Friday, October 01, 2021

Who's afraid of the big bad COVID?

 kw: analysis, epidemiology, immune system, vaccination, herd immunity

The magic number is 7. We'll get back to this. 

The first thing to understand about a pandemic disease is the ratio of infection to symptomatic illness. Only then can you understand the progress of the disease through time in a population. This ratio is the first thing a national disease-monitoring organization such as CDC should determine. However, they have not, or if they did, they are not telling. I have sought other sources.

Dr. Anthony Fauci, without citing sources, claimed a few times that of the total number infected with SARS-CoV-2 virus, about 40% have no symptoms. An estimate out of South Korea claims 30%. But both of these are actually talking about asymptomatic carriers, those who have no overt symptoms but can still spread the disease. A few test surveys that I have been able to find showed a different picture. In a test survey, everyone in some population is tested, such as residents in a dormitory. Reports popped up, were public for a few weeks or less, and then vanished. They had a narrow range of numbers of the ratio of infection to illness. From these I got the magic number above. Stated a better way:

For every 7 persons whose test showed they were infected, one was ill and the rest had no symptoms.
 The range of magic numbers was between 5 and 9. For one test survey it was 10. Therefore, in the earlier stages of the COVID-19 pandemic, when there were no accurate tests, the numbers of known cases was only 1/7th of the actual number of infections.

If we combine that with the 30%-40% "claimed asymptomatic carrier" rate, we can surmise the following, for a total of 1,000 infected persons:

  • 143 will be ill at some point (we're not counting deaths yet; some of these will die).
  • Between 61 and 95 will be "carriers" who have no symptoms, for a total of 204 to 238 who can infect others.
  • The remaining 762 to 796 who are infected will recover without consequence, for themselves or for others.

Now to re-examine the first bullet point above: How many of the 143 will die? Spoiler: less than 2, and maybe much less than that.

I am going to use data from the charts supplied at Worldometer, as faulty as it is. The definition of a "Case" has changed over time. Early on, people with certain symptoms were "presumed positive". Later, testing was implemented. To date, in the U.S. about twice as many tests have been performed as there are persons in the country. However, there are those who get a test every week, some (like myself and my wife) who have been tested 3-4 times, and well over half of U.S. residents have never been tested. At the present time, the number of "cases" includes test results, which depends on the accuracy of record-keeping (We all have heard stories of people who were in line to get a test, had "signed in at the door", and then before getting tested, opted out and left; later they got a letter in the mail stating that they had tested Positive. Maybe the person in back of them in line was the one really tested, or something. We'll never know).

There is the further problem with "no Flu season in 2020-21". Really? Is that believable? Reasonably accurate tests for SARS-CoV-2 were just coming into use during the winter of 2020. COVID "cases" were among the "presumed positive". I contend that between 30,000 and 60,000 U.S. residents who are counted as "COVID deaths" actually died of Influenza. There are also those who died while they were infected with the virus, but they did not die OF the virus (car accidents, suicide, etc.). News of such events is being suppressed, so it is hard to gather statistics. Let's hope the number is small. With all those disclaimers, let's look at this chart, taking it (mostly) at face value.

The blue and brown curves are 7-day averages, as calculated at Worldometer. Blue is cases reported each day, however such cases were determined. This is for the U.S., and the axis to use is labeled "100k" and so forth. Five waves of infection can be seen; they peaked in April 2020, late August 2020, January 2021, April 2021 and late August 2021.

Each peak has a corresponding peak in daily deaths, the brown curve. The axis is labeled "2k" and so forth. These curves are scaled to have visible parity during the third wave. Note that the peaks in deaths and the curves for daily deaths are offset from the peaks and curves for cases…except for the first wave. At the beginning, people didn't get help until they were at death's door, so many of those who died did so within a day of being admitted to a hospital, and they had been reported as a "case" on the day of admittance. Thus, let's look at the same chart, with cases shifted 15 days back, which makes the third wave overlap as well as possible. 

This presentation makes the dates harder to discern. I presented a similar chart on August 1, just 2 months ago, when the fifth wave was just beginning, stating "Herd immunity has arrived." This conclusion was based on the anomaly about Wave 4: there was no peak in the death rate, and during the summer of 2021 case rates were lower than at any time since mid-March 2020.

The 5th wave is the Delta wave. It is smaller than Wave 3 because it is occurring primarily among the unvaccinated (in which I count those formerly infected: "vaccinated by God"). It also appears to have about a 15-day delay between discovery and death. However, look at the subtle vertical shift over time. The death rate is lower in proportion during Wave 5 than it was previously. And the gorilla in the room is the very high death rate during Wave 1.

What happened during Wave 1? Firstly, we had no clue what was going on. There were no effective treatments. President Trump ordered certain companies to ramp up the production of ventilators. It turned out that ventilators caused more deaths than they prevented. They aren't supposed to be used for weeks at a time. But even more, many of these deaths occurred in nursing homes where the virus ran rampant. This was aggravated in five states whose Governors ordered COVID patients moved from hospitals back to the nursing homes they came from, creating the first super-spreader events. 

Secondly, there were no effective medicinal interventions yet. Now there are two for early use (coded IVM and HCQS), and also monoclonal antibody treatments such as Regeneron, which was used to treat President Trump. Thus, the blast of early deaths represented the "low hanging fruit". A large proportion of the most vulnerable Americans died in Wave 1. Most variants of the virus that have arisen later cause fewer deaths, and we have medicines that work better. So let's look at another couple of charts.


For these I used the 7-day averaged number of cases or deaths at the peak of each wave. These are not totals for each wave, be clear on that. For a few cases in one state or another, and in the U.S. during Wave 4, where there was no peak in the death rate, I used a date 15 days delayed from the peak in cases.

The chart on the left has the data for the U.S. along with the five states whose governors forced COVID patients into nursing homes. Each bar represents the ratio of peak death rate divided by peak case rate, in each wave. The chart on the right has data for seven states I found of interest, including some in which I have lived. The one I find of particular interest is South Dakota (I lived there 8 years), which seems to have had a better handle on this disease than the rest, particularly in Waves 1 and 5.

The "easy take-away" is this: During Wave 1, D/C was about 7% nationwide, ranging from 4.5% to 9.5% for the five states shown on the left, and (except for NH) between 1.7% and 4.5% for the seven states shown on the right. The death rate has continued downward since then.

While state numbers hop around a bit, the national averages for the five waves are

7%, 1.7%, 1.4%, 1.0%, 1.1%

Let us return to the magic number, 7. On average, for 7 infections, there is one illness. Is all the testing finding every infection, whether ill or not? Not really. The vast majority of tests are done by those who either think they are sick, are feeling sick, or fear/think they have been exposed. So, if there are 6 people out there with no symptoms for everyone who has symptoms, and very few of those 6 are getting tested, they are still not known.

We were told that we needed to achieve 70% "fully vaccinated" to gain herd immunity. That was based on an infectivity rate for the Alpha variant, which is pretty much out of the picture by now. Back to variants in a moment. To date (Oct 1, 2021), just over 185.25 million Americans are recorded as fully vaccinated. This is called 56.1% of the population in news reports, but of course no children under age 12 have been vaccinated, and it isn't certain that they ever ought to be, at least with today's vaccines. That's 48 million, or 14.4% of the population. So the proportion of those12 and older who are fully vaccinated is about 65%. Getting close! But let's remember, the 2-shot "vaccines" are claimed to be 95% effective, while the one-shot version is 65% effective. We can expect about 90% overall effectiveness, so the "actually immune" adults in the U.S. total about 58.5%. One more factor must be considered.

The number of past infections that have resulted in recovery is 33.7 million, or 11.8% of persons 12 and older. 58.5+11.8 = 70.3%. By the criterion set by the CDC, we have achieved herd immunity. More vaccinations and more recoveries happen every day, so we are moving farther and farther into "herd immunity" territory.

So what's with Wave 5? I call it the Delta Wave. A word on variants.

There are many "serotypes" of the SARS-CoV-2 virus. A year ago it was reported that about 30 were circulating in the U.S., and more than 100 were known in China. It's practically impossible to get useful data out of China any more, so we don't know how many serotypes exist. A Serotype is a minor variation in the RNA of the virus. Not all have any practical effect. But a few do. The serotypes are grouped into families by RNA similarity and by clinical measures including infectivity and virulence. So far, there are 12 such Variants.

Infectivity is a measure of how many virus particles one must ingest to cause an active infection, for a person of "average immunity" (a quantity that has never been quantified). Those 5%-10% of vaccinated persons for whom the vaccine "didn't take" have lower immunity, didn't respond strongly enough to the mRNA agent in the vaccine, and so didn't develop a useful antibody defense. They were easier to infect before, and remain easier to infect. For most of us, there is some number, perhaps 1,000 particles, that are sufficient to swamp our early immune response and trigger active infection (whether we ever get symptoms or not, and I picked 1,000 "out of the hat"). We may be exposed to 100 particles several times, and out body fights them off, all the while getting more "wise" to the virus. That produces natural immunity without infection.

Reversing the logic, we have the case spreading rate. For a virus of average infectivity, someone who is infected might infect two other persons during his or her period of active infection. The 70% figure for achieving herd immunity was based on a case spreading rate of 3. I have read claims that the Delta variant is more infective (a smaller number of particles are sufficient to cause active infection), such that the case spreading rate is 6. 

Some claim that if this rate is greater than 5, herd immunity is no longer possible. That is nonsense. Those who state such things have their math wrong. They are using a simple ratio, but the math actually requires inverting a Weibull distribution, and never goes to 100%, meaning that herd immunity is always possible. However, it does get harder to achieve when infectivity is greater. For example, polio has a very high infectivity, as does measles, but we rely on herd immunity in both cases by striving for vaccination rates of 95% of the population, primarily by requiring all school children to be vaccinated for measles and polio (and a bunch of others).

Virulence refers to the likelihood of serious illness or death. If we look at Wave 1 above, it appears that virulence was such as to cause a 5% death rate, before we found effective treatments, and now it is about 1%. Untreated, AIDS and Ebola have a near-100% death rate. Influenza has a virulence about 1/10th as great as SARS-CoV-2, with a great range depending on the yearly variant.

So, although there are hundreds of serotypes out there, we hear of only Variants ranging from Alpha to Mu, the 1st and 12th letters of the Greek alphabet. Waves 1 through 5 were due to Variants Alpha and Lambda (11th). A Variant is a collection of similar serotypes. Delta was the fourth variant identified, but was kept out of the U.S. until late this summer. Now it is dominant.

If the Delta variant were to arrive in a totally naïve population, a big, big Wave of infections would occur. The comparatively smaller size of Wave 5 shows that it is occurring among the non-immune, which presently comprise 30% of adults in the U.S. All the variants so far known cause only mild infection in the vaccinated. Yes, there have been a number of vaccinated people who caught the disease and died. They are among the 5%-10% identified earlier. The mRNA vaccine didn't produce a useful response in them.

Now, a final word about the magic number, 7. For at least Waves 1 through 4, reduce the death rate by a factor of 7 to get a true death/case ratio. It is likely also true for Delta, so we find that actual death rates for the five waves are:

1.0%, 0.25%, 0.2%, 0.14%, 0.16%

That's a low death rate, and I repeat, we have achieved herd immunity for Alpha and Lambda, and we're on the way to achieving it for Delta.


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