Is the Covid-19 Virus as Damaging/Virulent as We Have Been Led to Believe?

Many of you have seen that Stanford University in California came out with some dramatic new numbers this past weekend. In my opinion, they are important. Are they the final word? Likely not. But they are the first of a certain type of information that will help us understand better what might be going on.

Let’s review the study as I understand it and the meaning it has for each of us.

First, let’s look at why the study is important. We need to have a bit of an understanding of what these reported numbers are all about. (And for those who have forgotten their math lessons from many years ago, when we write, for instance, 100/1000, this means 100 divided by 1000 which would = 0.10. This will be helpful in the very elementary math we use below.)

Lessons from a Make Believe (Hypothetical) Community

Using very round numbers in a hypothetical population, suppose we have tested 1000 people as being positive for the Covid-19 virus. Let’s also suppose we believe that probably only those 1000 people have been infected by the Coronavirus.

In this situation, if 200 people became sick and had notable symptoms then we would assume 20% of the people who have been infected get symptoms. (200 sick/1000 presumed to be infected = 0.20 which is 20%) Some would have mild symptoms and some would become quite ill. Here 20% of the infected get sick or show symptoms. The other 80% have no symptoms and feel fine.

Continuing with this scenario, let’s say 100 of these people have to be hospitalized. We would then say that 10% of the exposed people were hospitalized. (100 hospitalized/1000 presumed infected = 0.10 which = 10%)

If 10 people in this group died, then 1% of the those exposed in the future could be expected to die based upon these numbers. (10 deaths/1000 infected = 0.01 which is 1%)

To summarize the percentages of our hypothesized population:

1000 people is the presumed infected population.

200 sick would show that 20% of the infected are presumed to get sick from the virus.

100 people hospitalized would be 10%.

And if 10 people died, there would be a 1% death rate.

But what if in our hypothetical world, we decide that we should test a lot more people to get a better feel of really how many people out there had been infected by the virus? We’d take our test kits out through the community and test a lot of people.

With our new testing we now have found that there are in fact 10,000 people who show that they have antibodies to the Covid-19 virus - a whole lot more than we have previously thought. Antibodies are what the body forms to protect itself against many different things. You can measure antibodies against peanuts, or bee venom, or grass. So it’s not a big stretch to test for antibodies to Covid-19 viruses and find out if your body has had to deal with them.

So we find that there are in fact 10,000 people with positive Covid-19 antibodies whereas we used to think that there were only 1000. Therefore we have to calculate again what percentage of people infected by the Covid-19 virus had to go to the hospital and what percentage died.

The number who got sick in this scenario, in this community, was 200. We now know that out of 10,000 people who got the virus, only 200 got sick. (We use the same 200 getting sick as the top number and the new information that there are 10,000 infected as the bottom number. 200 sick/10,000 infected = 0.02 which = 2%) This amounts to only 2%, not 20% like we originally thought. Very good news. In this scenario, a far lower percentage got sick and thus we know that the virus is not nearly as serious as we had when we thought that 20% got sick.

In this hypothetical community, 100 people had needed hospitalization. We have learned 10,000 people had gotten the Coronavirus and thus only 1% would have needed hospitalization, not 10%. (100 sick/10,000 infected =  0.01 which = 1%) Again, some very good news.

And the best news would be that since we know that 10,000 people got the virus and only 10 died, the actual percentage dying from infection by the Covid-19 virus would be 0.10% which would be very close to the actual percentage of people that die from the annual flu. (10 deaths/10,000 infected = 0.001 which = 0.10%) Some years there are more deaths from flu, and some years the numbers are a tad better. But it would then be considered to be very similar to the flu. And thus it would not be nearly as big a deal as we originally thought it was.

With the new understanding that a lot more people had been infected than we previously knew, the numbers, in summary, look more like this:

10,000 is now the population that has been infected.

200 sick would show that 2% of the infected get sick from the virus.

100 people hospitalized would be 1%.

And if 10 people died, there would be a 0.1% death rate. And to be clear, this is 1 death in 1000.

This is why we need to have a far better understanding of how many people in the community have been infected. We originally in this hypothetical example had thought that 1% of infected people die which would be far worse, approximately 10 times, than the flu. Now we would feel far less threatened since it is a roughly equivalent percentage of deaths as the annual flu.

The Stanford Study Results are Similar to the Numbers in Our Hypothetical Community

The researchers at Stanford were unimpressed with the numbers showing Covid-19 as being a far more severe problem than the flu. They didn’t believe that the evidence supported the conclusion. They recognized the need to have a more accurate bottom number in the equations (denominator). When we use a bottom number of 1000 infected vs 10,000 infected in our hypothetical community, it makes a huge difference.

The Stanford study attempted to get a much more realistic number regarding how many people had been infected. They knew how many people had gotten sick, and how many people had to be hospitalized, and they had some idea of how many had died from Covid. But they didn’t really know how many people in the surrounding communities had been infected.

In our example above, the imaginary study team found that the actual number of people infected with the Coronavirus was ten times greater than they had previously thought.

In the Stanford study, they found that the number of people infected was potentially 50-85 times as many as they had previously been led to believe.

Prior to the study, Santa Clara county had 1094 confirmed cases of Covid-19. And in that many people, there had been 50 deaths. That would mean that the death rate was 4.57%. (50 deaths/1094 infected = 0.0457 which = 4.57%) That is a pretty high death rate! And numbers like that could be quite scary. 

The Stanford study showed there were many more who had been infected but most of them showed no symptoms. I’m reading 50 to 85 times more people infected than what they had previously thought. For my calculations let’s pick 70 times as it’s kind of in the middle of the range.

1094 cases x 70 = 76,580 infected people (not the previously assumed 1094).

76,580 relative to 50 deaths means that the percentage dying from becoming infected is only about 0.07% (not 4.57%). (The number of deaths is the same. 50 deaths/76,580 presumed to be infected = 0.0006529 which = 0.06529%) That’s a huge difference. And a very encouraging difference.

Is Covid-19 as Serious as We Have Thought?

So that leads us to wonder if the Covid-19 Pandemic is really as severe an issue as we have been led to believe.

I have just listened to two interviews with Dr Jay Bhattacharya, one of the Stanford researchers. He confirms that based on their work, the death rate from the disease is “orders of magnitude” lower than what was expected. In his opinion, the threat of Covid-19 virus is far less of an issue than what he used to think.

His group has two more similar studies coming out within days or weeks. One is being done in Los Angeles and another study is being done with the general staff of Major League Baseball. The MLB study is not being done with only the professional players. It’s being done with office people and the people who work in the stadiums such as servers, janitors, etc.

There are still many who claim that this pandemic is huge and may still wreak havoc well into the future. Thus they argue for more shutdowns of the country. One example published on April 21, 2020 is from the National Review and is available online. The article is entitled “Coronavirus Kills More Americans in One Month Than the Flu Kills in One Year”.

The author certainly has his points. Covid-19 is likely a serious disease. However, I would disagree with some of his statistics and conclusions. My point is that things are not yet clear cut. And caution is advised.

But what do I mean by caution? Please go back to previous posts on our website and read about the various thing that you can do to build up your immune system so that you can effectively fight the the coronavirus (and any other virus, for that matter) and be far less likely to get sick and or die.

In summary, if the Stanford study is close to being correct, Covid-19 is not nearly as big a deal as we had thought. We need more groups around the country doing similar studies to support or disprove the claims of this study.

But I think more studies of this sort will support the conclusions from the Stanford study.

And I don’t think that you have to be too worried about it - especially if you are doing the various things that we have been recommending.

If you are older and have significant health issues, it might be good to follow the recommendations by the government. But I’m not convinced that shutting down businesses across the country is necessary for the health of the general population especially if they were to take basic immune boosting steps. As we’ve outlined before, very little sugar, and take vitamin D, vitamin C, and vitamin A as starters.

Be prepared and be ready to take actions suggested in previous posts. And if you are having a tough time, we can help.