People at Increased Risk for Severe Illness

Important Questions Regarding the Response to Coronavirus

As the Covid-19 issue has become so prevalent and so disruptive, and as I have had so many requests for my opinion, whatever it may be worth, I felt compelled to share my perspective.

As a trained scientist I have had repeated to me, and I have repeated to others, thousands of times, the phrase, “valid analysis of valid data is everything”. In science valid data is everything. Without valid data in science, we have no ability to make valid, data-centric conclusions which can be used to create valid, data-centric policies with the best chance to achieve desired outcomes.

Data is neither calming nor fear-mongering. Sometimes data creates rational fear, sometimes it calms irrational fears. Most importantly however, valid data is required to create scientific, rational responses and scientific, rational policies that have the best chance to produce desired outcomes. Without valid analysis of valid data, we are guessing. Guessing, by definition, is not science. We need science. We need rational, data-driven scientists that guide politicians and the public to make rational decisions.

Let’s start with the recently changed definition of pandemic. Here are some citations from a 2009 article published in The British Medical Journal regarding the over-reaction to the 2009 A/H1N1 “pandemic” entitled ‘Calibrated response to emerging infections’, which I think are highly relevant to the current “pandemic”. (Doshi, P. Calibrated response to emerging infections. BMJ 2009;339:b3471).

I suggest you read this entire article, I think it offers an important perspective and it is very well written and well referenced.

Here are the citations:

“Since the emergence of novel A/H1N1, descriptions of pandemic flu (both its causes and its effect) have changed to such a degree that the difference between seasonal flu and pandemic flu is now unclear. WHO, for example, for years defined pandemics as outbreaks causing 'enormous numbers of deaths and illness,' but in early May, removed this phrase from the definition.”

WHO definition of influenza pandemic before 2009 A/H1N1 “pandemic”: 'An influenza pandemic occurs when a new influenza virus appears against which the human population has no immunity, resulting in epidemics worldwide with enormous numbers of deaths and illness.'

WHO definition of influenza during and after 2009 A/H1N1 “pandemic”: 'An influenza pandemic may occur when a new influenza virus appears against which the human population has no immunity.' Note no mention of “enormous numbers of deaths and illness”.

CDC description of pandemic in 1997 before 2009 A/H1N1 “pandemic’: 'The hallmark of pandemic influenza is excess mortality.'

CDC description of pandemic during and after 2009 A/H1N1 “pandemic”: 'There are some pandemics that look very much like a bad flu season.' Note no mention of mortality.

Canada definition of pandemic in 2006 before 2009 A/H1N1 “pandemic”: 'An influenza pandemic results if many people around the world become ill and die from such a virus.'

Canada definition of pandemic during and after 2009 A/H1N1 “pandemic”: 'An influenza pandemic does not necessarily cause more severe illness than seasonal influenza.” Note no mention of mortality.

“On 26 April 2009, with 20 cases and no deaths in the US, the Department of Health and Human Services declared a nationwide public health emergency [regarding the A/H1N1 “pandemic”].”

My first point is that we have changed the definition of pandemic and this alone means that a pandemic is now defined as something that is no different, or even less fatal than, a normal flu season. The word pandemic has serious fearful connotations because it is anchored to widespread severe illness and mortality. Why is this the case? Because prior to 2009 this was the definition of a pandemic.

The fact that the current outbreak of Covid-19 is already being classified as a pandemic when there is no evidence that Covid-19 is causing more deaths than regular influenza is important. This would not have been the case prior to 2009.

An important question to be answered, since a pandemic is now defined as an illness that is no worse than a normal flu season in terms of illness and mortality, is, what are the hospitalization and mortality figures in a normal flu season? The CDC reports that the annual number of people in the U.S.A. who get ill from the flu each year ranges from 9-45 million, that between 140,000 and 810,000 are hospitalized, and that 12,000 -61,000 die from the flu each year.

So, it would appear then, that to meet the criteria of pandemic, Covid-19 would have to at least equate to the worst-case scenario of an annual flu season or cause 45 million illnesses, 810,000 hospitalizations, and 61,000 deaths in the U.S.A.. Let’s keep that in mind as we evaluate the response to the Covid-19 “pandemic”.

Let’s now discuss the lack of valid data regarding Covid-19.

In order to compare Covid-19 to the above stats for annual flu, and to evaluate the appropriateness of our response to Covid-19 compared to our response to the flu, we need to have accurate stats or data on Covid-19. Herein lies another HUGE problem.

Below are some quotes from a very recent paper by John P.A. Ioannidis: C.F. Rehnborg Chair in Disease Prevention, Professor of Medicine, of Health Research and Policy, of Biomedical Data Science, and of Statistics; co-Director, Meta-Research Innovation Center at Stanford. Here is the reference to the paper: Ioannidis, J.P.A. A fiasco in the making? As the coronavirus pandemic takes hold, we are making decisions without reliable data.

Dr. Ioannidis shares my opinions both about the importance of data, and the lack of available valid data regarding Covid-19. Below are some quotes from his paper.

“In the coronavirus pandemic, we’re making decisions without reliable data.”

“The current coronavirus disease, Covid-19, has been called a once-in-a-century pandemic. But it may also be a once-in-a-century evidence fiasco.”

“At a time when everyone needs better information, from disease modelers and governments to people quarantined or just social distancing, we lack reliable evidence on how many people have been infected with SARS-Co-V-2 or who continue to become infected.”

“The data collected so far on how many people are infected and how the epidemic is evolving are utterly unreliable.”

“We don’t know if we are failing to capture infections by a factor of three or 300. Three months after the outbreak emerged, most countries, including the U.S., lack the ability to test a large number of people and no countries have reliable data on the prevalence of the virus in a representative random sample of the general population. This evidence fiasco creates tremendous uncertainty about the risk of dying from Covid-19. Reported case fatality rates, like the official 3.4% rate from the World Health Organization, cause horror – and are meaningless. Patients who have been tested for SARS-Co-V-2 are disproportionately those with severe symptoms and bad outcomes.”

“Adding these extra sources of uncertainty, reasonable estimates for the case of fatality ratio in the general U.S. population vary from 0.05% to 1%.”

In other words, there are likely many, many cases of Covid-19 that go undetected while the most serious cases get detected. This biased selection criteria regarding who gets tested is likely greatly confounding both the serious illness or required hospitalization rates and the mortality or death rate because the hospitalization and mortality rates are calculated as the number of hospitalizations or deaths divided by the number of cases. If the number of cases, the denominator, is vastly underestimated and the number of hospitalization or deaths, the numerator, is not, then the rate of hospitalizations or death per case gets vastly exaggerated.

You cannot have an accurate hospitalization or mortality rate that is calculated as a percentage of hospitalizations or deaths from total number of infections if you don’t have an accurate number of the total number of infections. Garbage in, garbage out. The data on total number of cases is GARBAGE – this is irrefutable! What this means, as Ioannidis is pointing out, is that our estimates of hospitalization and death rates are also, at this point, GARBAGE.

Now, it is not just the relative rate of hospitalizations that is significant. The gross number of hospitalizations is also very crucial because a large number, regardless of what percentage of total cases this represents, could still overwhelm the capacity of the hospital system and this is cause for rational fear.

To figure this out we need two numbers. We need the maximum number of people we think might be infected at any given time and we need to know the percentage of those people that will require hospitalization at any given time. Predicting the maximum number of people that might get infected is difficult but reasonable estimates are possible if we know how infectious or how easily spread the virus is. In the case of Covid-19 it appears it is more infectious than the flu but again, we have no real data because we don’t know how many people are infected. We also don’t know what percentage of those infected require hospitalization. We just don’t have the data we need.

We do have data from Italy regarding total number of deaths attributed to Covid-19, as of the time I am writing this, the death total in Italy is 6,077. However, we have no idea what the death rate in Italy is because they suffer from the same lack of accurate data regarding total number of people infected.

Now, let me be clear. The death total in Italy is horrifying and tragic. However, the important question with respect to evaluating Covid-19 vs the normal flu, is not if Covid-19 is causing death, but whether or not this total is significantly higher than the total of influenza-linked deaths in Italy in a normal, or even severe flu season.

We must also keep in mind that, whatever the flu season hospitalization and death statistics are, they do not elicit the reaction of initiating social isolation and shutting down the economy. Nor do we have flu infection counters and flu-linked death counters on the screen of every news cast. Nor, for more perspective, do we do this with air pollution fatalities (7 million per year worldwide), or traffic fatalities (1.35 million per year worldwide). One must wonder what the reaction would be if we did. One must also wonder, why we don’t.

Why are deaths from these causes less important, especially due to the flu, since social isolation would clearly have the same effect on flu as it would on Covid-19. Why do we not declare each flu season a flu pandemic and insist on social isolation and shut down the economy? Probably because these deaths are considered an insignificant, and thus accepted portion of, the 60 million deaths that occur every year worldwide.

Like it or not, as a society we have concluded that it is acceptable that every year, thousands of people, mostly elderly with underlying health conditions, will die from flu or, more accurately, complications from the flu. We could socially isolate every year and almost certainly prevent many of these deaths, but we have decided that the cost:benefit of such a policy does not warrant implication of such a policy. I’m not arguing if that is correct or incorrect, or moral or immoral, I’m simply arguing that it is a reality and one that must be used as a comparator for any policy decisions regarding Covid-19.

A 2019 paper published in the International Journal of Infectious Diseases reported that in the 2016-17 flu season, the estimated number of deaths attributed to influenza in Italy was 24,981. They also report that, “Italy showed a higher influenza attributable excess mortality compared to other European countries, especially in the elderly.” (Rosano, A. et al. Investigating the impact of influenza on excess mortality in all ages in Italy during recent seasons (2013/14-2016/17 seasons). International Journal of Infectious Diseases 88 (2019) 127-34.)

This means that the number of deaths in Italy attributed to Covid-19, albeit with the drastic social isolation measures put into place, represent less than 24% the number of deaths from “influenza-like-illness” in the 2016-17 flu season – which was not identified as a pandemic and did not result in any social isolation policies. In fact, as in every major country, the annual flu season was not named a pandemic, was barely reported on, and certainly did not result in a flu infection, hospitalization, or mortality rate counter on virtually ever news cast. Again I ask, why not?

Again to quote Ioannidis, “If we had not known about a new virus out there, and had not checked individuals with PCR tests, the number of total deaths due to “influenza-like illness” would not seem unusual this year.”

Now, what we can’t say, is what the number of deaths in Italy would have been without the drastic social isolation measures or what the number of deaths in the U.S. or Canada might be without drastic social isolation measures. We have not data on this either.

My argument is not that we have data to show that we are over-reacting. We don’t. My argument is that the reaction we are having is not based on data and that it is based on worst-case scenarios. We need more data. We also have to understand, and empathize, the fact that in the face of inadequate data, politicians and healthcare agencies are forced with the unenviable position of having to make a decision. Damned if they over-react, damned if they under-react. These poor people have such grave responsibility and such little data, it must be extraordinarily difficult.

I am certainly not suggesting we damn them for either! I openly admit that I might make the same decision based on the current available data, or lack thereof. What I don’t admit is that I would not have done EVERYTHING POSSIBLE to get better data. This is the real tragedy; we could have gotten better data. I’m not even sure who is responsible for this but somebody is or some agency is and whoever is responsible should be held responsible and measures to avoid this in the future MUST be put into place, or into law perhaps.

I’m also saying that, to date, no country is reporting deaths from Covid-19 that surpass even a normal flu season. Is this because of the drastic social isolation measures that have been taken? We don’t know. We don’t even know if the drastic social isolation measures we are taking are effective. Again, we just don’t have any valid data. I hope you are seeing the importance of valid data!!

Will there be HUGE consequences to emotional, physical, financial, and likely social health because of the drastic social isolation measures we have taken? Yes, this can be confidently stated based on data; we have studied the effects of social isolation and unemployment and bankruptcy and losing homes. Just take a look at the research on the effects of unemployment and poverty on emotional health and addiction, and deaths from addiction, and hunger, and health effects of malnutrition. Look at the research on the effects of poverty and drug addiction on crime rates. Let’s at least validly assess the data we do have. Let’s at least consider the potential loss of life from the policy as seriously as we do from Covid-19. It’s not about money, it’s about the effects of financial ruin on mortality rates and quality of life.

If we are going to create models or scenarios of the consequences of Covid-19, it seems logical and reasonable to also create models or scenarios of the consequences of our response to Covid-19. If we are going to use worst case scenarios to guide our policies for Covid-19 should we not also use worst case scenarios to evaluate the consequences of these policies and take these scenarios into consideration when creating policy?

So, the real question is, are the consequences of the drastic measures going to more harmful than the consequences of Covid-19 if we did not take these drastic measures? We don’t know, we don’t have data. We should at least be asking this question and this question should at least be part of the discussion.

Would a better strategy have been to do whatever necessary to isolate or quarantine the immunocompromised rather than shut down the entire economy and isolate the rest of the population who are at the same or less risk of harm from Covid-19 as they are from the cold or flu?

Let’s at least start asking these questions. Let’s not just presuppose that the response we are taking is the only option, or even the only option moving forward, or that we cannot alter this option as valid data comes in. Let’s not lock ourselves into any response that is not based on valid data. Let’s admit we don’t have the data, let’s collect the data, and let’s properly analyze and use that data when we do get it.

In the meantime, let’s all fully participate in the current social isolation strategy so that we can at least get some valid data regarding its effectiveness. If we don’t follow the recommendations of the current strategy, and the current strategy fails, we will never know if that failure was caused by non-compliance or from the fact that the strategy was ineffective. In such a scenario those in charge may choose to indefinitely continue the same drastic policies.

Let’s hope the current drastic measures are successful and that we can all get back to our regular lives sooner rather than later and get to work spending the next several years recovering. Let’s be empathetic to each other and let’s be kind to those less fortunate who will suffer more than we will.

Let’s be aware that it is the elderly and frail that are most at risk from Covid-19 but let’s also be aware that it is the poor and the young who are most at risk from the financial effects of the social isolation policy in response to Covid-19. All lives matter and all lives must be considered. An immediate death from Covid-19 is no more or less tragic than a gradual death from depression and suicide, drug overdose, or malnutrition from poverty and despair caused by unemployment.

Let’s be good citizens who follow the policies put into place by those who are well-intentioned while we are also being good citizens who demand data-driven policies and data-centric answers to our questions about existing policies.

Whatever ends up being worse, the effects of Covid-19 or the drastic measures that have been put in place to try and deal with it, let’s all work together to get through this and to recover from it.

The truth is that we are now in the position of suffering the consequences of both. Dark times indeed.

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