Jay L. Wile's Blog, page 9

A Cool Gravity Demonstration

Dr. Scott Carr does a demonstration that shows gravity accelerates all object at the same rate. From time to time, I teach classes at Anderson University. While I usually teach science for science majors, over the past few years, I have been co-teaching a class with Dr. Scott Carr called “Teaching STEM in the Elementary Classroom.” It is designed to give elementary education majors the tools they need to incorporate science, technology, engineering, and math lessons in their K-6 classrooms.

I started teaching it just because I enjoy working with Dr. Carr, but I have continued teaching it because the class is really fun. A good portion of the class time is spent having students come up with experiments that their students could either do or watch. Of course, I have seen all sorts of science experiments for elementary students, and my elementary series actually contains a total of 450 of them. Nevertheless, every year I see at least one new experiment or a new variation on an experiment I already know. This year is no exception. We have only been in class for two weeks, and already, a student named Melodie Nord presented a great experiment that shows gravity accelerates all objects at the same rate. A slow-motion video of it is given below:

As you can see in the video, water is falling out of a hole near the bottom of the cup in a stream. However, once the cup is released, the water stops falling out of the hole. It is still falling, of course, but the cup is falling with it. Since the cup and its entire contents fall at the same rate as the water that would have come out of the hole, the cup “keeps up” with the stream that was coming out of the hole. As a result, there is no stream of water. This shows that whether it is a tiny drop of water or a cup full of water, gravity accelerates everything at the same rate, regardless of mass.

I have a plaque on my wall that says “Doscendo Discimus,” which is a Latin proverb that means, “By teaching, we learn.” It is true whether I am teaching nuclear physics at the graduate level or STEM for elementary education majors!

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Sweden’s COVID-19 Strategy Didn’t Work

A comparison of Sweden and Denmark in terms of COVID-19 (click for higher resolution)
I have written two posts comparing the COVID-19 situation in Sweden and Denmark (see here and here). I find the comparison useful, because they are very similar countries in the same basic region of the world, but they had remarkably different responses to the disease. Sweden initially avoided lockdowns and tried to target their social restrictions, while Denmark followed the practices of most other countries, strongly limiting what their citizens could do during the pandemic. Sweden thought that if they allowed the disease to run its course among those who are not at high risk, they would achieve herd immunity, and the disease would lose its impact. As a result, they tried to target their severe restrictions to those who were at high risk, allowing the rest of the population to live life more normally.

By fall, there were those who thought the strategy had worked. Case rates were falling, and Sweden seemed to have weathered the storm. However, in my August post, I said that Sweden had not reached herd immunity, and it turns out that I was right. If you look at the above graphs (data from the European Centre for Disease Prevention and Control), you will see that while both Sweden and Denmark saw a leveling off in the summer and early fall, COVID cases and deaths quickly shot up later on. To date, Sweden’s COVID-19 deaths per million are more than three times that of Denmark’s, and right now, there is no indication that either country will see a slowdown in cases or deaths, at least not until the vaccines are widely distributed.

Now please understand that comparing two different countries is fraught with peril, and even though Sweden and Denmark are similar in many ways, we cannot use these data to definitively say that government-imposed lockdowns are responsible for the difference. Indeed, there is a fairly recent study that tries to compare different countries, and they conclude that while some social restrictions did reduce the spread of the disease, severe restrictions (like lockdowns) didn’t help at all. Interestingly enough, they use Sweden as part of their baseline for countries that didn’t implement severe restrictions, but they do not use data from Denmark in any way. I personally think their analysis uses countries that are just too different to be compared in any meaningful way.

To show you what I mean, I added the U.S. and Italy to the graphs above to show you where they fit.

Notice that while the general shape of Italy’s death graph is similar to that of Sweden and Denmark, the U.S. deaths look very different. Conversely, when it comes to cases, the U.S. graph has the general shape of Sweden and Denmark, while Italy is different. Finally, notice that the total number of deaths per million varies by nearly a factor of five, despite the fact that three of the four countries on the graph had strict limitations on what many of their citizens could do.

I think there is one firm conclusion we can make from the data presented above: Sweden’s strategy of trying to control the disease using herd immunity acquired through exposure did not work.

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Despite What You May Have Heard, 2020 was the Deadliest Year On Record

This is an example of one of the many false things you will read on social media. 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 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.

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“Climate Change” Is Not Killing Pacific Northwest Coho Salmon

It has become so fashionable to blame every calamity on “climate change” that scientists are overlooking REAL environmental issues, like tire waste. (click for credit)

Nowadays, if you want to get funding and become popular in the scientific community, you need to blame any natural calamity you are studying on climate change (aka global warming). For example, salmon populations in the west have been on the decline, and predictably, global warming has been trumpeted as the cause. As one source suggests:

Pacific salmon that spawn in Western streams and rivers have been struggling for decades to survive water diversions, dams and logging. Now, global warming is pushing four important populations in California, Oregon and Idaho toward extinction, federal scientists warn in a new study.

Of course, when serious scientists actually looked at the situation, they found that temperature is not responsible at all, at least not specifically for coho salmon. The scientists investigated multiple possibilities, and they ruled out rising temperatures. As one of the authors stated:

We had determined it couldn’t be explained by high temperatures, low dissolved oxygen or any known contaminant, such as high zinc levels…

Like good scientists, then, they ruled out the “fashionable” explanation and decided to find the real cause. Not surprisingly, they did. They found that urban stormwater runoff could cause the same symptoms that were known to be killing the coho salmon, so the authors painstakingly analyzed the runoff and ran multiple tests.

They identified the chemical that was killing the coho salmon but could not figure out where it came from. Eventually, the researchers found that this chemical was similar to a preservative used in tires, which is charmingly known as “6PPD.” After several experiments, they found that when 6PPD is exposed to ozone and sunlight, it can be broken down into the killer chemical. Thus, the coho salmon are not being killed by today’s favorite boogeyman. Instead, they are being killed by a chemical produced as a result of tire waste.

Now, of course, since the authors of this study seem to be careful scientists (unlike so many that exist today), they are unwilling to generalize their results. Thus, this conclusion applies only to what is killing the coho salmon in the Pacific Northwest. There might be other causes for what is killing the other species, but I hope this motivates scientists to question the “fashionable” explanation of “global warming” and actually do some serious scientific investigation, like this team did. If so, real science might still be able to help us understand (and the hopefully fix) the problem.

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I Will Be Getting the COVID-19 Vaccine as Soon as I Can

Creative Commons License, click for source

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.

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Yes, The World Was Warmer Before “Global Warming”

An arrow that is roughly 800 years old. It was exposed by melting ice in Norway.

(image from study that is being discussed)

If you get all your information regarding climate change, aka “global warming,” from social media or most news outlets, you would think that we are living in a time of unprecedented warmth. However, if you read the scientific literature, you know that climate proxy data from around the world indicate that this is just not true. If you aren’t familiar with the term, “climate proxy” refers to data that scientists use to attempt to understand climate conditions of the past. Tree rings, for example, are sensitive to temperature and precipitation, so it is thought that we can use them to determine past climate conditions. Many climate-sensitive things like recorded harvests, coral growth, pollen grains, etc. can be used as climate proxies. Analysis of such climate proxies indicate that the earth was significantly warmer in the Middle Ages than it is today. Climate scientists refer to it as the “Medieval Warm Period,” the “Medieval Climate Anomaly,” or the “Medieval Climate Optimum.”

Those who are invested in promulgating terrifying stories about the effect people have on the earth’s climate attempt to downplay or disregard this well-established part of the earth’s history, but the data are quite convincing. The latest set of evidence to be added to the pile is an archaeological study from Norway. The first line of its abstract reads:

In the context of global warming, ice patches are increasingly important foci of high-elevation archaeology.

In other words, places like the area examined in the study have been covered in ice for a long time, but now, because of global warming, that ice is melting, revealing what has been entombed there.

What did the melted ice reveal? 68 arrows and five isolated arrow heads. This led the authors to describe the area as “…the most arrow-rich known ice patch site in the world.” They used carbon-14 dating to determine the age of the artifacts, and they say that their finds range from about 700 years old to 6,000 years old. The older the age, the less reliable carbon-14 becomes, so I doubt that any of those ages are really correct. However, we can certainly say that these arrows come from a time long before the Industrial Revolution!

Why do people make arrows? To hunt game. The authors conclude that this area, which has been covered in ice during recent times, was a rich hunting ground during several periods in the past. That means the area must have been much warmer in the past. Now, of course, we can’t make any conclusions about the earth’s climate from just one region. However, it is at a high elevation in the northern part of the globe (latitude 61 degrees). Such areas tend to stay cold, so the fact that it was warmer in the past is best understood in the context of a warmer earth. This adds weight to the proxy data, allowing us to more confidently conclude that there is nothing unusual about the temperatures the earth is experiencing right now.

Yes, the climate is changing. It is always changing. Yes, human activity probably has something to do with it, although the magnitude of that effect is unknown right now. However, the vast majority of the evidence indicates that what we are experiencing right now is not in any way unprecedented.

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Kansas Confirms Mask Mandates Don’t Do Much To Prevent the Spread of COVID-19

Comparison of COVID-19 cases in Kansas Counties that adopted a mask mandate on July 3 and those that did not. (click for higher resolution)

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.

When I initially read this study, I had to admit that I was very skeptical for a couple of reasons. First, if you look at the graph, there was a huge drop in cases in the mask-mandate counties just 4 days after the mandate was adopted. Given the fact that there is a delay between infection and positive test, it’s clear that at least that part of the drop had nothing to do with the mask mandate. Also, I was very surprised that the data stopped after just nine weeks. Because of the incubation period of the virus and the time it takes to do a test, any effect of a policy will take a long time to be realized. Nine weeks seems like a very short time. Thus, I decided to use the same source used by the study to take a direct look at the data. When I did that, I saw that the study’s conclusion is just an artifact of the way the analysis was conducted.

Rather than manipulating the data by taking rolling averages, I simply graphed the number of cases seen each day. Also, I am specifically interested in the difference between the populations after the mask mandate went into effect. Below, you see the results from the day after the mask mandate started (7/4/2020) to the day the study ended (8/23/2020). The graph entitled “Kansas Mask Mandate Counties” contains data from the mask-mandated counties that are listed in the study (second note under the graph). There were three counties (Cowley, Pottawatomie, and Riley) in which a mask mandate existed in a city but not the county as a whole. Those are not included either graph. The remaining counties are the ones that make up my “Kansas No Mask Mandate” counties.

Click for higher resolution

Notice that there is really little difference between the two. In general, COVID-19 cases bounce up and down, but they both stay rather constant throughout the entire length of the study. Statistically, there is a slight decrease in cases in the mask-mandate counties, but that is mostly because of the large spike at the beginning of the graph, which cannot have anything to do with the mask mandate. It is simply too soon after the mandate took effect.

Why does the study show such a marked difference between the counties? Mostly, it’s because of the fact that very little time is considered in the study. The number of infections were pretty small, and the data are spiky. As a result, there is a lot of statistical error in the analysis. You can see this by looking at the study’s 95% confidence intervals, as listed below the figure. The best the data can say is that after the mandate went into effect, the mask-mandate counties decreased by somewhere between 0.14 and 0.03 cases per 100,00 per day, while the no-mask-mandate counties increased by 0.01 to 0.21 cases per 100,000 per day. That means the statistical error is close to 100%! When your statistical error is that large, you really can’t make any definitive conclusions about what the data are saying.

There are two more reasonable ways to look at the data. First, we can look at the cumulative number of cases reported each day. That’s shown below:

Click for higher resolution

In this case, the time the study ends is given by the red line. Notice that in both sets of counties, the infections did not drop. They rose. Now, the rate at which they rose is different. The number of new infections per day is given by the slope of each graph. Notice that for the mask-mandate counties, the graph is a straight line during the course of the study. Thus, the infection rate did not drop. It stayed constant, as the slope of a straight line is constant. For the no-mask-mandate counties, the graph curves upwards slightly during the course of the study. Thus, the infection rate increased slightly in those counties during the course of the study. Notice, however, that since late October, both sets of counties are seeing an increase in infection rates, since both graphs are curved upwards.

So do these data indicate there is a difference between how COVID-19 spread through the counties over the time period of the study? Yes. It shows that the mask-mandated counties had a slightly slower spread of COVID-19 than the non-mask mandated counties. However, as is consistent with the data I discussed in my previous post, the effect is small. Once again, then, masks do seem to have an effect on slowing the spread of COVID-19, but that effect is small. Anyone who is counting on masks to significantly reduce the spread of the disease is not looking at the data.

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Mask Recommendations Make Little to No Difference

A surgical mask like the ones used in the study being discussed (click for credit)

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.

Having said that, there has been one study that concluded mask mandates reduced the rise of COVID-19 infections by a tiny amount. However, the study couldn’t conclude that the masks were the cause of the tiny decline. Most likely, when a mask mandate is instituted, people become naturally more cautious, limiting their social interactions, being more aware of social distancing, etc. Thus, it’s possible that the masks had nothing to do with the small reduction in COVID-19 cases.

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.

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A New Kind of Vaccine for COVID-19

Pfizer’s description of how an mRNA vaccine works (click for larger version)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.

This new kind of vaccine takes a different approach. Rather than injecting you with a weakened/inactive version of the pathogen (or a chemical mimic), it injects you with the instructions that your cells need in order to make a protein that is found on the pathogen. These instructions are coded in a molecule called messenger RNA (mRNA), which is the way a cell expects to receive such instructions. Some of the cells in your body will make the protein according to those instructions and “display” it, which will cause your immune system to think it is being attacked by a pathogen. This will stimulate your acquired immune system to respond. It will then remember that response so if you get attacked by the real thing, it is ready.

You can’t just inject mRNA into the bloodstream, however, as it will be removed rather quickly. Thus, the mRNA is enclosed in a fatty membrane called a “lipid nanoparticle.” The membrane and its mRNA can enter your body’s cells. Once that happens, cells recognize the mRNA as instructions for making a protein, and it is sent to a protein-making center called a “ribosome.” Interestingly enough, the membrane-enclosed RNA also stimulates the innate immune system, so this kind of vaccine needs no adjuvants, at least based on what has been seen so far.

But what happens after the mRNA is used at the ribosome? After a while, it decays away and is recycled by the cell. Why? The DNA in the nucleus of each cell contains instructions for making the proteins that the cell needs to make, but it never leaves the nucleus. As a result, the instructions are sent from the nucleus in the form of mRNA. Thus, there is a lot of mRNA in the cell, and all used mRNA decays and is recycled as a matter of course. This kind of vaccine just adds one more mRNA to the cell, and the cell treats it like it treats any other mRNA.

But wait a minute. If mRNA comes from DNA, is it possible that this mRNA can somehow interact with your DNA, fundamentally changing it? Not based on what we know about the cell. DNA is found in the cell’s nucleus, and mRNA cannot enter the nucleus; it can only leave the nucleus. Thus, there is no way this mRNA can affect your DNA. There is a class of viruses called “RNA retroviruses” that have the ability to take their RNA and convert it into DNA, which can then enter the nucleus. However, that virus has a special chemical (a reverse transcriptase enzyme) and other support chemicals to get that job done. With this kind of vaccine, there aren’t any chemicals like that, so as far as we know, there is no way for this mRNA to even come close to the cell’s DNA.

Why would you want a vaccine like this? Because it has several advantages over a traditional vaccine. First, there are no adjuvants. Every time you add another chemical to anything that goes in the body, you have increased the possibility of side effects. Fewer chemicals should mean fewer possible side effects. Second, since this is fully synthetic, it is relatively fast to produce. Thus, it is thought that this kind of virus can be made for situations just like this one, where the sudden introduction of a pathogen produces a new disease that is infectious. Third, the development of the vaccine doesn’t require the virus itself. All you need is the sequenced genome. Thus, there no chance of a virus-related accident during production.

Regarding Pfizer’s version of this vaccine, not much is known. The early clinical trial has been published, and its results are very encouraging. Only 45 volunteers were involved. 36 got the vaccine, and 9 got a placebo. Those who got the vaccine produced more antibodies than what is seen in patients who have recovered from COVID-19, indicating that the vaccine produces a more than adequate immune response. Almost all of the volunteers who got the vaccine reported pain at the injection site, and many reported headache, fatigue, and fever, which were dependent on the dose that was given. Only 2 of the 9 placebo-injected people reported such side effects. There were no severe side effects for anyone. A later clinical trial involved 195 participants and two versions of the vaccine. One version produced fewer side effects than the other, but the immune responses in the participants were similar to those in the first trial. Once again, then, very encouraging results.

Of course, both clinical trials had small test groups, which is why the current clinical trial (for the version that produced fewer side effects in the second trial) has 43,538 participants. Unfortunately, the data related to that trial are not available, since it is not over yet. However, based on the information I linked previously, that trial has reached a milestone: 94 patients have tested positive. This is important, because 94 infections among the participants is statistically significant enough to conclude whether or not the vaccine is protective against the virus. Based on what the company is saying, more than 90% of those cases must have been in the group that received the placebo, which means the vaccine provides strong protection against the disease. However, we don’t know that yet, since the data have not been released.

Nevertheless, Pfizer cannot get emergency authorization for this vaccine until the trial has been going for two months, because the side effects must be tracked for at least that long. Supposedly, that milestone will be reached by the third week of this month. The clinical study will continue until at least 164 of the participants have been infected so that a better estimate of the vaccine’s effectiveness can be determined. I am personally very excited about this vaccine (and other candidates like it), but until more data are published, I will withhold judgement. However, if the data from the current clinical trial are as good as the data from the early one, I will be eager to get an injection.

I will add one note of caution. This kind of vaccine has never been used before, except in clinical trials. Thus, nothing is known about its long-term effects, except what is predicted based on our current knowledge of cellular processes. Those who are more cautious about medical interventions should take that into account. Of course, I must also add that we don’t know what the long-term effects of COVID-19 infections are either, so one must weigh both unknowns when making any decision related to the disease.

I will keep my readers apprised of any new developments.

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This Study Says That More Carbon Dioxide Will Not Cause Much More Warming

Carbon dioxide absorbs the infrared radiation that the earth emits, trapping it before it leaves the planet. This warms up the atmosphere, making the earth a haven for life. Obviously, then, the more carbon dioxide we put into the atmosphere, the warmer it will get, right? Not necessarily! As I tell my high school and university students over and over again: Science isn’t simple! As a result, conclusions that seem “obvious” to most people (even most scientists) are often absurdly wrong. A recently-produced study that has not yet been published in the peer-reviewed literature makes this case about carbon dioxide and global warming, aka “climate change.”

The “obvious” conclusion that more carbon dioxide means more global warming ignores the fact that carbon dioxide doesn’t absorb all the infrared radiation it encounters. Instead, it only absorbs specific wavelengths. In addition, the amount of each wavelength that carbon dioxide can absorb varies with wavelength, the temperature at which the absorption happens, the concentration of the gases in the surroundings, etc., etc. Because of such effects, there comes a time when adding more carbon dioxide to the atmosphere has a negligible effect on the amount of infrared radiation absorbed. When that happens, you have reached saturation, and increasing the amount of carbon dioxide will not increase the atmosphere’s warming.

Now all of this is well known, and most global warming models attempt to include these effects in their calculations. The problem is that they treat them in a crude way. This is understandable, since a model that is trying to simulate the entire atmosphere has to consider a lot of things. As a result, most of them are treated crudely so that the model doesn’t become overwhelmingly convoluted. That’s where this unpublished study comes in. The authors test the effect of treating the science related to saturation crudely, and they say it renders the models pretty much useless when it comes to understanding how carbon dioxide affects the present atmosphere.

How do they come to this conclusion? They consider more than 300,000 different infrared wavelengths that carbon dioxide and other greenhouse gases (water, ozone, methane, and dinitrogen oxide) absorb. They compute how much the gases will warm the atmosphere by absorbing each wavelength. First, they make the computation without considering details like the temperature, the other gases in the atmosphere, etc. This is roughly equivalent to how current models treat the situation. Then, they do it considering all those details, using the present makeup of the atmosphere. They find that in the present atmosphere, the amount that more carbon dioxide can contribute to global warming is 10,000 times smaller than what current models assume. The same can be said for water vapor. For carbon dioxide and water vapor, then, the atmosphere is very, very close to saturation. As a result, more carbon dioxide and water vapor in the atmosphere will not warm the planet in any meaningful way. Ozone, dinitrogen oxide, and methane are also close to saturation, but not nearly as close as carbon dioxide and water vapor.

How do we know that their analysis is correct? We don’t. When they compare their calculations of how much infrared radiation is being absorbed for each wavelength to what satellites have been measuring, they see virtually no difference. Thus, their calculations seem to reflect reality very well. However, I am not very knowledgeable about the details, so there might be fatal flaws in their analysis that I am not seeing. Once again, science isn’t simple. I really hope this gets published in the peer-reviewed literature so that experts can weigh in on the conclusions. Unfortunately, I am not confident this paper will get that far. If its conclusions are correct, then there is absolutely no basis for the fear-mongering that surrounds carbon dioxide emissions. There are so many scientists whose careers have been made based on that fear-mongering, they may simply keep the paper from being published.

Fortunately, science is self-correcting. One way or another, we will figure out the details related to this issue. It might take longer than it should, and it might be after terrible decisions have been made based on faulty climate science, but at some point in the future, we will find out whether or not these authors are correct. I hope it is sooner rather than later!

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