The Coronavirus Pandemic: Viral Psychology

The Coronavirus Pandemic: Viral Psychology

I entered the North Austin Trader Joe’s and couldn’t get in the door.  There was a flood of people walking in and out of the door.  Others were standing at the entrance deciding whether to enter or move on to another grocery store.  I decided to order through Uber Eats.

 

I eventually went to Trader Joe’s on at a less trafficked hour after social distancing was implemented.  I had time to speak with some folks in the line with me.  The lady in front of me was 72 years old veteran of the Hong Kong flu, who exercised regularly, but not as much as her son.  She came to Trader Joe’s because she and her husband love the Italian pasta at Trader Joe’s.  She did not want to run out.  Once she entered the store and saw the lines and the empty shelves, and decided she needed more.  As we were talking, she something caught her eye.  It was canned black beans in our neighbor’s cart.  I held her spot will she made a quick dash to the canned food aisle.  She came back with 4 cans.  I looked around and others were doing the same thing.  This phenomenon was self-reinforcing.  This explained the texts I was getting from friends and family about the virus, the stock market, shortages, and more.

 

Speaking with patients daily, I understand how psychology plays into their information processing.  As behavioral economist know, humans are poor at thinking in terms of probability.  A run on toilet paper and personal protective equipment, a tanking stock market, and overcrowded grocery stores are behavioral economics principles come to life.

 

To be clear, the COVID-19 (also known as SARS-CoV2) pandemic, is an infectious disease and public health problem that has spilled over into the rest of society and economy.  COVID-19 is a highly contagious novel beta-coronavirus, with a spectrum of symptoms.  At one end we find asymptomatic patients and at the other we find people need ventilator support.  Couple obvious challenges arise:

  • How do we identify the asymptomatic COVID-19?
  • Who’s at risk for becoming critically ill?
  • How do we treat this illness?
  • How do we keep the asymptomatic patients from potential patients needing ventilator support?

 

For the trained, we can turn to data and experience.  But how is the average person processing this information?   Remember for every Daniel Kahneman, the Nobel Prize winning economist, there’s a person at opposite end of the bell curve.

Let’s look at some concepts in behavioral economics and how they may apply to the coronavirus pandemic.

 

 

Anchoring Bias

This bias occurs when we rely on an initial piece of information rather than the whole picture.  The classic demonstration is through a priming question.  For example, we first ask was FDR older than 130 when he died before we ask how old was FDR when he died?  We will get a higher number from a test group than if we first ask was FDR older than 40 as our priming question.

Asking a test group to calculate 1 x 2 x 3 x 4 x 5 x 6 x 7 x 8 x 9 x 10 in a short amount of time (less time than needed to do the arithmetic reliably) results in a lower average guess than asking a group to calculate 10 x 9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1.  Experiments show we tend to disproportionally weight earlier information.

So, people have been relying on initial information to make judgements about the coronavirus.  They are anchoring much of the decisions to the initial messaging.

This explains several observations.  The most egregious error was when the pandemic was labeled a hoax.  Individuals who anchored their subsequent judgments to the “coronavirus hoax” may have delayed implementing social distancing, worsening the spread of the virus.

 

Availability Bias

People often use examples that come to mind more readily to assess the likelihood of risk given a specific topic.  When asked about the risk of hurricanes and other natural disasters, people often use examples that come to mind.  We can influence people by reminding them of a recent incident with a good or bad outcome.

The fellow Trader Joe’s shopper above was using lessons she learned during flu pandemics and applying them to the current coronavirus pandemic.  She had not taken the time to research the difference in reproductive number and case fatality rates.  When trying to understand the current pandemic, she filled in her knowledge gap by using rules of the first respiratory virus that came to mind.

 

Zero risk bias

People face risk on different fronts and often we chose to reduce the risk from one front entirely, to reduce cognitive strain, over decreasing the risk on different fronts for a greater overall risk reduction strategy.

Zero risk bias may explain the run on toilet paper.  Though people cannot completely control the risk for contracting the coronavirus, individuals can drive the risk of running out of household items to almost zero by stocking up.

 

Optimism and Overconfidence

Behavioral economist Richard Thaler best explains this phenomenon when he anonymously surveys his students prior to the beginning of an MBA course about what percentile they’ll end up in at the end.  Usually less than 5% of the class thinks they’ll be below low median.  Basically, most people think they are above average.

I wonder what spring breakers crowding Florida beaches in the middle of the pandemic would say if we asked them about personal risk?  Equally importantly, how likely are you to falling prey to personal cognitive biases? Above average, average, below average?

 

Especially during a crisis, we must take time to understand personal and population-wide cognitive biases.  If done properly, we will find ourselves reaching rational decisions faster, without irrational detours.  Our messaging will be more direct and effective.  In short, we can solve the coronavirus pandemic and limit its spill over into other societal aspects.

 

 

References

Kahneman, Daniel.  Thinking, Fast and Slow.  First edition.  New York: Farrar, Straus and Giroux; 2003.

Thaler, Richard H.  Misbehaving: The Making of Behavioral Economics.  First edition.  New York: W. W. Norton & Company; 2016.

Thaler, Richard H and Cass R. Sunstein.  Nudge: Improving Decisions About Health, Wealth, and Happiness.  2nd edition.  New York: Penguin Books; 2009.

 


I grew up in Salt Lake City and a suburb of Houston. I completed my MD and MBA in the great state of Texas. I gravitated to Austin and have found a home base for my journey. I spend my time working as a Hospitalist (inpatient internal medicine doctor), consuming information, writing, working out, investing, traveling, and hanging with my dog.

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