of thousand tests. When I told him that I previously worked in the polling industry, he put it in terms that resonated with me. He said, “Random representative testing is like polling. We run thousands of opinion polls in this country. We should similarly get a representative sample of the population and get them tested. It is just so easy.”

A recent television interview with Anthony Fauci, director of the National Institute of Allergy and Infectious Diseases and member of the White House Coronavirus Task Force, underscores the need. After estimating that 100,000 to 200,000 Americans could die of the coronavirus, he said that projections are a “moving target” and that models are “only as good and as accurate as your assumptions.” But how good are models if the data is insufficient?

Ioannidis warned of a potential evidence fiasco in a recent op-ed for Stat. He wrote, “The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable. Given the limited testing to date, some deaths and probably the vast majority of infections due to SARS-CoV-2 are being missed.”
Eran Bendavid and Jay Bhattacharya, also professors at Stanford, echoed that concern in The Wall Street Journal, writing, “The true fatality rate is the portion of those infected who die, not the deaths from identified positive cases.” They speculate that due to how infectious the coronavirus appears to be, and because tens of thousands of people traveled from Wuhan to America in December, millions of Americans could have been infected.

Random sampling will tell us what percentage of the population has the coronavirus and its lethality. Only testing the very sick skews mortality rates and leaves us in the dark about how many Americans are unknowingly walking around asymptomatic or with mild symptoms. Looking at other countries’ data also has its challenges; age structures, climate differences, quality of health care systems and testing all vary.

The elimination of red tape and point-of-care innovations by companies such as Abbott Labs have made testing easier and more readily available. To date, the United States has administered more than 1 million tests. That means we now have the capacity to test those in need and to get better data.
With so much at stake, we need to have the best data possible through random sampling — and it needs to be done now.

 

[ChanRasjid]

Yes! I think I understand random sampling. But I think no government would care to do it.

The rate of true infection rate in a country may be found as a good and large enough random sample test for covid-19 would give a very good approximation of how much of the population is infected. Then we monitor how many of those tested positive would finally die and it would give us a true fatality rate for this pandemic.

We can do it but it still need some resources. In many countries we do have a digital database of all residents within a region. In Singapore we could just select a random sample from a constituency. We then send teams to visit the selected person and have testing done on them; but the testing should be done within a short time period - say within 3 days (the sample may already have people already tested and some may even be in ICU; so this group may also be included). There is no need to pass a parliamentary bill as many people will cooperate for such a scientific study.

But I think no organization nor government would do such a random study. Governments are - in general - lethargic and would only act when circumstances force them to act.

Chan Rasjid.
Singapore.

"Chemical Analysis Of Plain Distilled Water May Refute Mass-Energy Conservation Of E=mc²"
"The Relativistic Mechanics of E=mc² Fails"; E=mc² is wrong.
"Is Mass Spectrometry Accurate"; Penning trap cannot measure atomic mass.
"Coulomb Electric Gravity"; gravity is all Coulomb electric.
http://www.emc2fails.com

 

[Leongsam]

Yes! I think I understand random sampling. But I think no government would care to do it.

The rate of true infection rate in a country may be found as a good and large enough random sample test for covid-19 would give a very good approximation of how much of the population is infected. Then we monitor how many of those tested positive would finally die and it would give us a true fatality rate for this pandemic.

We can do it but it still need some resources. In many countries we do have a digital database of all residents within a region. In Singapore we could just select a random sample from a constituency. We then send teams to visit the selected person and have testing done on them; but the testing should be done within a short time period - say within 3 days (the sample may already have people already tested and some may even be in ICU; so this group may also be included). There is no need to pass a parliamentary bill as many people will cooperate for such a scientific study.

But I think no organization nor government would do such a random study. Governments are - in general - lethargic and would only act when circumstances force them to act.

Chan Rasjid.
Singapore.

"Chemical Analysis Of Plain Distilled Water May Refute Mass-Energy Conservation Of E=mc²"
"The Relativistic Mechanics of E=mc² Fails"; E=mc² is wrong.
"Is Mass Spectrometry Accurate"; Penning trap cannot measure atomic mass.
"Coulomb Electric Gravity"; gravity is all Coulomb electric.
http://www.emc2fails.com

Current available data puts the figure at about 1% of a random sample. It could well be double that or more once antibody tests are developed to detect who had the infection and is not better.

 

[Leongsam]

nationalreview.com

The Case for Randomly Testing the General Population for the Coronavirus | National Review
About Robert Zubrin

5-7 minutes

Medical staff at an NHS drive through coronavirus disease (COVID-19) testing facility, Chessington, England, March 30, 2020. (Peter Nicholls/Reuters)
Otherwise, we are flying blind.

In the face of the current coronavirus pandemic, authorities are taking measures that are having massive negative economic impacts. Some say that these measures are wildly unwarranted. Others, that they are disastrously insufficient. Who is right?

Nobody knows. No one can know what the right course of action is, because the available data to provide a basis for these enormously consequential decisions is woefully inadequate. The most important statistics we need to know to develop a strategy to deal with the situation are the size of the pandemic and its lethality. Current data provides no basis for accurate estimation of these vital metrics.

For example, as of the morning of March 30, Johns Hopkins reports that 143,532 Americans have tested positive for COVID-19, with 2,572 deaths. If taken at face value, this would suggest that the infection rate among Americans is 0.044 percent, with a 1.8 percent death rate among those infected.

But we know that such a conclusion would be inaccurate, because millions of people feeling symptoms are being turned away by testers, and there must be millions more, with and without symptoms, who are choosing not to volunteer for testing. So, without doubt, the size of the infected population is being underreported, perhaps grossly so.

The shortage of testing has led to a situation where only VIPs can be sure of getting tested if they suspect illness. Thus we hear about Tom Hanks, Prince Charles, and Boris Johnson testing positive, but how can any such assemblage provide a statistical base? Well, there is the U.S. Congress, where four House members and one U.S. senator have tested positive for COVID-19, for an infection rate of 1 percent and a death rate of zero. But Congress, while arguably politically representative of America at large, is hardly an optimal sample for medical polling purposes. Plausible arguments can readily be made why congressmen should have either higher (they attend lots of meetings) or lower (they don’t take mass transit) infection rates than the general population.

To get the right answer, we need to random-test the public. We don’t need to test all 327 million citizens — although, when feasible, that would be very desirable for the purpose of identifying immune individuals and putting them back to work. For the purpose of getting a rough estimate of the size of the infected population, we need to random-test only about 1,000 people nationwide. That is the approximate size of most election polls, and, provided that reasonable care is taken to ensure that the sample is representative of the electorate, such polls can generally predict the outcome within plus or minus 3 percent. It’s true that occasionally a 45 percent–polling underdog can pull off an upset victory, but never a 20 percenter, let alone a 1 percenter. Limited polls might not always predict the winner, but they inevitably show who is in the competitive range. For purposes of quantifying the epidemic, that would be an enormously valuable correction to our current state of ignorance.

It is also probable that deaths by coronavirus are being underreported, or overreported, given opportunistic infectious diseases, notably pneumonia. There is reason to suspect this is the case for Germany, which reports 560 deaths in 63,929 cases (compared with 2,612 deaths in 40,751 cases in France), and certainly Russia, which claims nine deaths in 1,836 cases. So all deaths from disease should be tested to see if coronavirus played a role. But clearly, the great unknown that needs to be measured is the prevalence of COVID-19 among the population that is outside the medical system altogether.

Let’s say that the poll tests show that the general infection rate is, in fact, the same 1 percent as seen so far with Congress. That would mean that instead of there being 120,000 infected Americans, there are over 3 million. It would also imply a much lower lethality rate than 1.8 percent, although care must be exercised in drawing conclusions in this regard, since the deaths occurring today need to be compared against not today’s infected population but what its size was in the recent past, as there is a time lag between infections, illness, and death. Once that average time lag is assessed, the true lethality rate can be computed. This is very important, because if the lethality rate really were 1 percent, then, lacking alternatives, it could make sense to allow risky treatments that kill 0.1 percent of patients, whereas this would not hold true if lethality were only 0.01 percent.

If we can increase the nationwide random-testing rate to 5,000 per day (about twelve daily in each congressional district), then once the time lag is assessed, repeated poll testing of the population would provide predictive information about what to expect in the near future, giving advance intelligence to our defenders about how hard the enemy virus will hit us and when and where such blows will strike.

We need that intelligence if we are going to win this war. Random poll testing of the general public should begin without delay.