image of map of US displayed as multi-colored bar graph

“Causality” is a difficult concept, yet beliefs about causes are often consequential. A troubling illustration of this is the claim, which is being widely shared on social media, that the coronavirus is not particularly lethal, as only 6% of the 190,000+ deaths attributed to the virus are “caused” by the disease.

We tend to think of causes in too-simplistic terms

Of all of the biases and limitations of human reasoning, our tendency to simplify causes is arguably one of the most fundamental. Consider the hypothetical case of a plane crash in Somalia in 2018. We might accept as plausible causes things such as the pilot’s lack of experience (say it was her first solo flight), the (old) age of the plane, the (stormy) weather, and/or Somalia’s then-status as a failed state, with poor infrastructure and, perhaps, an inadequate air traffic control system.

For most if not all phenomena that unfold at a human scale, a multiplicity of “causes” can be identified. This includes, for example, social stories of love and friendship and political events such as wars and contested elections.1

Causation in medicine

Causal explanations in medicine are similarly complex. Indeed, the CDC explicitly notes that causes of death are medical opinions. These opinions are likely to include not only an immediate cause (“final disease or condition resulting in death”), but also an underlying cause (“disease or injury that initiated the events resulting in death”), as well as other significant conditions which are or are not judged to contribute to the underlying cause of death.

In any given case, the opinions expressed on the death certificate might be called into question. Even though these opinions are typically based on years of clinical experience and medical study, they are limited by medical uncertainty and, like all human judgments, human fallibility.

When should COVID count as a cause?

Although the validity of any individual diagnosis might be called into question, aggregate trends are less equivocal. Consider this graph from the CDC which identifies the number of actual deaths not attributed to COVID-19 (green), additional deaths which have been attributed to COVID-19 (blue), and the upper bound of the expected number of deaths based on historical data (orange trend line). Above the blue lines there are pluses to indicate weeks in which the total number (including COVID) exceeds the reported number by a statistically significant margin. This has been true for every week since March 28. In addition, there are pluses above the green lines indicating where the number of deaths excluding COVID was significantly greater than expected. This is true for each of the last eight weeks (ignoring correlated error, we would expect such a finding fewer than one in a million times by chance). This indicates that the number of deaths due to COVID in America has been underreported, not overreported.

Among the likely causes for these ‘non-COVID’ excess deaths, we can point, particularly early in the pandemic, to a lack of familiarity with and testing for the virus among medical professionals. As the pandemic unfolded, it is likely that additional deaths can be attributed, in part to indirect causal relationships such as people delaying needed visits to doctors and hospitals out of fear, and the social, psychological, and economic consequences that have accompanied COVID in America. Regardless, the bottom line is clear: without COVID-19, over two hundred thousand other Americans would still be alive today. The pandemic has illuminated, tragically, our interconnectedness and with it our
responsibilities to each other. One part of this responsibility is to deprive the virus of the
opportunity to spread by wearing masks and socially distancing. But this is not enough: we
need to stop the spread of misinformation as well.

 

1 Some argue that we can think of individual putative causes as “individually unnecessary” but as “jointly sufficient.” In the 2000 US Presidential Election, for example, consider the presence of Ralph Nader on the ballot, delays in counting the vote in some jurisdictions, the Monica Lewinsky scandal, and other phenomena such as the “butterfly ballot” in Palm Beach County, Florida. Each of these might have been unnecessary to lead the election to be called for GW Bush, but they were jointly sufficient to do so.

Kevin Lanning is a professor of psychology and data science at the Wilkes Honors College, a freestanding public liberal arts college within Florida Atlantic University. Lanning has written on the relationship between personality and natural language and the network structure of scholarly communities. He has been fortunate to be able to work safely from home during the pandemic. ---------------------------------------------------------------------------------------------------------------- Ashley Graham Kennedy, PhD holds degrees in astrophysics, humanities and philosophy, and is assistant professor of philosophy in the honors college and assistant professor of clinical biomedical science in the medical college of Florida Atlantic University. Her research focuses on diagnostic and clinical reasoning, and some of her recent work has appeared in British Medical Journal, Journal of Medicine and Philosophy, and Journal of Evaluation in Clinical Practice. Ashley also teaches philosophy of medicine, biomedical ethics and logic to pre-medical and medical students.