Fiction vs. Fact? How to Evaluate What you Read about COVID-19

Fiction vs. Fact? How to Evaluate What you Read about COVID-19

Are you overwhelmed by all of the different information you are getting about this pandemic, and not sure what to make of the data?  You are probably not alone.  In a crisis like this, the amount of misinformation rivals, if not exceeds, the useful information that you need.

To help with this question, I’m going to set aside my jewelry designer hat and put my philosophy hat back on.  My Ph.D. is in Analytic Philosophy, which extensively trains you in broad based research, and I taught critical reasoning classes for almost 18 years.  By sharing just a few simple tricks, I think I can do my bit to help empower you to get a better handle on what’s fiction and what’s fact. 

  1. It is understood that you are not an expert here.  Neither am I.  We are not doctors or statisticians and we don’t know how to computer-model population migration in a time of frequent international travel.  In addition, we may not know how to read and evaluate a study for its promise.  That is one reason why the information we receive will be based on indirect evidence.  We rely on testimony from other people who we don’t know we can trust.  These other people should be experts.  If they are, you can and should defer to them. 
  1. Experts in a field should have the relevant degree and/or experience.  This relevance should be as specific as possible.  A podiatrist is not an expert in influenza or other infectious disease.  A doctor can and will have a lot of relevant information, but ideally you want to look at information written by or in conjunction with an infectious disease specialist, or any relevant experience. Alternatively, you want the person quoted in the article to be referred to by name, so that you can do a quick check to see who that person is.   
  1. The information should come from a reputable source.  Facebook, for instance is not a reputable source because it does not have a fact checking process for what is published there.  If you get your news from Facebook, then track down its origin.  If no origin is mentioned, chuck it.
  1. The source should not be biased.  The individual or news outlet that publishes it should not have a personal interest in you believing what they say.  Bias is everywhere: politicians want you to vote for them, news channels want you to keep watching, drug companies want you to purchase what they advertise.  We have to accept that bias, but we can do what we can to diminish it, for instance by cross checking via triangulation.
  1. When you use triangulation you verify the data you have received by checking with another, independent source of this data.  The more independent verification you receive, the more you can hope that the news community, medical community etc. has reached something of a consensus. The more consensus there is among the relevant expert community, the better.
  1. What about eyewitness reports and personal experience related to us in a YouTube or other video?  Assuming that the eyewitness is telling the truth (I want to set lying aside here), such information is useful but also limited.  If a hospital worker tells you there are not enough masks where she is working, or that they are asked to ration, this may not mean that there are not enough masks available.  Perhaps the hospital is stockpiling because a hospital administrator is afraid the hospital will run out.  Or perhaps not, but the problem is you don’t know for sure. Again, it depends on who is talking, and in what capacity.
  2. Another problem with eyewitness testimony is that you cannot generalize from it.  What may be true in one hospital may not be true at another.  What is true in Louisiana may not be true in Texas. What is true about how one person reacts to the virus may not be true of another.
  1. If a study is referenced in the information you read, was the study conducted by a reliable source?  Is it a large-scale study or does it only consist of a small sample (i.e. a few dozen people)?  Is the sample randomized so that we can trust that it generalizes?  If you don’t know, just consider a few facts that illustrate that generalizing information is not very easy. In Italy there are a lot of people dying right now.  Does this mean a lot of people will die in Colombia (just to pick someplace other than here)?  Probably not.  Could be more, could be less.  The demographics of these two countries are different in a number of relevant ways.  Just some of those facts are average age, average health (i.e. are there a lot of smokers), the health care system itself, available supplies and doctors, government response, etc. 

As you can imagine, I have been doing a lot(!) of reading and watching TV over the past few weeks.  I’ve talked to doctor friends, I have looked at all news media including the German ZDT and the BBC, and yes, YouTube.   Not Facebook, I’m afraid.  Not a fan (for news anyway).

Here are a few things to read and watch that I personally found helpful, and why.

  1. https://vimeo.com/399733860

The video in the link above was recorded on 3/22/2020 and explains extensively how you can protect yourself and your family from COVID-19.  The author is Dr. David Price of Weil Cornell Medical Center in New York City, which is now exclusively devoted to COVID-19 patients.  All Weil does is see COVID patients, all day, every day.  This video is worth watching in its entirety.  The presentation is very careful and detail-oriented and does not overstate its conclusions. The presentation seems both transparent and without bias.

 

Above is a CNN interview with Bill Gates, recorded on 3/26/2020.  While Bill Gates is not a doctor, he has no political or other bias in this matter, as a philanthropist he’s not looking for personal gain.  Gates gave a TED talk on pandemics in 2015 (https://www.ted.com/talks/bill_gates_the_next_outbreak_we_re_not_ready/transcript?language=en) Gates is a highly intelligent computer scientist who knows how to hire other highly intelligent computer scientists and he has the resources to crunch data and do computer modeling.  

 

  1. 3/21/2020 New Yorker article entitled “Keeping the Coronavirus from Infecting Health-Care Workers.” 

The article above is authored by Dr. Atul Gawande, a surgeon at Brigham and Women’s Hospital in Boston. Gawande is very well published and the winner of numerous prizes for his articles addressed at a general audience.  You will find that this very readable piece correlates with the claims made by Price.

 

  1. https://www.latimes.com/science/story/2020-03-22/coronavirus-outbreak-nobel-laureate

Above is perhaps the most contentious of the list of articles I have put together.  It is a Los Angeles Times Article with an interview with Nobel Prize Laureate Dr. Michael Levitt.  Biophysicist Levitt won his Nobel Prize for multiscale modeling for complex chemical systems, and he argues that lessons from China show that with proper social distancing guidelines in place, the pandemic could be over sooner than is predicted.  This is iffy because the US started testing extensively and officially urging social distancing only about 10 days ago.  So we are a bit late to the game, and are right now experiencing the steepest increase in infections.  Nevertheless, according to the Coronavirus Map at John’s Hopkins, https://coronavirus.jhu.edu/map.html, out of 164,000 positive tests as of Tuesday Morning, only 1.2% had died, compared to 3.5% in China, without extensive use of hazmat equipment (obviously this is is subject to change as most of these cases were just diagnosed).

So, I included this last article despite the many variables that could change Levitt’s conclusions because it ends on a slightly more optimistic note.