Author’s Note: Dr. Birx, Dr. Fouci, and others continually talk about “the data,” its importance, and what they have learned from it. I know too little about epidemiology to offer commentary concerning what is discoverable from sound data concerning COVID-19. I do have some largely unreported reasons not to believe “the data” upon which the country is relying is as sound as some would have us believe.
The data depicted above is from John Hopkins’s much-referenced COVID-19 Map. The information is chocked full of misleading information. Let’s sort out a few of the big ones.
The most prominent number on the map is “Total Confirmed,” the total number confirmed COVID-19 infections worldwide. The fact that the “Total Confirmed” number is reported at all, much less touted, implies that it is valuable information about how contagious/dangerous the virus is. Not so fast! The number is far less informative than it is cracked up to be and it is being misused[i]:
- First and foremost, “Total Confirmed” is flawed and is insignificant (more on that below) compared to an overwhelmingly more meaningful number, i.e., a number that might be labeled “Total Infected.” That is the only number that can reveal the danger posed by COVID-19. That epidemiologists are looking to “Total Confirmed” for answers reminds me of the old adage about an economist looking for his lost keys under a streetlamp. When asked if he lost his keys near the lamp, he said, “no.” When asked why he was looking under the lamp for the keys, he answered, “because this is where the light is.” Epidemiologists do not have access to the number that sheds enough light on COVID-19 to fully assess its danger. Without knowing how many or what kind of people have been infected with COVID-19, their only option is to grope around in dim light for compromised data. That data is a distant second best.[ii] [If you are interested in what can and should be done about this problem, I highly recommend the endnote ii video.]
- Another critically important number ignored by “Total Confirmed” is the number or percentage of people exposed to the virus who do not contract the disease. Not everyone exposed to the virus becomes infected.[iii] Consider these examples:
- President Trump has attended multiple meetings with people who soon after tested positive for COVID-19.[iv] Yet all of the several tests he has taken since reveal that he is not infected.
- Many, perhaps most, doctors, nurses, and assistants who are exposed to the virus every day have tested negative.[v] For example, if only 10% of the people exposed to the virus get infected, social distancing, much less universal stay-at-home orders would be a cruel hoax. I suspect that the contagion rate is higher than 10% but much lower than 100%, which is the impression that the COVID-19 Map might leave in the minds of the unwary.
Consequently, the “Total Confirmed” number omits many, perhaps a majority of infected people. In terms of the more relevant (but unreported) number of severe illness and death per person infected, the “Total Confirmed” number is seriously flawed and misleading. It leaves the impression that COVID-19 is much more dangerous than it is.
- The object of the “Total Confirmed” number is to inform as to how dangerous/scary COVID-19 is, i.e., how alarmed people should be. Let’s look at some of the ways “Total Confirmed” overstates the danger of COVID-19.
- Many people (some say a majority[vi]) infected with COVID-19 experience no effects. Whether they represent the majority of COVID-19 “victims” or not, they can be a huge number. Omitting large cohorts of the population in question unscientifically skews the results. In this case, the skewing overstates how scary/dangerous the virus is.
- People experiencing flu-like symptoms disproportionately seek tests and get “confirmed.” On average, the sample of people tested is unrepresentative of the COVID-19 infected population, i.e., they are sicker than the average infected person. Unrepresentative data is of limited value for analysis purposes but also skews the results toward scariness.
- In light of the above, the “Total Confirmed” number is necessarily smaller than the total number of people infected. No one can know how small a fraction “Total Confirmed” is of Total Infected.[vii] Comparing “Total Confirmed” to the number of severely ill or deaths (almost all of which are counted), the COVID-19 Map and the COVID-19 DATA Pack overstates the scariness of COVID-19—bigly.
- Even the “Total Confirmed” number is not nearly as scary as people appear to believe it to be.
- 81% of the confirmed COVID-19 cases are “mild.”[viii] Some are so mild, especially in children,[ix] that the symptoms are hardly noticeable, while others are indistinguishable from colds or the flu. So, the odds of an infected person (counting both confirmed and unconfirmed) having serious problems is substantially less than the 20% of “Confirmed Cases” the COVID-19 Map reports. Based on some reporting,[x] it is likely less than 10% of all COVID cases. Deaths per infected person could be much less than 2% of people infected.
- With its “New ICD code introduced for COVID-19 deaths,” the CDC is causing physicians to overstate the number of COVID-19 deaths. The code requires, “COVID-19 should be reported on the death certificate for all decedents where the disease caused or is assumed to have caused or contributed to death.” [Emphasis Added.] Rules that err in favor of what appears to be a desired, scarier attribution overstate the danger.
- Compilations of incomparable data are always of limited use. COVID-19 data from one country, state, or city has limited applicability to other countries, states, or cities. Here are some illustrative examples:
- COVID-19 first visited New York City and Seattle at approximately the same time. The population density of NYC is 3.4 times greater than in Seattle (and 7.3 times greater than Houston).[xi]5% of NYC residents use public transit, while only 20.1% do int Seattle (Houston doesn’t make the top 50 list that includes cities with only 7.8% ridership).[xii] NYC has 282 skyscraper buildings (massive clusters of people in confined spaces), while Seattle has 21.[xiii] Based on these characteristics, New Jersey, just across a river and connected by subways, should experience contagion rates more similar to New York than Seattle. These observations are born out by this data chart Dr. Brix presented.
- A person’s genetics can have a big impact on susceptibility and reactions to viruses. The genetics of populations vary by country.[xiv]
- The prevalence of certain preexisting conditions of an area has a significant bearing on the impact of the pandemic. The prevalence of relevant preexisting health conditions and combinations of preexisting conditions in each country or state are not measurable during the outbreak. The relative relevance of all the combinations of preexisting conditions when exposed to a new virus is determinable only after the virus’s pandemic is in the past, if ever.
- The quality and quantity of testing by the listed counties vary widely from country to country. When testing began relative to when the virus entered the counties varied significantly, e.g., the U.S. got off to a slow start. How testing progressed varied by country, e.g., slow starting America now outpaces most, if not all, other countries.[xv]
- Cultural differences likely play a role as to how a population will respond to advisories or orders, e.g., stay at home orders. Determining what cultural characteristics are relevant would be a challenge, would not be consistent from country to country, and probably cannot be measured in real-time anywhere, much less everywhere.
- As noted above, different jurisdictions will classify the causes of deaths and define “mild,” “severe,” and “critical” conditions inconsistently.
- Hopefully, few cities will have to suffer the consequences of the bad advice that New York City officials gave to New Yorkers.[xvi] For sure, edicts from officials will vary.
- According to reports, U.S. Intelligence has confirmed that China misrepresented the extent of its COVID outbreak.[xvii] China is a big part of the COVID-19 story, and the numbers its population adds to the analysis could substantially alter conclusions and recommendations.[xviii]
This list could go on indefinitely. Hopefully, this list is sufficient to convince you that “the data” upon which the country is relying to make monumental decisions about the extent to which and for how long the economy should be stifled is not all that it is cracked up to be. [See also, “Dr. Fauci Follies.”]
[v] “KCUS tested 48 samples, seven positive, doctors test negative.” [Google appears to be deep-sixing this kind of information. How this article slipped through Google’s filters is a mystery to me.]
[xiv] See endnote ix.