John Avlon takes on the medical establishment in video: These unlikely events are still more likely than a blood clot after the J&J vaccine.

All news teams encounter a  universal problem when the issue goes beyond the general competence implied by a modern, liberal education. Avlon’s team has grabbed statistics for a way into the problem. But as I wrote in AstraZeneca, What to Do?,

Statistics needs mechanisms. If peculiarities of cases are not correctly weighted, the statistical  threshold, surpassing chance, could be missed. Mechanisms  focus statistics.

Without the mechanism of these clots, the stats of the video are useless as reassurance. The FDA and CDC are concerned about adverse effects that are buried in noise of the unknown future. With mechanisms, you know what you are looking for. With knowledge of mechanisms, you can rule things out, like future mass casualties.

If you were to time travel back 60 years, to the time of dark ignorance preceding molecular biology,  to a med school class in tropical diseases, the prof might remark, if not in writing,  “Eventually, if an individual receives enough immunizations, the recipient will probably die.”

The current state of knowledge is vastly greater. Nevertheless, it might surprise that it is still  not possible to predict with certainty whether a particular virus, for which the genome is completely known, can reproduce in a particular host. The viral landscape remains shrouded in twilight, with at least the possibility of long term effects that must be ruled out by rigorous investigation. Statistics  by itself does not suffice.

The chance of widespread harm, from a vaccine administered to a mass population, is the nightmare of vaccinology. Here presents a hazard, on a scale Hippocrates could not have imagined, which reminds us of the first principle of bioethics: “First, do no harm.”

News teams cannot be expected to have specialist knowledge. They may rely on individuals who have been misqualified as competent on the issue. What systematic could a news team find useful to plug this gap? It’s worth taking a look at the (Wikipedia) Delphi method. Quoting,

Delphi is based on the principle that forecasts (or decisions) from a structured group of individuals are more accurate than those from unstructured groups.^[6]…

CNN, you might find it fascinating to assemble a group to address John Avlon’s question, and watch them work. Just by watching, you get insights into the structure of knowledge of the field in question.