“I believe in innovation, and the way you get innovation is you fund research and you learn the basic facts.” – Bill Gates


Even Less Positive 

JM is negative. So are PR, RT, and SC. K is positive. So is PB, my trainer.

PB’s result was not a surprise. In the week between contracting the virus and having symptoms, I trained with him three times. That was three hours of proximity when I was breathing heavily indoors. So that makes two positive, four negative, and eight that are currently asymptomatic but waiting for results.

I’m back to reading the most recent studies, trying to answer the questions everyone is asking:

* How deadly will the current surge be?

* How close are we to herd immunity?

* Is the current strain of the virus less virulent than the older ones?

It’s now six months since we had our first confirmed case of COVID-19 in the US. Back then, the facts were very few and the models for predicting the infectiousness and lethality of the virus were very poor. Some of the important speculations made at the time were scarily wrong.

Today, there is loads of data to look at.

The problem is that the Corona Crisis has become so politicized that it’s impossible to gather the information you need from press reports. The left-leaning media reports almost exclusively findings and conclusions that are frightening. The right-leaning media reports almost exclusively findings and conclusions that are optimistic.

So what I’m doing is looking at as many studies as my research assistant and I can find, note the results, ignore the conclusions, and focus on the facts.


How deadly will the current surge be?

 Here are the facts:

As I said on Monday, the current surge began a month ago. On June 8, there were 21,269 new cases and 908 new deaths reported in the US. As I write this, on July 7, the number of two-week-average new cases in the US is 44,343 with 705 two-week-average new deaths. The number of two-week average new cases two weeks ago was 25,274, while the two-week-average new deaths was 675. That represents a surge of 75.5% in new cases, but an increase in average new deaths of only 4.4%.

Here’s an example of the bias you’ll see in interpreting the facts. While the right-leaning media was pointing out the “good news” that the rise in the death rate has been very small, the left-leaning media was reminding us that there is an average two- to three-week lag time between symptoms and death. “Expect to see a surge in deaths soon,” they said.

That didn’t happen.

So the left-leaning press moved on to scarier stories (like the diminishing ICU bed capacity in Texas and Florida). And the right-leaning media has been reporting on studies that suggest the current strain of the virus might be less virulent than what we experienced in March and April.

Whatever the reason for the currently low death rate, the fact is that new cases are still climbing. And they are likely to keep climbing until social distancing becomes widely practiced among the younger populations.

My guess is that the current surge in new cases will peak soon, probably in the next week or two, and then it will fall, almost as fast as it climbed. But then we will have a second wave in September or October, unless, by some miracle, we can achieve herd immunity before then.


So, how close are we to herd immunity? 

Viruses don’t extinguish themselves. They proliferate until their basic reproductive rate (R0) drops below 1. And that happens only when the percentage of the population that has achieved immunity reaches a certain threshold.

The classical model that epidemiologists use to predict herd immunity estimates that the threshold for COVID-19 is around 60% of the population. But the model assumes that a population gains immunity due to a vaccination program, rather than as a result of infection during an outbreak.

Meanwhile, mathematicians at the University of Nottingham in the United Kingdom and Stockholm University in Sweden realized that different groups of people within a population spread infections at different rates. And when they updated the classical model to take into account rates of transmission in different age groups and among people with varying levels of social activity, the threshold for herd immunity was way below 60%.

The new model suggested that herd immunity would be achieved once 43% of the population had contracted the virus. At that point, the infection would stop spreading and the outbreak would come to an end.

Two other studies have suggested that the pandemic could be over sooner and be less lethal than feared.

One, conducted by the Karolinska Institute in Sweden, found that the prevalence of immunity to the coronavirus that causes COVID-19 might be much higher than indicated by previous research. And a study by researchers associated with the University Hospital Tübingen in Germany found that people who have been previously infected with versions of the coronavirus that cause the common cold also have some immunity to the COVID-19 virus.

In the Swedish study, researchers performed two tests. One was meant to identify the presence of antibodies produced in response to COVID-19 infections. The other was to check for T-cells, another virus-fighting component of the immune system.

“One interesting observation was that it wasn’t just individuals with verified COVID-19 who showed T-cell immunity but also many of their exposed asymptomatic family members,” said one of the researchers. “Moreover, roughly 30% of the blood donors who’d given blood in May 2020 had COVID-19-specific T-cells, a figure that’s much higher than previous antibody tests have shown.”

In the German study, researchers analyzed blood samples of 365 people, of which 180 had had COVID-19 and 185 had not. When they exposed the blood samples to the COVID-19 coronavirus, they found, as expected, that blood from those who had had the illness produced a substantial immune response.

More significantly, they found that 81% of the subjects who had never had COVID-19 also produced a T-cell immune reaction. This would suggest that earlier common cold coronavirus infections might provide about eight in 10 people some degree of immune protection from the COVID-19 virus.

These were not huge studies. They have to be tested again. But if they prove out, it would be very good news.


Is the current strain of the virus less virulent than the older ones? 

I haven’t found the answer to this question yet.

I have read about several studies that suggest it might be true – that the strain of coronavirus that currently affects about 70% of those that are infected is less virulent than the strain that killed so many people in March and April. But I haven’t yet found those studies, so I’m going to have to report on this again when I do.

For now, I can say this: The people to whom I gave the virus and I have had minimum to moderate symptoms. That’s too small a sample to draw conclusions from, but it’s enough for some hope.


 This essay and others are available for syndication.
Contact Us [LINK] for more information. 

Continue Reading

proliferate (verb) 

To proliferate (pruh-LIH-fuh-rate) is to multiply; to increase or spread rapidly and excessively. As I used it today: “Viruses don’t extinguish themselves. They proliferate until their basic reproductive rate (R0) drops below 1.”

Continue Reading

Once you’ve been infected with the coronavirus, it spreads through your body via cell-to cell transmission. This is how it works:

The coronavirus contains ribonucleic acid (RNA) surrounded by a protective layer, which has spike proteins on the outer surface that can latch on to certain human cells. Once inside the cells, the viral RNA starts to replicate and also turn on the production of proteins, both of which allow the virus to infect more cells and spread, especially to the lungs.

Continue Reading

If you are really into the math behind the COVID-19 models, you’ll love this guy (Stanford University’s Michael Levitt). I can’t get enough of him and yet I understand very little of what he’s saying.

I ran Part 1 of this talk a few weeks ago. This is Part 2. Here, Levitt discusses two commonly used growth curves, the Sigmoid Function and the Gompertz Function.

Continue Reading