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Unmasking The Covid Realities – The CDC Still Needs To Find The Data

Mark Twain famously said: Get your facts first, and then you can distort them as much as you please. As if to stand these words on their head, the US Covid-19 response has been an exercise in selective data collection. This is not only hubristic but also unscientific. The consequences, if the process continues, will result in further pain and suffering. Making matters worse, the Centers for Disease Control, CDC in its new mask guidance has introduced confirmational bias into the equation. Confirmational bias happens when we search for, favor, and recall information that supports our desired outcome while, simultaneously, dissuading us from collecting any facts that might prove counter to that desired end. In this case, the desired end is a rapid return to normalcy.

The desire for a return to normalcy (however defined) is understandable, but in this case, it cannot be achieved at any cost because that cost will be devastating. Many politicians, and even some scientists, are ignoring Twain’s advice. They are less interested in acquiring all the facts and prefer to embrace those select views which comport to proclamations of successful crisis management.

The news in this case, is not all bad – nor is it all good. There is ample evidence that we are seeing some progress in dealing with the COVID-19 pandemic; witness the declining infection and death rates in the U.S. – presumably in response to vaccinations, better social and personal responsibility, and the seemingly indefatigable care provided by health care workers.  However, one need only realize that the U.S. still has moving 7-day averages of over 38,534 new cases and 780 deaths to realize that this is far from over. Or, if you prefer, look at India with 2.9% of its population fully vaccinated and Seychelles with 61.9%. The former has 23 million cases and 250,000 deaths while the latter has a higher number of infections per capita than India!

India’s catastrophe may be blamed in part on poor planning and false claims of Covid-19 control, but Seychelles seemed to be doing everything right yet is entering very dire straits. What is missing? We lack comprehensive data.

A few days ago The Select Coronavirus Crisis Subcommittee Hearing on the Pandemic Response made it pellucidly clear that we are implementing policies, expending resources, and confusing the public because of incomplete, or totally absent, data. All four witnesses (Anthony Fauci, Rochelle Walensky, David Kessler, and Peter Marks) repeatedly stated that they lacked the data to be more specific in answering direct questions. The answers they did provide, were based on reports that were weeks or months old rather than on more current information. One telling exchange was that between Senator Susan Collins and Dr. Rochelle Walensky over The New York Times article ‘A Misleading C.D.C. Number’ which presented the exaggerated risk of outdoor transmission of Covid-19. Dr. Walensky cited an earlier report for the C.D.C. recommendation as there was no current data available to justify a revision.

Within two days of her testimony, Dr. Walensky reversed herself and announced that masks were no longer needed for outdoor, and even many indoor, gatherings of vaccinated individuals. This action suggests that the response was based on political and public pressure rather than cold, unbiased, and sterile data. Is this relaxation of mask-wearing warranted? We will know within weeks. We may not like the outcome.

Another example of the importance of data collection and analysis comes in the form of a recent report from the Institute for Health Metrics and Evaluation (IHME) that suggests 6.9 million people worldwide have died from the disease, more than twice as many people as has been officially reported. The IHME analysis mined data and considered six drivers:

1.   the total Covid-19 death rate, that is, all deaths attributed to Covid-19 infection;

2.    the increase in mortality due to needed health care being delayed or deferred during the pandemic;

3.   the increase in mortality due to increases in mental health disorders including depression, increased alcohol use, and increased opioid use;

4.   the reduction in mortality due to decreases in injuries because of general reductions in mobility associated with social distancing mandates;

5.   the reductions in mortality due to reduced transmission of other viruses, most notably influenza, respiratory syncytial virus, and measles; and

6.   the reductions in mortality due to some chronic conditions, such as cardiovascular disease and chronic respiratory disease, that occur when frail individuals who would have died from these conditions died earlier from Covid-19 instead.

This detailed analysis gives a more accurate assessment of the problems presented by the pandemic, yet despite the obvious need for better data collection and analysis, the C.D.C. announced that it would be cutting back on data collection. This cannot go on. Only with clear, unfiltered, and unbiased data can we hope to mount an effective and efficient response to the problem. This is no time for distortion. We must start with the facts.

There is, however, a path to good news. Absent better, more widely available, and effective therapeutics, we do have a currently available, and underused, tool at our disposal that you have most likely never heard of. It is not in itself a therapeutic, but it is essential for effective and efficient pandemic planning and targeted therapeutic development.

The National COVID Collaborative (N3C) is an electronic health record repository of over 5.6 M+ patients including 1,550,337+ Covid positive patients.  This staggering amount of information is held in 6.2 B+ rows of data and provides enough substrate to currently support 173 projects. The projects range from evaluation of anti-thrombotic therapies to the effects of alcohol consumption on Covid-19 outcomes and a host of other studies.

If we need validation of this approach, the business world has recognized and invested in the collection of data for more than a generation. And some hedge funds have made hundreds of billions in the process. The Man Who Solved the Market tells the story of Jim Simons who started Renaissance Technologies and led it to become arguably one of the most, if not the most, successful hedge fund. He achieved this by replacing the emotion, intuition, and insight model with a quantitative, data-driven approach. His team mined mountains of data looking for hidden patterns of market governance. This approach is now recognized as a critical tool for not just investing, but also for innovation, research, and development. I go even further and suggest that this model, if applied to N3C, holds the promise of real solutions to the Covid-19 dilemma. Quantitative analysis offers a path. N3C provides the tools. With this information, we may understand what is going on in the Seychelles, India and of course here in The US. Then, and only then, will we be able to both understand and learn how to deal with Covid-19. If there’s any doubt of this, think of Mark Twain again, because he also said “a forgotten fact is news when it comes around again.”

What do you think?

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