As I have said countless times before, social media is a horrible source for information. Someone can post a lie, and people who are too lazy to investigate issues for themselves will simply share that lie. Pretty soon, lots of people have been fooled. This is especially true when it comes to the COVID-19 pandemic. Consider, for example, the image on the left. It claims that with just two weeks left in 2020, the total number of deaths in the United States was lower than the total number of deaths in 2019. This, of course, is meant to support the conspiracy theory that the COVID-19 pandemic isn’t real. The problem, of course, is that the post is simply false, and anyone who spends even a short amount of time investigating it will see that.
Back in September, I posted a graph that was widely available on the internet. I checked it with the data that were known at the time and found it to be accurate. Even back then, we knew that 2020 was lining up to be the deadliest year in history. In July, several news outlets (like this one) ran a story on a medical study that showed deaths in the U.S. had spiked by 18%. In October, more stories (like this one) reported that there were 300,000 excess deaths in 2020 compared to the same time frame in 2019. In late December, several stories (like this one) reported that 2020 was on track to be the deadliest year in U.S. history.
If you don’t believe these reports, you can check the data for yourself. I downloaded the file yesterday, and it indicated that there were 3,128,646 deaths in the U.S. from 1/1/2020 to the week ending 12/19/2020 (the last week available at that time). In 2019, the total death count was 2,852,610. Now please note that these numbers are still not final; they will both increase. The 2020 numbers will increase more with the final weeks being included and with new information coming in from very rural areas. Nevertheless, it is quite clear that 2020 was significantly more deadly than 2019. In fact, in terms of total numbers, it is the deadliest year on record. Even when you look at the increase in deaths between 2019 and 2020 as a percentage of the population, you find that it is second only to what happened between 1917 and 1918, when deaths as a percentage of the population rose by 46% because of World War I and the Spanish influenza pandemic.
There are many reasons to distrust the government. Indeed, there are many things that I think the government is lying about. In each case, however, I have come to that conclusion because I think the data demonstrate that the government is promoting falsehoods. In the case of the COVID-19 pandemic, however, the data are clear and easily found by anyone willing to invest even a modicum of effort investigating the issue. It is real, and it turned 2020 into the deadliest year in U.S. history.
Not long ago, I wrote a post about the COVID-19 vaccine produced by Pfizer. At that time, I only had access to the results of the small clinical trial, but those results were very encouraging. Now, the initial results of the large clinical trial are available, and they are even more encouraging. In short, the vaccine is 95% effective at preventing symptomatic cases of COVID-19 in the group that was being tested. While there were side effects, they were generally mild. Of course, not all kinds of people were tested. People under 16 years of age were not included in the clinical trial. Neither were pregnant women nor those who are immunocompromised. Thus, the results don’t apply to people in those groups.
Like most clinical trials used for licensure of a medication, this was a large-scale, placebo-controlled, double-blind study. That means a large number of people (43,538) were randomly assigned to receive either two doses of a placebo (an injection of saltwater) or two doses of the vaccine. The doses were separated by 21 days. Neither the people getting the injections nor the researchers directly involved in the study were aware of which injection each person got (that’s what “double blind” means). Once there were enough COVID-19 cases among all the participants to make a reasonable conclusion about the results, the researchers learned which injection each participant got. At that point, they could compare the two groups.
When they made the comparison, they found that starting seven days after the second dose, there were only 8 cases of COVID-19 in the group that got the vaccine doses, while there were 162 among those who got the saltwater injections. Thus, the vaccine clearly provides strong protection against COVID-19, at least among people like those who were in the study. Now please understand that people in the study were only tested for COVID-19 if they exhibited symptoms, so this says nothing about whether or not the vaccine protects against asymptomatic COVID-19 infections.
Of course, the small clinical trials had already shown that the vaccine would be effective at preventing symptomatic cases of COVID-19. This large-scale trial was done to confirm that result and, more importantly, to determine whether or not the vaccine is safe for the majority of people. While it is impossible to know for sure, all indications are that for people over 16 who are not pregnant and not immunocompromised, the vaccine is safe. The vast majority of vaccine recipients reported pain at the injection site, compared to only a small percentage of those who got the placebo. Small percentages of those who got the vaccine also reported redness and swelling at the injection site.
The most commonly-reported side effect after pain at the injection site was fatigue. In people aged 16-55, for example, 59% of those receiving the vaccine reported fatigue after the second dose, compared with 23% of those who got the placebo. The percentages were slightly lower for those over 55. Headache was the next most common side effect, followed by muscle pain, chills, joint pain, fever, diarrhea, and vomiting. Figure 2 from the study gives a good summary. There were a total of four people who had severe reactions to the vaccine. Those reactions were a shoulder injury related to administration of the vaccine, severely swollen lymph nodes, an abnormal heart rhythm, and unexplained severe sensations in the leg. There were two vaccine recipients who died, but there were four placebo recipients who died. None of the deaths were judged to be related to the clinical trial.
Based on these results, I plan to get the vaccine as soon as I am allowed to. My wife is in a high-risk group, and she will as well. My adult daughter and her husband have a business that requires extensive travel throughout the U.S. They will also be getting it. Whether or not you or your family get this vaccine (or one of the others that will no doubt become available over time) is up to you. Medical decisions are deeply personal and should be made in consultation with a physician who knows your medical history. I would never presume to tell anyone how to make such decisions. I simply wanted to communicate to my readers what I think the data say about this vaccine.
I will add one more thing. One of my readers said that she heard the COVID-19 vaccine can make women unable to have babies, because the vaccine is training the body’s immune system to fight a protein that is similar to syncytin-1, a protein important to the formation of a placenta. Thus, it is possible that a woman who gets pregnant after getting the vaccine will be unable to form a placenta. While it is true that the proteins are similar, their similarity is in their function, not their actual structure. Both proteins facilitate connection to a membrane, but they do so in very different ways. As a result, their structures are quite different, and a protein’s structure is what the immune system attacks. Thus, there is no reason to expect that the vaccine will cause the immune system to attack syncytin-1.
In addition, women who contract the actual disease would have the same problem, since the immune system attacks the same protein whether it comes from the instructions given by the vaccine or the virus itself. I don’t know of any reports indicating that women who contracted COVID-19 are unable to form a placenta. Finally, while pregnant women were excluded from the trial, 23 got pregnant during the trial. Twelve of them were in the group that got the vaccine. They are being followed, and as of the December 4th National Vaccine Advisory Committee meeting, no adverse effects have been found.
My previous post discussed two studies that seem to indicate masks have little effect when it comes to stopping the spread of COVID-19. I had several Facebook commenters who disagreed with my interpretation of the studies, which is not surprising. One commenter linked a recent study promoted by the CDC, which makes the remarkable conclusion that in Kansas, counties that adopted a mask mandate saw a 6% decrease in new cases, while those that did not adopt the mandate saw a 100% increase. If true, that indicates masks have a strong effect when it comes to stopping the spread of COVID-19. After reading the study and doing my own analysis of the numbers, I have to say that unfortunately, it is not true.
Once again, let me preface this by saying that I am not anti-mask. I wear a mask whenever I am in public, and I did so even before my state made it mandatory. In addition, I am not telling people to stop wearing masks. As I said in my first post, any mask not made specifically for viruses will be pretty much worthless in protecting the wearer. However, a mask does reduce the number of water droplets that the wearer spews into the air, and since those droplets can contain viruses, it probably does protect the people around the wearer, albeit to a small extent. Thus, you should wear a mask. At the same time, however, you need to have a realistic idea of what kind of protection it provides. So far, the data say it offers only a little protection.
With that out of the way, let’s look at the study. It examined various counties in Kansas that adopted a mask mandate on July 3, 2020 and compared them to the other counties that did not adopt a mask mandate. It developed a seven-day rolling average of new COVID-19 cases for both sets of counties and compared the numbers before July 3 and After July 3. The graph (shown near the bottom of the study) shows that while the 7-day rolling average continued to climb for those counties that did not adopt a mask mandate, it fell a bit for those counties that did. Thus, the mask mandate actually reduced COVID-19 cases, while lack of a mandate resulted in a steady increase in cases.
In the midst of this pandemic, most governments are requiring people to wear mask in public. I will start this by saying that I began wearing a mask early on in the pandemic, long before any mandates were made. I didn’t wear one because I thought it would be effective. Even a basic understanding of science tells us that standard masks provide little protection against the spread of a virus. Protecting yourself against a virus using a mask that is not made specifically for viruses is roughly equivalent to protecting your yard against mosquitoes by installing a chain-link fence.
However, a mask does reduce how many water droplets you spew into the air, and since those droplets can carry viruses, there is probably some small protective effect for those with whom you come into contact. I wore a mask early on simply to put others at ease. Now I wear one because I think people must follow a society’s rules (unless they are immoral) in order to be a functional member of that society. If the mandates were lifted, however, I would still wear a mask in public until the pandemic dies out, simply because some people think it protects them, and I want to put such people at ease.
My publisher sent me a recent study that tries to address the question a bit more effectively than the study linked above. It didn’t test masks directly, because it would be impractical to follow people around making sure they were wearing their masks. However, the study gave 3,030 people a set of recommendations for protecting themselves against COVID-19. They included things like social distancing, etc., as well as the recommendation to wear a mask, 50 surgical masks, and instructions on how to use them. The study also gave 2,994 people the same set of recommenstions, minus the mask recommendation, the masks, and their instructions. After 1 month, they tested people for COVID-19 antiboides. This was all during a time when their communites did not issue any mask recommendations or mandates.
The results showed that slighly fewer people in the mask group contracted COVID-19 than those in the no-mask group. However, because the number of people who contracted COVID-19 during the study was small, the difference between the groups could have been the result of random chance. In the end, the authors use basic statistics to conclude that the mask group was somewhere between 46% less likely to get the disease and 23% more likely to get the disease. As they say:
The recommendation to wear surgical masks to supplement other public health measures did not reduce the SARS-CoV-2 infection rate among wearers by more than 50% in a community with modest infection rates, some degree of social distancing, and uncommon general mask use. The data were compatible with lesser degrees of self-protection.
Now, of course, we have no idea what percentage of the people in the mask group actually followed the recommendation, but the study made it pretty easy to do so. Combined with the study I linked at the beginning of the post, I think we can conclusively say that if the typically-used masks provide protection against COVID-19, it is small. Thus, when “experts” say nonsense like this:
If we could get everybody to wear a mask right now, I really think in the next four, six, eight weeks, we could bring this epidemic under control.
We know they are not using science to inform their opinion.
There has been a lot of talk about Pfizer’s COVID-19 vaccine, and a reader asked me to comment on it. The company claims it is more than 90% effective at preventing the disease, which is better than what most health-care experts were expecting. If true, that news is exciting enough. To add to the excitement, it is a new kind of vaccine that has great potential, if it works the way it is supposed to. There is another company trying to produce a similar vaccine, but it looks like Pfizer is in the lead, so for the purpose of this article, I will focus on its version.
Let me start by saying that I have no connection to Pfizer or any other pharmaceutical company. I am a science educator who writes about science issues like this one. I am also not a medical doctor or medical researcher. I am simply a nuclear chemist who has broadened my knowledge base by writing (or co-writing) a series of textbooks used by home educators and teachers in Christian schools. Thus, I am no expert on these matters. However, I get most of my information by reading the scientific literature, which allows me to avoid a lot of the misinformation found in the standard media outlets and (even worse) social media.
Before I talk about Pfizer’s vaccine in particular, I want to explain how this kind of vaccine works. To understand that, remember that a traditional vaccine uses a weakened/inactivated form of the pathogen whose infection it wants to prevent (or a chemical mimic of that pathogen). This causes your body to react as if it is being infected by the real thing. As a result, it mounts a defense that is specific to that pathogen and remembers how to fight it. That way, if you get infected by the real thing, it can mount a swift immune response. This process takes advantage of your acquired immune system. However, you also have an innate immune system, and the active ingredient of the vaccine does not stimulate it. As a result, traditional vaccines have additives, called adjuvants, which are designed to stimulate your innate immune system. That way, everything in your immune system works the way it is designed to work.
I have referenced this article in some comments I made previously, but I want to highlight it in a separate post, because the graph it contains (also shown above) makes it clear that the COVID-19 deaths are not some manipulation of the data. They are real. Very real. The purple bars in the graph represent all deaths recorded in the U.S. each week since 2017. The yellow line represents a projection of the maximum number of deaths that should have happened each week. The projection is based on historical data, and it fluctuates with the season. That’s because there are usually more deaths in the winter and fewer deaths in the summer, and as you can see, the actual deaths show that same fluctuation.
Notice that for most weeks, the actual deaths were lower than the maximum number of projected deaths. That’s expected. If the projection is done well, there should rarely be a time when the actual number of deaths meets or exceeds the maximum projection. However, there were some weeks in December of 2017 and January of 2018 when that happened, because there was a particularly virulent strain of the flu that season. As a result, more people died than were expected.
But those excess deaths are dwarfed by the ones that start showing up the last week of March in 2020. In that week, about 4,000 more than the maximum projected deaths occurred. Since then, the actual deaths have exceeded the maximum projected deaths by a considerable margin every week. All of this is discussed in the article from which I took the graph. However, I want to make a couple of additional points.
First, look at the shape of the excess deaths. There appear to be two peaks – one very large one the second week of April, and a smaller one at the end of July. This is important, because it looks very, very similar to the COVID-19 deaths reported over the same time span:
When the excess deaths have essentially the same time profile as the COVID-19 deaths, you know that the COVID-19 deaths make up most of the excess deaths. This tells us that the vast majority of COVID-19 deaths are real and most certainly represent people who would not have died had there not been the COVID-19 pandemic.
Second, some friends have asked me why they don’t know anyone who got the disease or died from it. After all, if there really have been more than 180,000 people who died from the disease and more than 6 million confirmed cases, shouldn’t everyone know someone who has suffered from it? Of course not! There are 328.2 million people who live in the U.S. That means about 2% of the population has contracted COVID-19, and about 0.05% have died from it. Thus, your chance of knowing someone who died from it is ridiculously low. While your chance of knowing someone who contracted it but didn’t die from it is significantly higher, remember that for most cases, the disease is mild. Thus, you would have to know someone well enough that you track his or her common illnesses to be aware that he or she had the disease!
It disturbs me that there are so many people (many of whom are Christians) who think this pandemic has been made up. The data clearly say that it hasn’t been. Lots of people died because of the disease, and misinformation will only increase the number of deaths. Now please understand that I am not saying that I support any of the measures that governments have taken to slow the spread. We don’t know enough about the disease or the consequences of the actions that have been taken to know whether or not they are a good idea. I said this before, and I will say it again:
As a scientist, let me assure you that no one really knows what we should be doing. There are a lot of experts saying a lot of different things, and you should listen to all of them. Then, you should decide what works best for you and your family, and you should start doing it. But once you decide what you and your family should be doing, please please please show grace to those who choose to do something different. Since the experts can’t agree on a proper course of action, there is no reason to expect your neighbor to agree with your course of action.
In addition to showing grace to others, please please please stop spreading the false idea that the COVID-19 deaths are few in number or not real at all. They are real, and there are a huge number of them. There is simply no other way to understand the data.
On Saturday, I received the image on the left from a well-meaning individual. She wanted me to see that we have been fooled regarding the severity of the virus that causes COVID-19. By Sunday, this image (or one like it) was all over my Facebook feed. Please understand that the statement starts out as completely false and then uses true statements to imply something else that is completely false. Unfortunately, it tends to resonate with people who do not understand medical science and who have not been personally affected by the pandemic. As I watched this lie literally spread around the world, I couldn’t help but think of Jonathan Swift’s famous statement1
Falsehood flies, and the Truth comes limping after it.
Here is my attempt to get the truth to come limping after this falsehood.
More importantly, this image is meant to imply that COVID-19 is not dangerous because the vast majority of people who die from it have some other illness. Once again, that is simply 100% false. If you look at the underlying conditions that are included in the 94% (table 3 in the link above), you find things like high blood pressure (hypertensive diseases), diabetes, obesity, etc. The image tries to categorize them as “serious illnesses,” and depending on the person, they might be. However, they are present in a large percentage of the population. 45 percent of adults in the U.S. have a hypertensive disease, 10 percent of the U.S. population have diabetes, and 42 percent have obesity. Thus, a huge number of people in the U.S. have at least one of the “serious illnesses” that make you likely to die from COVID-19. In other words, there are many, many people at risk of death from COVID-19.
But how can we say that these people died of COVID-19 when they had some other condition? Because most of these conditions are completely treatable and will not generally kill a person. However, when that person gets an infection, the underlying condition makes it harder for his or her body to fight off the infection, leading to death. The more serious the infection, the more likely the person is to die. In fact, the majority of people who die of an infection like influenza, pneumonia, tuberculosis, etc. have an underlying condition that makes it more difficult for them to fight off the infection. Thus, it is not even remotely unusual that 94% of people who die from COVID-19 had one or more underlying conditions. It is common for many serious infectious diseases, especially in the developed world.
There is one more issue in the image above that I must address. It says that the overwhelming majority of people who died from COVID-19 were of advanced age. That’s true, but it’s true for all deaths in the developed world, not just COVID-19 deaths. Indeed, a recent study compared the ages of people who died from COVID-19 to those who died from all causes. Guess what? They were quite similar:
In fact, the age distribution of deaths attributed to COVID-19 is quite similar to that of all-cause mortality, which tends to increase by about 10% every year of age after age 30 y.
We don’t know a lot about COVID-19, and there is no way to scientifically state the best cause of action against the disease at this time. However, we do know that it is a very serious disease, and it is being downplayed by some using falsehoods like the image above. Please stop the misinformation! If you want to share something about COVID-19, at least make sure it doesn’t communicate something blatantly false, like the image above does.
ADDENDUM (added 9/4/2020): Someone on a friend’s Facebook feed wrote an incredibly insightful comment that I must share. She said that if you really think that the only COVID-19 deaths are the ones that had COVID-19 as the sole cause, then you must think that AIDS has a mortality rate of zero!
1. The Examiner, Number 15 November 2 to November 9, 1710, (Article by Jonathan Swift), Page 2, Column 1, Printed for John Morphew, near Stationers-Hall, London. Return to Text
In a previous post, I compared COVID-19 cases and deaths in Sweden and Denmark. As I said then, it’s because they are very similar countries in the same basic region of the world, but they have remarkably different responses to the disease. Sweden has avoided lockdowns and tried to target their social restrictions, while Denmark has followed the practices of most other countries, strongly limiting what their citizens can do during the pandemic. While no comparison of two different countries is conclusive, I think the results are very interesting. The data come from the European Centre for Disease Prevention and Control, and while it may very well be a biased source of data, at least it is equally biased for both countries.
The graph on the left shows the cumulative COVID-19 cases per million. That means each day on the graph shows the total cases that were reported by that date, divided by the population in millions. Initially, Denmark had more cases (probably because initially they were testing more), but as you can see, Sweden quickly surpassed Denmark in cases per million, and the difference between the two countries has continued to grow. Since the death rate of COVID-19 is low (but higher than most infectious respiratory diseases), many people (including myself) think that death rate is a better indicator of the severity of the pandemic. Thus, the graph on the right shows the cumulative deaths per million. Notice that Sweden has more than 5 times the deaths per million as Denmark.
If the comparison between these two countries is legitimate, then, government restrictions did reduce the number of COVID-19 deaths per million in Denmark. However, there are those who suggest that this might be okay, since Sweden will reach herd immunity faster than Denmark. In the long term, then, Sweden will have fewer COVID-19 deaths because the spread of the disease will stop sooner.
Based on my evaluation of the data, I don’t think Sweden is significantly closer to herd immunity than Denmark. Take a look at the graph below, which records cases per day per million. Rather than adding all the cases reported by a given date (as is done in the graph on the left above), this shows the daily reports of COVID-19 cases per million.
If Sweden were closer to herd immunity than Denmark, the recent cases per million per day in Sweden should be lower than the cases per million per day in Denmark. However, they are not. For most of August, Sweden and Denmark have roughly equivalent cases per million per day. That tells me the disease is spreading roughly the same in the two countries right now, but Sweden has lost five times the people (per capita) as Denmark. As a result, my analysis indicates that Denmark’s restrictions kept a lot of people from dying of COVID-19, and that will continue to be the case in the long run.
Yesterday, President Trump held a press conference to announce a new possible treatment: convalescent plasma. Based on an analysis of several different studies, it seems to be the best candidate yet (in my non-medical-doctor opinion). I say this because of the kinds of studies that have been done. First, there have been three randomized clinical trials. This means patients were assigned to either get the treatment or not get the treatment based on random chance. The group that got the treatment was compared to the group that didn’t (called the control group). In the three studies, the death rate in the treatment group was half that of the control group. There were also five matched-control studies, where the treated patients were compared to a control group specifically selected to closely match them. The results of those studies were similar to those of the randomized clinical trials. There were also four case-series studies, where patients were given the treatment and their progress was tracked. While that kind of study has practical uses for physicians, its ability to determine the effectiveness of a treatment is extremely limited. However, the case-series studies seem to support the other two kinds of studies. All of the studies were done on patients with severe or life-threatening cases of COVID-19.
Taken all together, then, the treatment looks very promising. However, I do have to say that each study was very small, so even when all the patients were analyzed, the total number was only 804. Phase three clinical trials that determine whether or not a drug should be widely used typically involve a few thousand patients. Thus, this is still a limited data set. Also, many of the studies (as well as the analysis linked above) are not peer-reviewed. As a result, there could be major flaws that have not been noticed. A recent analysis (once again not peer reviewed) of more than 35,000 patients seems to support the small studies, but since it has no control group, it cannot be used to draw any real conclusions. Nevertheless, the FDA has approved emergency use of the treatment, and it is asking those who have recovered from the disease to help in determining whether or not it is truly effective.
How can someone who has recovered from COVID-19 help determine the effectiveness of the treatment? To understand that, you need to learn a bit about the wonderful mixture that is running through your circulatory system.
First found in alpacas, nanobodies are like antibodies, but they are smaller, simpler molecules. Because of that, they are easy to make and manipulate. Essentially, scientists can build a small gene that produces the nanobody, insert it into certain microorganisms, and let the microorganisms churn out the nanobodies. As a result, there have been many, many different kinds of nanobodies produced over the years. The researchers searched a database that contained more than two billion nanobody genes, and they found 21 that should be able to bind to the virus’s spike proteins in some way. They put those genes into yeast, extracted the nanobodies that were produced, and studied them.
Based on their analysis, they found the three most promising candidates and tested them against the virus itself. One of the nanobodies was particularly effective, so they focused on it. They mutated the gene multiple times to make slight changes to the nanobody and tested the result against the virus. They then produced a gene that could take the three most effective nanobodies and chain them together. The result was a chemical that basically shut down the virus’s ability to infect human cells.