I don’t think it’s an understatement to call COVID-19 the defining “trend” of 2020. When COVID-19 began rapidly spreading through the United States, my home country, my college had to close the campus and move all of the students out. At this point, you have likely had your fill of the virus and the resultant restrictions.
As we close 2020, I want to review, from the perspective of an American non-expert trying my best to understand the experts, where we are in this pandemic.1
Coronaviruses, named after the crown-like spikes on their surfaces, are RNA viruses that affect mammals, including humans, and birds. They cause respiratory infections and cold-/flu-like symptoms. The coronavirus that has brought “regular” life to a standstill and drastically changed the course of 2020 is officially called SARS-CoV-2 and regularly referred to as COVID-19. The first report of COVID-19 came from Wuhan City, Hubei Province, China, in December 2019.
The origins of the disease – that is, how it evolved and how it was transmitted universally – are contested, and several potential origin stories have been proposed, but scientists are still uncertain. A common hypothesis is that it crossed to humans from bats through an intermediate species, as Dr. Lingfa Wang discovered was the case with SARS, though this should not encourage a demonization of bats.
At the end of 2020, the World Health Organization invited ten top researchers, among them the epidemiologist who tied MERS to camel and the veterinarian who linked the 2014 West Africa Ebola outbreak to rooting bats, to further investigate the origins of COVID-19, ruling out no propositions. This includes the theory that it emerged from a lab, whether as a Chinese bioweapon or from the accidental lab release of a natural virus from the Wuhan Institute of Technology, a hub of bat coronavirus research and BSL-4 laboratory. The Los Angeles Times provides a summary of and links to the research done up to May 2020 on the genetic evidence that COVID-19 was not lab-engineered, but good science demands that nothing be discounted.
Means of spread & mask science
Regardless of its origins, how it passes from human to human now is well-known: Droplets or particles produced when an infected person “coughs, sneezes, sings, talks, or breathes” can be inhaled by another person, who may be consequently infected. Another scenario is surface contact with the virus, though the risk is lower. Given that the former is the method believed to more commonly transmit the disease, governments around the world have encouraged the use of personal protective equipment, or PPE, particularly masks. A series of studies have demonstrated the effectiveness of masks for the reduction of community transmission via source control.
In April 2020, a New Jersey driver crashed his SUV into a pole that, according to the police report, may have been caused by “insufficient oxygen intake/excessive carbon dioxide intake” after “excessive wearing” of a N95 mask. This event prompted fears that wearing face masks for extended periods of time could inflict carbon dioxide poisoning, or hypercapnia, on the wearer.
In reality, only an airtight mask could definitely achieve that, and airtight masks are not in general use; moreover, even N95 respirators, which has a very close facial fit and are reserved for front-line workers, pose little danger except for those with lung diseases, in which case carbon dioxide levels may rise after prolonged mask use. (To this point, this article is worth considering and cross-checking.)
That carbon dioxide can pass through a mask but COVID-19 cannot is due to the difference in size between carbon dioxide molecular sizes and COVID-19 virus and aerosol particle sizes: A COVID-19 particle is 100-125 nanometer in diameter, while a carbon dioxide molecule is 0.25-0.33 nanometers in diameter. Meanwhile, the most secure N95 masks filter only down to 300 nanometers, so molecules as small as carbon dioxide would “make it through.” Unlike carbon dioxide, the COVID-19 virus cannot float freely; it attaches to aerosol droplets, which range from 1,000 to 10,000 nanometers.2 Therefore, these droplets stay within one’s mask and possible COVID-19 virus particles stay in the mask while carbon dioxide molecules slip out. Similar reasoning follows for oxygen molecules, whose diameter is 0.12 nanometers or so.
For more information on this transmission via droplets and aerosols, Jayaweera, Perera, Gunawardana & Manatunge provide a thorough review of the literature, current as of September 2020. They recognize that the science is ongoing and that our current understanding may shift as researchers discover more about this unique coronavirus.
For some individuals, severe breathing problems prevent them from wearing a mask, and the CDC makes accommodations for them and for children under 2 years. For most, the sensation of breathing difficulty, and consequent assumed oxygen level compromise, is a product of unfamiliarity. Dr. Christopher Ewing, lung specialist in Alberta, Canada, explains, “Most of us aren’t used to wearing face masks, and the sensation of having a mask on your face might make someone anxious or uncomfortable. Although much of our breathing is unconscious and driven by our respiratory center, it can also be influenced by the mind. When we’re feeling discomfort, even subconsciously, it can change the way we breathe.”
The most commonly cited statistics in the news are the case count and the death count. Given differing population sizes, a gross number comparison between countries does not accurately reflect the COVID-19 condition in the United States. For example, as of December 9, 2020 (the date I began writing this post), the U.K. had 1.75 million cases and 62,000 deaths while the U.S. has had 15.2 million cases and 286,000 deaths. The numbers alone suggest that the United States is doing drastically worse than the U.K., but the larger numbers “make sense” given that the United States’ population is almost five times that of the United Kingdom.
The above graph, drawn from data from the European Centre for Disease and Control, indicates that per 100,000 people, France, the U.K., and Spain were performing worse than the U.S. in October. Interestingly, the U.K. responded to the impending pandemic with the same (non-)urgency as the U.S. Spain has exhibited an even slower response. For Canada and Germany, who suppressed spread in the spring and summer through quick, strict action, complacency and/or COVID-19 fatigue are fueling the post-summer second wave.
The next graph displays the number of confirmed COVID-19 deaths per million people in five countries from March 2020 to December 2020. Note the difference in scale: deaths per million with a rolling 7-day average. In the United States, death statistics are based primarily on the death certificates that the National Center for Health Statistics receives from the 50 states and the District of Columbia, though in April the CDC recommended also using probable and confirmed case classifications. As state-by-state methods of counting COVID-19 deaths vary, including with regards to timing of data submission, comparison across states may be inaccurate. The following, regularly page records per million deaths across the 193 member states of the United Nations, with the Holy See and the State of Palestine excluded: COVID-19 deaths worldwide.
There is a difference between someone dying from COVID-19 and someone dying with COVID-19, and this is reflected in death certificate evaluations. The CDC’s provisional death count, which relies solely on death certificates, was 291,757 as of December 23, 2020. This death count includes all deaths that involved COVID-19 in some way. In 6% of deaths, COVID-19 was the only cause listed on the death certificate. As may be imagined, denied latched onto this number to demonstrate how overblown the whole she-bang is. However, considering that the population at risk often has underlying conditions, that COVID-19 is not the sole factor isn’t surprising.
The National Center for Health Statistics explained to Reuters that “death certificates, filled out by a physician, medical examiner, or coroner, list any causes or conditions that contributed to the person’s death, determined based on the medical expertise of that professional”, and that the instigating condition that led to death is considered the “underlying cause of death.” An average of 2.9 additional conditions, such as the flu, respiratory failure, diabetes, and obesity, accompanied deaths involving COVID-19, but COVID-19 was still deemed to be the underlying cause in 92% of deaths. Dr. Maja Artandi furthermore notes that the numbers reflect how COVID-19 “can cause severe damage to the organs in the body such as the lungs, which then leads to respiratory failure and death.”
Focusing back on the United States cases, not deaths: President Trump has attributed higher cases in the United States to higher testing. One Facebook post argued, “There’s a ‘spike’ in Corona cases because there’s a spike in testing. If we gave more IQ tests there’d be a spike in morons, too.” Certainly, more testing would discover more positive cases, but this simplification ignores the positivity rate, another data point that the CDC has used to track the progression of COVID-19 in the United States. The positivity rate is the “percentage of positive virus tests among all virus tests performed.” If the virus is not spreading, the positivity rate should stay constant, provided that adequate testing is being administered.
According to the testing trends data from Johns Hopkins, constancy has not been the case for the United States. The graph below was retrieved on December 9, 2020 at 2:30 pm. It shows the positivity rate since the spring for the entire United States. The highest point is a 21.8% positivity rate between April and May. One can further interact with this graph here.
Though useful, the positivity rate, as currently assessed, is flawed: Lloyd has pointed out that the nonrandom, voluntary testing in the United States does not allow for the random sampling that would yield a more accurate picture of COVID-19 cases and spread. An additional challenge is that states calculate the rate differently, some dividing total number of tests by the number of positive tests and others dividing total number of tests by the number of people testing positive.
Like case count and death count, the positivity rate is not a fool-proof barometer for community health and COVID-19 containment success. It is best used to assess a community than to compare communities. Even within a community, though, researchers consider several statistics at once to yield a more accurate view of the situations. For example, South Dakota reported 448 new infections on December 1. This number, seemingly low, points to “a runaway outbreak and insufficient testing” when combined with their 42.5% positivity rate.
Boston University epidemiologist Matthew Fox emphasizes evaluation in context. A constant number of administered tests over two or three weeks accompanied by increases in positivity rate, for instance, would indicate increased transmission more than increased testing shortage.
As indicated above, per 100,000 people the United States has suffered “fewer” cases than countries like France and the United Kingdom. Looking at individual states, we can consider the impact of restrictions like mandatory masks and limited congregation on cases and fatality.
The graph above is from a research team at WalletHub. They compared 50 states and D.C. to identify the states with the fewest restrictions. They used a 100-point scale and 17 metrics, including requirement to wear a mask in public, large gathering restrictions, restaurant and bar reopening, non-essential business reopening, and “shelter in place” order strictness. The report was published in October 2020. The red bubbles are states with few restrictions and high death rates; the grey, high restrictions and high death rates; the green, few restrictions and low death rates; and the blue, high restrictions and low death rate. In these groups, there are 18 states, 8 states, 7 states, and 18 states, respectively. The restriction and death rankings can be interacted with on the WalletHub page. South Dakota, whose Governor Kristi Noem has never imposed lockdown measures or mandatory mask-wearing, had the highest score at 83.93.
The maps below from the CDC, retrieved, on December 9, 2020, scale the COVID-19 case rate and death rate across states. One can compare these maps with the WalletHub data to guess at the efficiency of restrictions to stymie the spread and mortality of COVID-19 in the 50 states and D.C. (One should proceed with caution when comparing, of course, given the different case and death recording practices between some states mentioned before.) These reports and graphs do not take the economic and mental impact of COVID-19 into account, though the WalletHub study does have an Unemployment Ranking vs Restrictions Ranking chart that briefly considers the former aspect.
The New Year
As 2020 turns into 2021, COVID-19 will follow the globe. How it will play out in this new year is uncertain, dependent on how communities maintain or relax restrictions, the release of the vaccines that companies like Pfizer and Moderna have developed, and the additional findings of the biologists, epidemiologists, and other scientists.
If you have suggestions or corrections for this essay, please do not hesitate to comment or to contact me privately. I am by no means an expert on medicine, epidemiology, or science and general, and am happy to learn from others.
Stay safe. Stay well. May you find some rest in 2021.