Today, WSJ published a scathing opinion piece by Dr. Marty Makary from Johns Hopkins University titled “The Flimsy Evidence Behind the CDC’s Push to Vaccinate Children: The agency overcounts Covid hospitalizations and deaths and won’t consider if one shot is sufficient.”
This is by far the most compelling article I have ever read so far on how poor the US government’s effort has been on collecting and understanding data on COVID-19. It is the most compelling because it is focusing on data issues, and not politics. It is the most appalling because it is focusing on data issues, and not politics.
Let me just unpack that just a little:
- The CDC is confusing effect with cause. For example, the CDC counted that there have been 335 child deaths with COVID symptoms. They now think those children died from COVID, and as a result they now argue children should be vaccinated. I honestly cannot believe when I read this. The well-educated CDC officials cannot distinguish the difference between causes and effects? (What have they been taking/drinking/smoking?) Apparently the author could not believe it either. He wrote: “I’ve written hundreds of peer-reviewed medical studies, and I can think of no journal editor who would accept the claim that 335 deaths resulted from a virus without data to indicate if the virus was incidental or causal, and without an analysis of relevant risk factors such as obesity.“
- US hospitals may have the incentives to (or at least have the appearance of to do so) over-reporting COVID cases. As I wrote in an earlier post, the CARE Act gives hospitals 20% more payment if a patient is listed as a COVID patient. Indeed, as the author wrote, “Hospitals routinely test patients being admitted for other complaints even if there’s no reason to suspect they have Covid. An asymptomatic child who tests positive after being injured in a bicycle accident would be counted as a “Covid hospitalization.” But why? The author did not conjecture. But financial incentives are major suspect, to say the least.
- The CDC was deficient in collecting the right kinds of data. The author gave two examples. The first is that early in the pandemic the CDC failed to report the medical conditions of Covid-death patients, and then “It took until March 2021 for the CDC to report that 78% of Covid hospitalizations were among overweight or obese patients.” Again, as I conjectured in my earlier post, the US may have done more harm by locking down the whole society, because most of the population did not need to be kept at home! The other example was that the author argued that the CDC should have collected data on “daily new hospitalizations for Covid sickness” instead of “hospitalization for anyone who tests positive for Covid”.
There are lots of great points in the article, again focusing on data issues. I highly recommend anyone who are serious about using data to guide decision-making read this article, and learn how not to collect and interpret data.