The Wall Street Journal published a piece titled “Shanghai Has Recorded More Than 130,000 Covid Cases—and No Deaths.” Seeing the darkly comic headline, I was excited. Finally, after two years, the WSJ appeared to be calling out the data fraud that was the foundation for this whole sordid experiment in totalitarian virus mitigation, however belatedly.
Alas, my excitement was premature. As it turns out, the authors of the article tie themselves into knots to explain China’s data. They even trot out Ryan Tibshirani, co-leader of Carnegie Mellon’s COVID-19 modeling team, to tell us that China’s death rate “can also be affected by factors like the age distribution and racial makeup of its population, vaccination status, type of vaccine and average distance to a healthcare facility,” the implication being that Prof. Tibshirani sees nothing wrong with China’s data, thank you very much.
Apparently, China’s low vaccination rate among its elderly population means they can have 130,000 cases and zero deaths. Make it make sense. “Science!”
I guess Mr. Tibshirani sees this as the more likely explanation than that the world’s most dishonest regime is simply lying. Unfortunately, he’s far from alone in his backhanded advocacy for the integrity of the Chinese Communist Party.
For two years, the elite journalists, scientists, politicians, and health officials who speak for our most prestigious institutions have been conspicuously and vehemently deferential to the integrity of China’s Covid data. Here’s what the New York Times’ David Leonhardt wrote just two months ago:
Well, now, in Shanghai, we have a “big outbreak” which the CCP has not covered up—but the death data coming out is still manifestly fraudulent. Would the New York Times care to revisit their conclusion that “the country’s official Covid counts have been at least close to accurate…because big outbreaks are hard to cover up”?
Perhaps it shouldn’t come as a surprise that these elites want, so badly, for China’s Covid data to be real, because for two years they’ve been imploring their citizens to emulate China, scoffing at our childish attachment to human rights and civil liberties.
Here’s Rochelle Walensky, shortly before assuming office as Director of the US CDC:
And here’s former Surgeon General Jerome Adams just two months ago:
Something tells me these leaders might take a different view on the quality of China’s data if it was their own lives—or the lives of their own children—that depended on it. But they’ve shown no qualms in staking the lives of millions of their fellow citizens on the quality of this graph.
By demanding western elites conform to a false reality in which they had to pretend China’s data was real, the CCP forced them into a referendum as to whom they were truly loyal—China, or their own people. In the vast majority of cases, they chose China. And two years on, even amid the horrific spectacle of China’s lockdown of Shanghai, they remain too cowardly and morally vacuous to reconsider their choice.
Even among lockdown skeptics, many can’t accept that public health officials could possibly be that incompetent. It all seems too dumb, too banal. But since March 2020, every single pandemic policy—from the strict lockdownsand masks to the tests, death coding, and vaccine passes—has been imported from China based on the idea that these “extreme social-control measures” had effectively allowed China to “control the virus.”
In an Orwellian “war on COVID misinformation,” those who pointed out that China’s data was obviously fake were vilified by their own governments as alt-right racists, neo-Nazis, and anti-vaxxers—even if fully-vaccinated. They were censored, professionally ostracized, and, as I experienced firsthand, had their social media accounts purged. Hundreds of millions were thrown into poverty, millions of small businesses were bankrupted, an entire generation of children was forced to isolate and cover their faces, and billions of life years were lost, all in service to the collective fantasy encapsulated by this graph.
Published under a Creative Commons Attribution 4.0 International License
For reprints, please set the canonical link back to the original Brownstone Institute Article and Author.