As a medical student and researcher, I staunchly supported the efforts
of the public health authorities when it came to COVID-19. I believed
that the authorities responded to the largest public health crisis of
our lives with compassion, diligence, and scientific expertise. I was
with them when they called for lockdowns, vaccines, and boosters.
I was wrong. We in the scientific community were wrong. And it cost lives.
I can see now that the scientific community from the CDC to the WHO to the FDA
and their representatives, repeatedly overstated the evidence and
misled the public about its own views and policies, including on natural vs. artificial immunity, school closures and disease transmission, aerosol spread, mask mandates, and vaccine effectiveness and safety,
especially among the young. All of these were scientific mistakes at
the time, not in hindsight. Amazingly, some of these obfuscations
continue to the present day.
But perhaps more important than any
individual error was how inherently flawed the overall approach of the
scientific community was, and continues to be. It was flawed in a way
that undermined its efficacy and resulted in thousands if not millions
of preventable deaths.
What we did not properly appreciate is
that preferences determine how scientific expertise is used, and that
our preferences might be—indeed, our preferences were—very different
from many of the people that we serve. We created policy based on
our preferences, then justified it using data. And then we portrayed
those opposing our efforts as misguided, ignorant, selfish, and evil.
We
made science a team sport, and in so doing, we made it no longer
science. It became us versus them, and “they” responded the only way
anyone might expect them to: by resisting.
We excluded important
parts of the population from policy development and castigated critics,
which meant that we deployed a monolithic response across an
exceptionally diverse nation, forged a society more fractured than ever,
and exacerbated longstanding heath and economic disparities....<<<Read More>>>...