The Power of Context: How Numbers Can Explain Science
If more people understood the numbers behind the COVID-19 vaccine side effects, normalcy would arrive faster.
Commentary, covid-19, normalcy, smallpox, Spanish Flu, scarlet fever, pneumonia, statistical analysis of disease
Some people are hesitant to get the COVID-19 vaccine because they distrust the vaccines, their effectiveness, and their side effects, or they lack concern about the virus. These individuals do not understand science. The creation and approval of the COVID-19 vaccine took less than a year and it may contribute to concerns about safety, however, its development was not rushed because scientists have used this technology for the past 20 years.
Vaccines have revolutionized medicine and improved human well-being. In England during the period of 1600 – 1800, one-fifth of London’s population died in plague outbreaks, half of the victims were children under 15. Many who survived smallpox, influenza, scarlet fever, and pneumonia were left blind, deaf, or malformed. Europeans carried these diseases when they conquered the Americas and an estimated 80-90% of the native people perished. Ancient Chinese pulverized smallpox scabs from the sick to inoculate the healthy, and in 1796 British doctor Edward Jenner developed the first modern vaccine using cowpox blisters to inoculate humans. Vaccines continued to be developed, improved and administered successfully so that by the year 2000 smallpox, polio, and measles have been almost eliminated. Denying the efficacy of vaccines is like denying the existence of gravity or the holocaust.
The COVID-19 Johnson and Johnson (J&J) vaccine was suspended by the CDC and FDA because blood clots developed in some recipients. Eighteen deaths were associated with the J&J vaccine. This is a true statement but fails to reveal measurement context. The events occurred at a rate of 7 per one million women vaccine recipients between the ages of 18 to 49. In other groups it was rarer. Such context quickly allows us to compare this detrimental effect with the overall COVID-19 death rate per million. If more than 7 per million die from vaccine-preventable COVID-19, then the vaccine causes less damage than the disease.
Numbers matter, but only in perspective. Keeping track of scale takes constant practice, but it is the fastest way to discover misleading or erroneous claims. Counting change used to be constant arithmetic practice, and physical cash, or even a check, established a sense of scale that is absent in a card swipe. For example, 9/11 is particularly poignant, and it will always be remembered that 3,000 people died that day. Subsequently, we can scale disasters in “9/11” units by dividing death tolls by 3,000. Each disaster is scaled to something meaningful to someone, and an objective sense can gain ascendancy over yet another emotional outrage. Last summer, the daily death toll due to COVID-19 in the US was 2,000 or 2/3 of a “9/11” unit.
Units are equally important and come in two broad categories. Extrinsic units such as grams, liters, and time, establish scale with respect to an agreed reference point. Intrinsic units such as velocity (distance per time) and percent (count per 100 events) establish the context of the measurement. Extrinsic terms can often be made more emotional and sell more copy. For example, unemployment at 10 million; COVID-19 killing millions. Such “facts”, while perhaps being technically true, defy comparisons with other sources because their context has been ignored, minimized, or obscured to work an emotional, political, or sales angle. Intrinsic statements are better. Unemployed persons were at 9.7 million in 2020, continued to trend down in March 2021, but is 4.0 million higher than in February 2020; 2,491 COVID-19 related deaths with 183,830 confirmed and presumptive COVID-19 cases in Oregon. Such statements are much drier, and difficult to remember, but they give the scale a context that allows for more than the emotional connection the media spurs with arithmetic gymnastics.
Numerical evaluation takes practice, but it can clarify our options when we need to choose. I personally still trust the CDC to do these cost-benefit analyses for me, including the recent relaxing of guidelines on use of masks. But if you must tune in to everyone’s viewpoint, arm yourself by watching your units, paying attention to scaling, and performing fun mental arithmetic crosschecks. Compare your calculations with friends, and if you come to different results, don’t despair, just work out who did the better job of observing and calculating by comparing your approaches. Scientists have been arriving at different results from similar observations for years. They just keep trying to figure out who observed and calculated more effectively to be useful.
About the Author:
Chrissa Kioussi, Ph.D. is a Professor of Pharmaceutical Sciences at Oregon State University and a Public Voices Fellow with The OpEd Project.