How To Deal With Coronavirus Part 5: We MUST Follow The Data, Not The Hype

I must begin by mentioning a little bit about my own career trajectory. Having been a Voice and Data Network Engineer for over 25 years, I have written numerous Business Continuity and Disaster Recovery plans and policies. I have held countless planning meetings. I have implemented some of those plans in the aftermath of events such Tropical Storm Allison, and Hurricanes Ike and Harvey. While this is my first plague, it is not my first crisis rodeo.

I speak from experience when I say that, as regards the public health, two principles above all else will guide effective response to the COVID-19 pandemic: prudent resource management and intensive application of all available data. When I say "follow the data", it is not merely a catchy phrase, it is an essential guiding principle towards successful public health response.

As I have said previously, I am neither a virologist nor a physician. I will not presume to pontificate on how COVID-19 infects the individual person, or how symptoms progress. For those individual medical discussions we must seek out the sanguine observations of health care professionals who are actively treating and observing the disease itself.

Rather, I am commenting on how communities respond to the disease, and how healthcare systems organize themselves to ensure that all sick individuals are able to receive treatment, whatever that treatment is. I am commenting on how businesses respond to ensure that they can remain in business while not spreading COVID-19 around. I am commenting on how governments--federal, state, and local--can enact prudent public health ordinances while not destroying the businesses which on which we all depend (quite literally for everything).

Talking Data Means Talking Logistics

At the communal, business, and government level, COVID-19 has never been a medical crisis, and has always been a crisis of resources. This has been something that both the complacent "it's just the flu, bro" deniers and the "It's not the flu!" hysterics have both ignored, to the detriment of everyone. The question was never whether it was or was not the flu, but how many people would get COVID-19's unarguably "flu like" symptoms, how many people would require hospital care, and how many people would need critical care.

Ensuring that people who need care receive care is a challenge of ensuring there are enough nurses and doctors (everyone should take a moment to thank any nurse you know--they are the front line in this crisis) to render treatment. That in turn is a challenge of ensuring there is space in the clinic or hospital to deliver treatment. It is a challenge of ensuring there are enough medicines, ventilators, protective gear, bed linens, disinfectants, and all the sundry "stuff" that gets used in providing care. It is a challenge of ensuring that other conditions are not neglected because of COVID-19: it is a poor public health outcome if we treat COVID-19 patients and ignore the heart attack victims, trauma patients, and innumerable other illnesses that regularly require medical care.

In short, it is a resource challenge. It is a challenge of logistics far more than science--knowing a successful treatment is meaningless if there are not the means to provide it. "Victory" against COVID-19 is not this myth of containment--not only has containment not been an option once China opted to lie and deceive about the disease, but the mass quarantine protocols attempted by China have been a clear failure--but rather successful management of medical resources so that we can treat the sick and continue on with our lives.

To direct resources to where they are needed most, to attend to the most critical resource, to even identify the most critical resources, we have no choice but to pay close attention to all the data we have. If we do not follow the data, we will not be able to husband resources properly, and that will mean hospitals not having supplies, nurses not having essential protections, and patients not receiving care. If we do not follow the data, we will not save all the lives that we can, and we will not save our communities. That is not an exaggeration. In this crisis, data is quite literally life.

For the sake of us all, follow the data!

Be Responsive Not Reactive

The paradox of information during a crisis event: it is at once wrong and indispensable. By the time data reaches us, it is out of date, and subsequent data will moot much of it. Yet if we do not follow it now, we are blind to the changes later, and such shifts are every bit as vital as any given snippet of data.

Washington State is a prime example of this. If one looked at the Influenza Like Illness patient visits from early to mid February, there was no disease outbreak worthy of note. By late February, however, significant disease outbreak was occurring, matched in time with positive test results for COVID-19.

Intriguingly, California showed a spike in ILI visits at the end of January, at a time when positive tests for influenza virus itself actually declined--indicating a probable uptick in COVID-19 and, thus, community spread. What makes that spike particularly fascinating is that it completely escaped the attention of the legacy media. There were no reports of overwhelmed hospitals, of full emergency rooms, of patients not receiving vital treatments.

What does this data tell us? Among other things, it tells us that while there was a relatively minor outbreak in California, the worst outbreak at the time in the United States was in Washington State. For public health officials particularly at the government level, this indicates where resources are needed most. For healthcare workers in other states who might be available to aid in treatment, this tells them where they are needed most.

It would be a mistake to regard the outbreak in California as severe as the outbreak in Seattle, or as the subsequent outbreak in New York City and New York State, which is now the most severe epicenter of COVID-19 in the United States.

It is an even bigger mistake to regard the whole of the United States as being the same as either New York, or Washington State, or California, or to regard New York as having an outbreak as severe as what is unfolding in Italy. New York is on a different trajectory than Italy; the case counts and timeline prove that unequivocally.

We must follow the data if we wish to respond intelligently to the disease and not react blindly. We must use all the information as it comes in to recognize the constantly changing landscape. The shape of the crisis yesterday is not the same as the shape of the crisis today, and neither will be the shape of the crisis tomorrow. Focusing on real world data and not being driven constantly by projections will keep attention focused on where the needs are most urgent, and on which resources are most urgently needed.

For example, even though the legacy media has been writing constantly about the dangers of full hospitals, in the Seattle area the most urgent resource need is proving not to be patient beds but PPE for healthcare workers. State and Federal stockpiles were not only not built up in anticipation for a disease outbreak of this scale, but those stockpiles have in many cases exceeded their shelf life and are now expired--spoilage is a constant challenge in resource accumulation, as it matters little to have an abundance of PPE that is no longer able to provided the needed protection. For obvious reasons, the CDC and state agencies are distributing even the expired PPE; the brutal logic of "something is better than nothing" applies.

This unfolding information also highlights critical resource needs. While many in the legacy media have been focusing on "testing testing testing", the data is telling us to focus on the manufacture of PPE first and foremost, as well as equipment such as ventilators. This is why President Trump correctly mentioned PPE and ventilators when he announced the invocation of the Defense Production Act, effectively putting the nation's industrial base on a wartime footing to expedite the production of needed resources. The needed resources are mask, ventilators, and similar materials, with COVID-19 diagnostic test kits somewhat farther down the list.

Following the data tells us what is needed most. Following the headlines merely tells us what is most popular among self-anointed "experts".

For the sake of us all, follow the data!

Testing Accomplishes A Whole Lot Of Not Much

Real world data also exposes the limitations of various response strategies. While the world's health experts have been a cacophony of clamors for tests, tests, and more tests, the real world data paints a far less rosy picture of testing.

Korea has used mass testing extensively, but the extent of disease uncovered by their testing is proving to be quite small: 96% of Korea's tests produce a negative result. Either the people tested presented with symptoms of something other than COVID-19, or the tests themselves are not all that accurate. Similar patterns are being observed across the United States--in Texas, where the disease outbreak is minimal, and in Seattle, where the disease outbreak is major.

What does this data tell us? Among other things, it reveals that mass testing is inadequate as a disease tracking tool. Contrary to what the "experts" have been saying, mass testing simply does not identify enough disease quickly enough to get in front of the community spread. This conclusion is confirmed by recent new outbreaks of COVID-19 in Korea.

This is not a criticism of the test itself. Far from it. Diagnostic testing is unequivocally an essential part of both patient treatment in the hospital setting and infection control among health care workers, who are at the highest risk owing to their constant exposure to the virus. I have said before that health care workers absolutely must be tested regularly, and I will keep on advocating for that.

Yet every tool has its limits. Every medicine has its purpose. As a tracking tool mass testing has shown itself to be not fit for purpose. Even the self-anointed experts are waking up to this reality and returning to the data set that has been tracking the disease all along, the previously mentioned Influenza Like Illness statistics. At the risk of sounding a tad egotistical by crowing "I told you so", we must also note that this information has always been available and it is unconscionable for so many presumed professionals to have ignored this data set for so long.

Could more immediate action have been taken in Seattle or New York had more scrutiny been applied to the Weekly Influnza Report for those areas? We can never say with certainty, but there is no doubt that an opportunity for more proactive measures was missed because people were focusing on the wrong data and setting the wrong priorities.

We must look at all the data, we must heed the conclusions that arise from logical consideration of all the data. Focusing on any one bit of data in isolation will lead us in a wrong direction.

For the sake of us all, follow the data!

Data Is Not Just About Answers, But Also Questions

As vital as all the resource management answers we may derive from the wealth of data that we have about the COVID-19 pandemic, we must not lose sight of something equally important, both for resource management but also for further medical research: questions.

One question I have asked repeatedly throughout this pandemic: "Where are all the cases?" Given the estimates and projections put forward, both as regards China and the rest of the world, the projections and the real world reports have never lined up. The patients have not materialized in hospital ERs or doctors' waiting rooms.

This question deserves more scrutiny than it has received, because if people have the disease and are not feeling compelled to seek medical treatment this has major implications both as to the severity of the disease and its public health impact. Keep in mind that in terms of public health, COVID-19 is not the crisis--full hospitals are.

This question also serves as a sanity check on many of the projections that are being offered up uncritically in the legacy media. One estimate offered up recently is that 86% of COVID-19 cases are undetected. Following that logic, and using the reported numbers at the time, one could quickly conclude there were approximately 38,000 COVID-19 cases in the United States. While that number is high, and has grown considerably higher even in the few days since that estimate came out, one reality will not change: 38,000 is not one million.

What is the significance of the number one million? That is the total number of estimated H1N1 cases in the United States two months into the 2009 Swine Flu pandemic--approximately the same point as we are now with COVID-19. By the end of the H1N1 pandemic, the United States experienced some 60.8 million H1N1 cases.

Therefore, when we read of projections that say 50-70% of Americans will get the disease, that 150 million Americans will be sickened by COVID-19, we must question how a disease that so far has not sickened even a significant fraction of what we saw in 2009 with H1N1 can possibly be able to sicken nearly three times as many. The 1918 Spanish Influenza infected 28% of Americans, H1N1 20% of Americans, yet COVID-19, despite less disease spread than either of those two pandemics, will infect more? How does that make sense?

It does not make sense. Which tells us that such projections are in all probability egregiously and even erroneously exaggerated. Which tells us that the concerns being trumpeted by those putting full faith in those projections are very likely not the real concerns before us, not the truly vital priorities for successful management and mitigation of COVID-19. The data says we are looking at the wrong targets if we look at these projections.

If projections are not being constantly updated with real world data, they must be discarded as worthless, for that is what they are. Where projection and data conflict, always stick with the data.

Even more critical than identifying the errancy of various projections is a vital medical question that needs exploration: Why is COVID-19 so much more serious in some places than in others. New York, as bad as it is, has not been on the same growth curve as Italy, despite having comparable population. Washington has not been New York. California has not been Washington. Neither Italy, New York, Washington, nor California have been Korea. Why is that?

Are there multiple strains of the virus? There certainly has been reporting of at least two strains, one more lethal and the other more infectious. Is the virus mutating rapidly, producing a changing picture as to which cases will become severe and which cases will not?

These are but a few questions posed by the data. I am no doctor, and I will not attempt to answer those questions. I will ask those questions again and again, and hopefully will find a doctor who can answer them. Knowing what the real world severity of a particular strain is allows us to chart what manner of response we are likely to need; if there are multiple strains out there--and the data at least raises that possibility--that question must be answered definitively. Refining projections as we go will give us greater visibility as to future prognoses, and give everyone some measure of guidance about what to expect from this disease. Projections grounded in reality will yield responses grounded in reality, while projections grounded in nothing at all will result in responses grounded in panic and hysteria--the worst possible response in any crisis.

For the sake of us all, follow the data!

Data Is Everyone's Friend

The greatest virtue of data is that everyone can trust data. Numbers are exactly what they are, neither more nor less. Everyone can look at a series of numbers and see if they are increasing or decreasing, and at what rate. Everyone can see the distribution of numbers and see where they might fall in that mix. Everyone can see rates of spread, locations of spread, and determine their particular risks and their community's risks for themselves. Data is there for us all to use as best we can. We owe it to ourselves, to our families, and to our communities to do exactly that.

Most of all, we should never place blind faith in any experts. No matter how well intentioned they might be, all of them are just as human as the rest of us. No matter how well intentioned they might be, they have already failed to provide the analyses we need, the conclusions we demand, the solutions we require.

I will even go so far as to say not to trust me. Look at the data, and decide for yourself if my conclusions make sense or not, if my logic is sound or not. Take what you find usable, and put aside what you do not. Do not follow me, follow the data.

But, for the sake of us all, follow the data!