Science, the Media & COVID Avoid the Popular Narrative; Think for Yourself
In the opening lecture of my first day in medical school at the University of California San Francisco in 1984 we were told the following
“50% of what you will learn in medical school over the next four years is false. The problem is we don’t know which 50%”
And this has played out in my medical career. Areas that have dramatically changed include:
• Change of HIV from an incurable disease to a chronic disease controlled by treatment
• Cure of Hepatitis C and Peptic Ulcer Disease with antibiotics
• Acknowledgment that Alzheimer’s can be prevented and delayed with appropriate lifestyle interventions
With COIVD-19, the changes in medical data has been dramatically accelerated with insights changing on a weekly basis. Multiple factors have been at play including that this was a new virus, that initial data from China was most likely incomplete and inaccurate, and that the entire scientific community has been working to solve this problem.
Changes in the case fatality rate are a good specific example with COVID. Most models were relying on initial data from China that was leading scientists to estimate that the case fatality rate could be as high as 1 to 5%. Since those estimates in February, our estimates of the case fatality rate has been reduced by a factor of 10 to 100-fold. In addition, it has also become clear that age is a major variable in who is at risk. The table below shows the CDC’s most likely estimates for the case fatality rate for people with COVID and symptoms as of May 30, 2020:
|Age||Case Fatality Rate||Survival Rate|
We could write a few “good news” headlines from this data
• “CDC says 99.95% of younger adults who get a COVID infection survive”
• “CDC case fatality rate estimates are reduced more than 10-fold from initial February estimates”
How many of those headlines have you seen?
Very few to none. And why not?
I believe one of the major reasons is because rapidly changing science data does not fit neatly into “overarching media narratives” that have become part of journalism in 2020. Journalists like to stick to a point of view and then organize all of their stories and information around that point of view.
If we are to really understand the truth with scientific data, we need to avoid the popular narratives and think for ourselves. An astute reader needs to understand the following:
• Initial scientific data is rarely clear-cut. In today’s day and age, media stories should always provide links to the data so that the reader can check the original sources themselves if they want.
• The “experts” are often wrong. It is easy for journalists to go to their “expert source” and present those viewpoints as the truth and start to build a “narrative.”
• Facts will change. The late economist John Maynard Keynes was known for saying: “When the facts change, I change my mind. What do you do sir?”
• Science advances only by proving hypotheses false. The philosopher Karl Popper proposed this view of science a century ago and it has held firm. A good example this is the pharmaceutical pipeline – for every 1 drug approved by the FDA there more than 6 failed candidates. However, each of those drug candidates had compelling data that warranted significant investment in the phase I clinical stage. It took research, time, and money to prove that the initial hypotheses were false.
One of the benefits of today’s internet is that it is possible to get multiple viewpoints and data so that readers can make up their own mind. A serious threat and danger to this is the emergence of social media “fact-checking or banning of alternative viewpoints.” For example, the CEO of YouTube has posted a policy stating that any viewpoints on COVID contrary to the WHO viewpoint will be banned. Which viewpoint? The one today or a few months ago? These efforts at censorship are inherently against the scientific method and should be condemned.
Dr. Craig Tanio