If data analysis is insensitive or appears to "trivialize" a pandemic, does it make the research false? The arguments of the lockdown and mask totalitarians are so fickle that they must resort to unprecedented censorship in order to win the day. Their views cannot coexist with any trace of dissent on the internet, which is why Johns Hopkins University, which has become a lead advocate for lockdowns, is evidently now censoring its own faculty in academic research.
Last week, the Johns Hopkins News-Letter, a student newspaper, posted an article by Yanni Gu titled, "A closer look at U.S. deaths due to COVID-19." It was based on an analysis conducted by Dr. Genevieve Briand, an economics teacher at Hopkins. I originally saw the article on Thanksgiving morning and quickly saw this very catchy conclusion. "These data analyses suggest that in contrast to most people's assumptions, the number of deaths by COVID-19 is not alarming. In fact, it has relatively no effect on deaths in the United States."
When I clicked on it Thursday night, the link was dead. Then I saw that the Twitter account for the Hopkins News-Letter announced that it had been deleted:
Thankfully, the internet is eternal and you can still see an archived version here.
Isn't it interesting how any analysis that seems to cast doubt on the prevailing panicked narrative of the virus must immediately be deleted or censored? When was the last time you saw one of the numerous inaccurate papers overstating the threat of the virus taken down from the web or labeled as inaccurate on social media?
How many people really died earlier in 2020?
The article originally posted by Gu seeks to answer the following question: Are there really anywhere near 260,000 excess deaths this year of people who died early due to COVID-19? Gu, the student who wrote the article, notes that based on Briand's use of CDC's excess death data, there have actually been relatively few excess deaths this year. More shocking still is that her analysis shows a commensurate drop in deaths among other typical leading causes of fatality this year. "Briand believes that deaths due to heart diseases, respiratory diseases, influenza and pneumonia may instead be recategorized as being due to COVID-19."
So how are the deaths being recategorized?
"The CDC classified all deaths that are related to COVID-19 simply as COVID-19 deaths. Even patients dying from other underlying diseases but are infected with COVID-19 count as COVID-19 deaths. This is likely the main explanation as to why COVID-19 deaths drastically increased while deaths by all other diseases experienced a significant decrease …
If [the COVID-19 death toll] was not misleading at all, what we should have observed is an increased number of heart attacks and increased COVID-19 numbers. But a decreased number of heart attacks and all the other death causes doesn't give us a choice but to point to some misclassification," Briand replied.
What professor Briand also found peculiar is that the percentage of deaths among those in the 65+ bracket appear to be relatively similar to those in younger brackets and has remained pretty constant even after the epidemic began.
To be clear, the data she is using is just from April. A lot of additional people have allegedly died from COVID-19 since then. However, April is when we experienced the strongest wave, which would have netted the most deaths of any month.
On Friday, following much social media buzz about the publication's retraction notice on Twitter, the News-Letter posted an editor's note explaining why the article was removed but did provide a link to it in a pdf. Just two of the paragraphs even attempt to entertain the points made in the original analysis. The editors claim the article "has been used to support dangerous inaccuracies that minimize the impact of the pandemic." Next, they move on to the typical "credentials" insult by noting, "As assistant director for the Master's in Applied Economics program at Hopkins, Briand is neither a medical professional nor a disease researcher."
The main point the editors' retraction notice makes is that the CDC has said there have been 300,000 excess deaths. However, we already know that many of them have been due to lockdown and that many the CDC considers excess deaths would have died from other conditions during the same calendar year, which is the main point of Briand's analysis. And with conflicting data, who is to say the CDC is correct about that? This is why this needs further study to harmonize and validate all the data, as Briand herself said.
Next, the editors' retraction notes,"Briand presented data of total U.S. deaths in comparison to COVID-19-related deaths as a proportion percentage, which trivializes the repercussions of the pandemic" and further "does not disprove the severity of COVID-19." So now an academic institution is writing an emotional screed about "severity." We all understand that people have died from the virus. If this virus killed people a few months early within the same year, we can have a debate over language sensitivity, but it doesn't disprove the point that the excess deaths for a given year are not what they are being portrayed as. While we can debate the language the student used in the original article stating the deaths were "not alarming," the retraction doesn't disprove, and in indeed tacitly agrees, with Briand's main research point – that the distribution of deaths seems to be fairly constant across all age groups.
Hence, one could take issue with some of the language used by the student to portray Briand's research, but the broader findings are intriguing and should be discussed and debated. This retraction is a political decision, not an academic one.
This is not the first analysis to "downplay" the human toll of COVID-19
While this analysis, which can be viewed in an hour-long video, needs further study, it's not like the point is entirely novel. The retraction notice notes, "Briand's study should not be used exclusively in understanding the impact of COVID-19, but should be taken in context with the countless other data published by Hopkins, the World Health Organization and the Centers for Disease Control and Prevention (CDC)."
Exactly! None of us are using the Briand analysis in a vacuum as an end-all. We want to embark on debate; the censors want to shut it down. This is part of broader evidence that this virus is not killing massive numbers of people well before their natural time to die.
Professor Neil Ferguson, the father of lockdown policies, suggested earlier this year that two-thirds of the people who would ultimately die in the U.K. would have died within the year anyway. Punctuating this point is a brand-new retrospective study published over the weekend by scientists at Rutgers University showing that 89% of those who died of COVID in two New Jersey hospitals had prior "do not resuscitate" orders. Thus, these are not exactly new excess deaths who died tragically early. The findings harmonize very well with any analysis showing limited excess deaths caused by the virus this year.
Also, much as with masks, some of the evidence we are now seeing on excess deaths tracks very closely with the original consensus – before the virus became a political issue and a tool for social control. On March 26, Dr. Anthony Fauci, along with National Institutes of Health deputy director of clinical research Clifford Lane and CDC Director Robert Redfield, published an article in the New England Journal of Medicine making exactly this point. They predicted that once the true number of asymptomatic and subclinical cases was factored in, "the overall clinical consequences of Covid-19 may ultimately be more akin to those of a severe seasonal influenza (which has a case fatality rate of approximately 0.1%) or a pandemic influenza (similar to those in 1957 and 1968) rather than a disease similar to SARS or MERS, which have had case fatality rates of 9 to 10% and 36%, respectively."
Well, given that the flu has all but disappeared since COVID-19 has become the predominant respiratory virus in circulation, that would mean there would not be a large number of excess deaths, given that this virus is replacing, not augmenting, the flu deaths. Last year, for week 46 of the CDC's Influenza Surveillance Report (ending Nov. 16), there were 1,786 confirmed flu cases. This year, there were just 41. That is a 97.7% decline! Which tells you that for this year, COVID-19 is the Angel of Death's respiratory fatality tool of choice, to the exclusion of the other typical tools.
The only other criticism the editors' retraction notice had of Briand is that her contention that other deaths were reclassified as COVID deaths is wrong because "COVID-19 disproportionately affects those with preexisting conditions, so those with those underlying conditions are statistically more likely to be severely affected and die from the virus." Again, she is discussing excess deaths – meaning people who would otherwise not have died this year. So her point is not just that some deaths have been mislabeled (e.g. motorcycle accidents turning into COVID deaths), but even among those who legitimately did die from the virus, many of them, as the editors' retraction notice is clearly conceding, would have died fairly soon from those other diseases. They are clearly granting the point that, by and large, these people would not have died of heart attacks or the flu 10 years later. These are people who largely would have died within the year. And let's not forget that, thanks to the lockdown policies, many of these people are also dying a few months early because of isolation.
Yes, the CDC's excess death data can be unreliable, and yes, we need more recent months of data to make a better assessment. But rather than engaging in censorship, why are we not debating the merits of both sides? Why does any shred of good news about the virus have to be stifled rather than rebutted or debated?
American media and scientific journals have strong bias against good news
This problem seems to be unique to the U.S., at least to the extreme lengths that the censorship is taken. A brand new working paper published for the National Bureau of Economic Research found that "ninety-one percent of stories by U.S. major media outlets are negative in tone versus fifty four percent for non-U.S. major sources and sixty-five percent for scientific journals." This was found to be true even when logic would dictate there should be more positive stories or studies in circulation.
"The negativity of the U.S. major media is notable even in areas with positive scientific developments including school re-openings and vaccine trials," observed Sacerdote et al. in the working paper. "Media negativity is unresponsive to changing trends in new COVID-19 cases or the political leanings of the audience. U.S. major media readers strongly prefer negative stories about COVID-19, and negative stories in general."
Thus, whenever any study, analysis, or news story surfaces showing that deaths might not be as bad as reported, it is immediately censored. Given that deliberate bias against good news, how are we to fairly evaluate the merits of the data and science? In that sense, the danger to the public is likely more in what is not being published than what is affirmatively being disseminated with pomp and flair across the dark annals of the web.
Nobody made this point better than Kamran Abbasi, executive editor of the British Medical Journal, in a recent editorial in which he accuses scientists and politicians of "suppressing science" for political gain.
"Politicians often claim to follow the science, but that is a misleading oversimplification," charged Abbasi. "Science is rarely absolute. It rarely applies to every setting or every population. It doesn't make sense to slavishly follow science or evidence. A better approach is for politicians, the publicly appointed decision makers, to be informed and guided by science when they decide policy for their public. But even that approach retains public and professional trust only if science is available for scrutiny and free of political interference, and if the system is transparent and not compromised by conflicts of interest."In other words, "shut up and mask up" is not science and certainly does not exude transparency that will give the public confidence in the decision-making process. And as Abassi warns, "When good science is suppressed, people die."