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Data, Science, and a COVID-19 Truth

“It’s going to disappear. One day, it’s like a miracle, it will disappear.” - President Trump

Earlier this year, I remember trying to ascertain the key differences between the typical seasonal flu and the novel coronavirus (COVID-19) that was emerging in faraway places. I learned quickly that COVID-19, otherwise referred to as SARs-CoV-2 had an older brother that emerged in 2003, SARs-CoV-1.

Both of these severe acute respiratory syndromes (SARS) started in Asia and had very similar transmission patterns, symptoms, and alarmingly high mortality rates; nearly 10% of cases. Indeed, the first SARS reared its ugly head during the months of November 2002 through March 2003. The WHO warned of the pandemic and the novel coronavirus quickly spread to over 24 countries in Asia, Europe, and the Americas. The guidance that was given to combat the disease at that time was 1) wash your hands, 2) don't touch the areas of your face, 3) cover your face when you sneeze and cough, and 4) don't share items that come into contact with respiratory secretions or fluids; they hadn't yet euphemized "droplets" into our daily lexicon. Doesn't that all sound eerily familiar?

In July 2003, when the pandemic was considered to be under control by all respected clinical infectious disease researchers, the WHO had reported that 8,096 people had been infected and that 774 people had died; from the entire planet; from every country put together from the first case to the last. The United States had only experienced 8 laboratory-confirmed cases and zero deaths. In the summer of 2003, the first novel coronavirus had disappeared - like a miracle.

So why is it that in November 2020 we have nearly 57,000,000 global cases and approaching 1,500,000 global deaths? Why is it that during the same period of the year in 2003, when the first virus seemingly evaporated from the earth, did the second wave of the 2020 virus crash more fiercely into the shore, and now why is the third wave of the virus overwhelmingly striking like a tsunami throughout just about every corner of the Earth?

It's because we relied on data that explained a scenario, of a viral spread, at a given point in time. We looked at our experience in the past, accumulated all of the most important and meaningful data, compiled by the best and brightest researchers, and drew conclusions. We assumed too many consequential similarities between SARs-CoV-1 and SARs-CoV-2 because they had too many apparent prescriptive similarities. We used our experience and data to draw the wrong conclusions at various points in time. We were wrong and we continued to be wrong. We failed to grasp the simple fact that everything continues to evolve and be different. We can't look at data regarding one event that happened in the past and notice that some variables are similar, and then conclude that the impact will be the same, any more than you can predict with certainty the outcome of a tossed coin; even if you have the best data of the past 100,000 coin tosses.

Data creates the basis to build ranges of valid scenarios; valid scenarios can describe the possible outcomes; expertise and insights from our greatest minds can help shape the probabilities of these outcomes and put in place designs to help policymakers to stabilize our countries to prepare for the inevitable, whatever it may look like.

Undoubtedly, the Trump administration used some data in an attempt to manage the crisis; their problem is that they used it incorrectly and at a static point in time. The President, himself, made the age-old mistake of supporting an early forecast of future events using data, and through policy and constant reassurance in the media, tried to mollify the masses even when the changing environment presented more questions than answers. The reality is that the early data and early models explained a potential scenario, a believable scenario, which had actually occurred, and when the data started to change so should have the forecasts and the then prevailing policies.

It should have been a natural dialogue. It should have been more forthcoming. It should have reflected the emerging realities of this newer, more lethal virus and the data patterns that showed that early assumptions were incorrect, and if not changed would lead to disastrous outcomes.

The data was there, but the people responsible for the message were not open to changing the message based on changing data. They feared it would have suggested mistakes, and to a limited degree, it can appear that way. But the larger mistakes were to ignore the changing data and subsequent knowledge and to not build policies off of the newest understandings. The first models assumed through data that the virus was equally transmittable on surfaces as it was airborne because the data they looked at initially suggested that to be the case. Dr. Fauci had initially said that masks weren't necessary "at that point in time", however when they realized that the spread was coming largely from airborne contact, the new data confirmed that masks were appropriate and necessary. Dr. Fauci wasn't wrong, he was just working off of data that did not describe the most appropriate scenario when he made that comment, and he was not wrong to change his opinion. Others were wrong to suggest that any statement made about these issues, the evolving unknown terrors, were and are immutable. Ah, the gotcha-game of the politicians and the media.

Yes, listen to the data and the science. But let us equally understand that data and science evolves and is a best-case placeholder for the future; this place holder is subject to many differences both in biology and the sociology of the human experience.

Death and taxes? Add wear a mask, social distance, and be patient for your vaccine.

No one could have explained or expected the magnitude of what we are experiencing. The data just didn't suggest it in reasonable probabilities. You would not have believed it could happen in 2020 because it didn't happen in 2003, and there was plenty of data to explain it. The problem was out of control before we knew it, and the blame falls freely across our society.

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