By Dr. Fred Bass

A professor of medicine and clinical epidemiology has pointed us in the wrong direction regarding the COVID-19 pandemic. What can we learn from this?

On April 10, the Georgia Straight reported that Dr. John Ioannidis, of Stanford University, had called out the media for panicking the public over COVID-19 and warned against “sensationalism”.

He said: “We don’t want to get them into a panic.”

Ioannidis noted that his work focuses on the strengths and weaknesses of data. He found the information we have on COVID-19 to be “not reliable”. He identified “major gaps” in what we know:

“How lethal is the virus? / How many people has it infected? / How many will it infect? / What is the likely eventual impact? / How effective are different measures...?”

He questioned the World Health Organization's estimated case fatality rate of 3.4 percent and compared it to the 1 percent fatality rate on the Diamond Princess cruise ship. 

Ioannidis said that we should distinguish between those who die “by” [because of] the virus from those who die “with” the virus [had the virus but it wasn’t the cause of death], and that exaggerated estimates could lead to inappropriate decisions about our society.

Stanford University’s profile of Prof. Ioannidis is astonishing: a professor of medicine and epidemiology, as well as multiple, simultaneous appointments (currently, and over many years) to noteworthy academic institutions and to boards of leading journals.

His papers, “Why most published research findings are false” (2005) and “Why most clinical research is not useful” (2016), were both published in the online journal PLoS. 

The work of Ioannidis has focused on traditional errors made in clinical research, but not on the epidemiological fieldwork required to address a pandemic. 

On March 17, statnews.com published his article entitled “A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data”.

In minimizing the potential impact of the COVID-19 pandemic, Ioannidis made these errors: recommending delay to get data before acting on a rapidly growing threat; underestimating the seriousness of COVID-19; inappropriately comparing COVID-19 disease rates in two very different groups of people; and, in estimating how dangerous the virus is, ignoring information about who becomes infected and where they become infected.

What can we learn from Ioannidis’s errors? 

First, as Ioannidis recognizes, early in the pandemic of a new virus, reliable data is not available. Epidemics grow like forest fires, quickly and dangerously. Time is of the essence. 

In the absence of diagnostic tests, treatments or vaccines for the COVID-19 virus, the only tool we have is physical distancing. When dead bodies are piling up in the churches of Lombardy and in refrigerator trucks in the New York borough of Queens, distancing is immediately required! 

Second, a pandemic brings death and disease. It also brings doubt, distrust, disruption and despair. To counter this, authorities should be encouraging people.  

But, as the titles of his papers show, his style is to be contrary and iconoclastic. This approach may be valuable when confronting long-standing, inflexible research practices.  

However, in the crisis of a pandemic, this approach is likely to further spread doubt and distrust. 

Third, when answering his own question “how lethal is the virus?”, Ioannidis compares the WHO’s 3.4% case fatality rate (death rate of persons in the hospital) with a cruise ship’s 1% infection fatality rate (death rate among those who are infected).  

Since sick people go to hospitals and usually healthy people go to cruise ships, this is a biased comparison. If Ioannidis was trying to show that the WHO was exaggerating the pandemic’s risk, he instead only demonstrated a biased mistake.

Fourth, regarding Ioannidis’s question, “how lethal is the virus?”, the answer is not a stand-alone measurement, because investigating the deadliness of the virus can’t be separated from knowing who got sick and where they got sick.

Considering the COVID-19 virus, if the person is older and has heart disease and if the place where the person stays is crowded and cramped, the virus will be more lethal. If the person is young and healthy and lives alone in his/her own bedroom, the virus will be much less lethal. 

The virus does not exist in isolation.  

Everything is connected! Even after the best research, the words, images, and numbers that describe a virus are human creations. They are useful, but they are abstractions from real life and can be in error. 

The mathematician-philosopher Alfred North Whitehead used the phrase “the fallacy of misplaced concreteness” to describe the confusion of words, numbers, and symbols with reality.  

Today’s dead bodies have more weight than next month’s more reliable data that Ioannidis seeks.

Uncertainty is valuable; distrust is undermining

Scientific knowledge grows when the work of science is openly shared, scrutinized, discussed, argued, and revised. Uncertainty is a necessary part of the process.  

When the pandemic of a new virus begins, uncertainty is to be expected. With time, competence, and good research, answers unfold. 

So, initially, when a knowledgeable scientist or physician says, “I/we don’t know,” the statement is usually accurate and instructive. 

However, if ignorance, fear and anxiety overpower the community’s ability to handle uncertainty, then distrust will come out on top. Unfortunately, the manufacture of doubt is now a commercial enterprise, often engaged by large industries that make dangerous products, such as tobacco and fossil fuels. 

Manufactured doubt is cranked up by communication technology. The New York Times recently mapped the politically motivated Internet spread of a study of the level of COVID-19 immunity in Santa Clara, California. The flawed study claimed that the severity of COVID-19 was exaggerated. [Article not peer-reviewed; a “preprint article". Two sources of bias: recruiting via Facebook ads; the antibody test used has significant number of false positives.]

Dr. Ioannidis was a coauthor of this study.

Compassionate competence trumps distrust

In the face of the COVID-19 pandemic and the widespread distrust that’s also present, two competent, compassionate public health leaders have appeared: British Columbia's provincial health officer, Dr. Bonnie Henry, and Alaska’s chief medical health officer, Dr Anne Zink. They both offer inspiring and empathetic approaches compared to Prof. Ioannidis’s persistent doubts.

On May 1, the Georgia Straight noted:

Despite the growing number of deaths that have created so much heartache for B.C. families, the provincial public health officer, Dr. Bonnie Henry, remains a beloved figure across the province.  …

Henry’s mantra, “Be kind, be calm, and be safe,” is always delivered in her media briefings in a reassuring and maternal way, soothing British Columbians feeling anxious, upset, and disconnected by the pandemic.

She tugs at our communitarian heartstrings with her pleas to stay inside to protect the most vulnerable. And her command of the facts has astonished many reporters as she answers question after question after question without hesitation …

Blueprint Alaska, on May 11, wrote:

She’s [Dr. Anne Zink] quickly become a…calming, trusted presence at the governor’s nightly press conferences to update us on the state’s efforts to combat COVID-19. And she is good at explaining the facts—beyond good, she is nearly perfect, yet to miss a beat. Dubbed the “explainer in chief”. Dr. Zink is doing so many things right when it comes to crisis communications…She knows her stuff.  …Zink is empathetic and human.

…She is calm and composed under pressure. …She speaks plainly and avoids jargon.

…She expresses gratitude and recognizes her team.

In closing...

• Uncertainty works well when we don’t have answers, but it should not delay urgent action.
• Scientific uncertainty can be exploited to generate doubt and distrust.
• Competent and compassionate leadership helps communities deal with overwhelming situations.