Are We in a State of Hysteria Over COVID-19? (2)


Reasons to Wonder

It would be irresponsible at this point to claim that our response to the COVID-19 situation is hysterical.  However, I do believe that it is legitimate to ask the question and explore the possibility that it is.  It’s indisputable that many people in the media, government and general population have behaved in hysterical ways as the pandemic unfolded.  But that fact in and of itself doesn’t necessarily mean that the overall government and cultural response is hysterical.  There are, however, reasons to wonder.

Model Based Projections

General Considerations

Given my previous concerns about the use of computer models to “predict” global warming / climate change (see here and here), it raises a yellow flag when I see our political leaders basing their decisions on this resource.  The flag turns to red when I hear the very people who claim expertise to create and interpret models of COVID-19 infection and mortality complaining about the lack of sufficient and/or accurate data.

A computer model can be conceptualized to consist of two main components, those being:

  1. The set of data necessary for the model to function and
  2. The mathematical functions that transform the input data into the desired output data.

In the cases of COVID-19 the data may be the number of new infections and deaths over time for a defined geographical region.  The transformation functions are difficult because the modeler must make assumptions about key dimensions and then convert these assumptions into mathematical relationships that describe reality, for example:

  • How contagious the virus is
  • The modes of virus transmission
  • Sensitivity of transmission to population density, mobility, etc.
  • Sensitivity of transmission to government policy (e.g., quarantine, stay at nome orders, etc.)
  • Severity of illness as functions of age, underlying health conditions, medical intervention, etc.
  • Mortality as functions of age, underlying health conditions, medical intervention, etc.
  • Among others…

Thus, when considering the predictions of models for a new and little-understood virus decision makers and the general public should respond with caution.  That is, they should understand that these models are not predictors of reality, but rather abstract, artificial constructions based on insufficient data and human understanding.  This all isn’t intended to exclude the use of models, but rather to ensure that their predictions are treated with the caution that the unseen but real uncertainties associated with their construction demand.

For those of us whose professional careers depend on mathematical modeling, and who are held accountable for the results, one statement attributed to the statistician George Box, best summarizes our position, that being: “All models are wrong, but some are useful.”  Dr. Deborah Birx of the White House COVID-19 task force put this model wisdom into practice with this recent statement.

“Models are models. When people start talking about 20% of a population getting infected, it’s very scary, but we don’t have data that matches that based on our experience.”

The good doctor isn’t denigrating models,  but she is insisting that they cannot be substitutes for reality.

We would all like to accurately predict the future for something as terrifying as a new virus that has caused a global pandemic.  And unfortunately there are too many people in the scientific community who are willing to take advantage of that desire.  So, when credulous politicians, media and general public come into contact with modelers seeking influence and notoriety, the results can be devastating.  In the following posts this issue will be illuminated  and discussed at length.

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