There’s more to science than random facts and ancient languages(1). It's one part invention, one part discovery, and all parts awesome. The most important discovery has been that nature is predictable. It contains logical patterns that we can describe with laws(2). The invention was all of the techniques and technologies now used to investigate nature and describe how it works(3). Taken as a whole, these techniques form the scientific method.
Science is a process of building models about how the world might work, and then testing them to see if they accurately describe that world. In this article, we will learn the ways that scientists, and really anybody, build these models. Then, we’ll get to see how those same principles relate to the ongoing sars coronavirus covid 2 (SARS-COV-2) pandemic and the coronavirus disease (COVID-19) that it causes(4).
Scientists gather information on past experience by reading peer-reviewed journals in their area of study and going to conferences to talk with other researchers working at different labs. In this way, the scientific method is meant to incorporate diverse perspectives into the knowledge it produces. Peer-reviewed journals publish the objective data recorded by researchers so that others can learn about it, or reproduce it. It's Like showing your work in algebra. From that background research, a scientist can make educated guesses about how things might play out in the real world, a hypothesis. This, in a nutshell, is inductive logic, and it's the logical backbone of most science. It's also something that pretty much everyone does naturally. If you’ve ever taken a test at school and got a particularly bad grade due to not studying, you might induce that if you study before the next one, you’ll do better. You can then test that hypothesis on your next exam.
When used skillfully and ethically, science is one of the best tools humans have invented to see the natural world as it really is. Without it, we experience reality filtered through our habit of favouring some information over others; our biases. Seeing the world in a biased way is not good if you actually want to know what is happening around you. During covid times(5), it's more important than ever to understand how science works. To build that understanding, we’ll need to dissect the scientific method like a frog in an early nineties high-school biology lab. Since we’re on the topic of animals, let's take a look at some furry and scaly friends from around the animal kingdom. Like humans, these creatures have also been affected by the pandemic.
As with a lot of other pandemics, SARS-COV-2 started out in animal populations before mutating enough to infect humans. These kinds of diseases are called zoonotic infections(6). A pandemic, by the way, is simply an infectious disease that spreads to most of the world. They actually occur pretty often, but usually aren’t infectious or deadly enough to warrant the kind of response that SARS-COV-2 has.
There are many different kinds of evidence, but when doing science, it's that which comes from objective measurements that is most important. The objective evidence showing that the first humans infected with COVID-19 were infected by bats came from analyzing the virus’s genetic programming, called RNA(7). They found that the virus infecting humans had 96% of the same RNA as a Coronavirus known to circulate in bats. Previous Coronavirus outbreaks also got their start by jumping from bats in the same area as the first COVID-19 outbreaks.
Just like COVID-19 jumped from an animal - likely a horseshoe bat - into a human, earlier versions of the virus jumped around between animals. Sparrows, hedgehogs, wild cats, and one particularly interesting mammal have all been shown to be potential intermediate hosts before the bats that first infected humans(8). So let’s zoom in now to these animals’ habitat in southern China.
There, in the grass, something is moving. An intrepid field biologist gets a little closer and sees...A reptile? Walking on its back legs? It's covered in greyish scales, has a head and tongue like an anteater, and a long, wide, armoured tail. It's actually a mammal. Its Latin name is “manis pentadactyla(9)”, but its common name is the Chinese Pangolin. The word comes from the Malay language and means “roller”. When frightened, pangolins curl up into a ball to protect their vulnerable parts with their tough scales. After possibly chasing the scaled ball around the woods for a while, the biologist subdues the pangolin (sorry, my dude), draws some blood, or else collects scat or urine, (sorry, my biologist dude) and sends it off to a lab. If this pangolin is infected, there will be viral cells in the fluids that were collected.
Viral cells, unlike bacterial, or pangolin cells, get their instructions from a chain of proteins called ribonucleic acid (RNA). At the lab, a technician puts the infected pangolin’s bodily fluids into a machine that can objectively measure the changes in the RNA. Then the technician uploads the measurements into a database called the Global Initiative to Share all Influenza Data (GISAID) that scientists from all over the world have been using in the fight against COVID-19.
In the spring of 2020, researchers like Maria Vasilarou from Greece started working with scientists in China (among many other countries) to learn how COVID-19 entered the human population. As great as these tools are, they don’t completely remove biases from science done based on their data. On GISAID’s website, at the bottom of the page on variants, authors are quick to point out that, “Observed frequencies are subject to sampling and reporting biases and do not represent exact prevalence”(10).
One of the things Maria’s team learned about the virus was that much of the data published early on in the pandemic about COVID-19’s genome suffered from sampling bias(11), which led scientists to have an incomplete picture of which animals hosted the virus before it jumped to humans. The sampling bias came from the fact that the first cases of COVID-19 for the most part traced their genetic roots to a bat origin, but the truth is a little more complicated. Plenty of bats at the Wuhan Wet Seafood Market turned out to have the same virus infecting humans in the area at the time, but that doesn’t necessarily mean that bats were the only non-human animal to play a key role in the evolution of the virus.
One of the labs that measured COVID-19 RNA was at Cambridge University in the United Kingdom. In a laboratory outfitted with very cool robotic arms for manipulating viral cultures(12), molecular biologists like Lalitha Sundaram prepared the test plates used in COVID-19 polymerase chain reaction (PCR) tests, which are generally used for determining whether a person has the virus. The sample is then put in a PCR machine, and a chemical reaction makes copies of the virus, if there is a virus in the sample. There are other methods of testing, but the PCR is generally considered the best(13). It's a pretty good objective measurement, but the data gained from PCR tests only go so far; they only tell us if our sample has viral cells in it, but not much else. If we want to learn more about COVID-19’s evolutionary past, and possible future, we’ll have to look elsewhere for that evidence.
Over in Greece, Maria and her team used a technique called the Basic Local Alignment Search Tool (BLAST) on samples whose genome had been entered into GISAID. Rather than just knowing whether or not a sample(14) contains the virus, BLAST compares the genome of two samples to each other, and determines their similarity(15).
When a hypothesis has been tested and shown to be true enough times, it forms a general theory. Some general theories you might know are Germ Theory(16), or the Theory of Relativity. In the case of the COVID-19 pandemic, we see a kind of natural experiment that is evidence in favour of the germ theory of disease. If it turned out that most of the people who got sick didn’t have the virus, that would have been evidence in favour of the null hypothesis. Like those other theories, our model for the origin of COVID-19 has also changed as we’ve collected more evidence. Over time, scientists came to realize that more animals were involved in COVID-19’s evolution than previously known. They didn’t know about this at the beginning of the pandemic because of sampling bias. This early evidence came from only one kind of animal, and in one place, mostly around Wuhan.
Because COVID-19 belongs to a larger family of viruses called Coronaviruses, epidemiologists had some decent background knowledge about this one. They knew that this species of virus circulated widely in bat populations, and that those same bats are often sold for food at markets in cities like Wuhan. Early genome sequencing of the virus found in humans and bats showed a 96% similarity, which is excellent evidence in favour of a bat-origin theory.
Since lots of people have been studying Coronaviruses and publishing the results of their experiments for years, Maria and her team created the hypothesis that it mutated in other animals before infecting bats, and finally humans. To test this, they analyzed the RNA of the virus that had been found in people. Then, they compared the genome of COVID-19 to that of animals living near the site of the first outbreak. Their results indicated that COVID-19 most likely came from bats, but before it infected bats, there was a recombination event, or mutation, in another animal(17).
Since Maria and company had access to copies of the virus from all over the world(18), and across a greater period of time than earlier research, their analysis did not suffer from the same degree of sampling bias that some of the earlier work did. Eventually, a viral strain that started in our scaly rolling pal found its way to the United Kingdom, where our human friend, Lalitha, prepared COVID-19 test plates for PCR tests. Molecular biologists at that lab then used techniques like BLAST, and determined that one of the strains of COVID-19 in human populations in the UK traced its origins to the keratin19 armoured sphere of might, the pangolin. The name scientists settled on for this variant is much less poetic; H.1.1.7, usually called the UK-Variant20, according to its entry in GISAID.
When a patient goes to their doctor with a sore throat and other cold-like symptoms, that is one kind of evidence. The problem for a doctor, who is a kind of scientist, is that what they’ve heard from their patient is subjective. Doctors take patient reports of symptoms seriously, but they need something more objective in order to provide science based treatment. Taken with epidemiological evidence, like nearby COVID-19 outbreaks, a Doctor uses inductive logic to conclude that their patient is infected. They’ll need to test their hypothesis with a more objective line of evidence to increase their level of certainty about that. So they order a PCR test. A medical professional sticks a gigantic q-tip up the patient's nose and gets some mucuous on the tip, and puts it in a plastic tube. That sample then goes off to a lab where someone trained in molecular biology or a similar field, like Lalitha, performs the reaction. If the test is positive, then the Doctor’s hypothesis appears to be true. If it were negative, they would have to modify their hypothesis, and do tests for other causes of their patient’s illness.
We've seen a few examples of science in action, of our first assumptions mutating as models are updated. COVID-19 infected bats before humans and becoming a pandemic. Later, when more evidence was collected, we saw how a larger, more randomly selected, less biased sample of data improved our understanding of the intermediary hosts of COVID-19, and the (19,
20) "hCov19 Variants - GISAID." https://www.gisaid.org/hcov19-variants/. Accessed 28 Feb. 2021.
third was an example of how doctors use the scientific method in diagnosing the virus. Investigators in all three examples gathered information, generated hypotheses, and thought of real world ways to test their ideas, which was an exercise in inductive logic. They recorded objective measurements like nasal swabs and computerized records of RNA sequences to either prove or disprove their hypotheses. Maria Vasilaru and their colleagues were able to control for sampling biases and more accurately determined which animals hosted Covid-19 before humans, like the armored, termite eating pangolin. Hopefully, after taking this cyberspace tour of SARS-COV-2 genomics, we’ve all learned the mechanics of how the scientific method has lead to our current understanding. More importantly though, we should now be able to see how inductive logic, and the basic logic of the scientific method, are immediately accessible and easily used by anybody. Whether it's studying for a test, baking a cake, or ending a pandemic, the scientific method has us covered, like the scales of a pangolin.