Han beskriver bl.a. – ret klart – hvorfor kritikken af, at vi ikke medtager modelstudier (som primært blev fremført af epidemiologer), var helt forfejlet. Her er teksten (mine fremhævninger):
Not surprisingly, many epidemiologists took vigorous exception to these results, which are so different from their theoretical models, which were excluded from the analysis. In their view, the Johns Hopkins study cooked the books. In fact, something deeper is at issue.
The scientific method is a proven approach to garnering deeper insights into how the world behaves. It begins with the development of a theory that rests on several assumptions, such as how a disease spreads in the population (e.g., by air or by touch). The theory is then used to derive a prediction, such as the number of COVID deaths avoided. The theoretical models that emerge are typically sophisticated mathematical equations that yield numerical predictions once data are applied to each variable in the model.
The models have to be tested, however. That requires analyzing past data to see whether their predictions were in the ballpark. This is not an easy task since observations, such as the number of COVID deaths, depend on many other factors besides lockdowns and these also need to be included in the analysis. One approach to create more confidence in a theory is to “backdate” models to see if their predictions are close to what actually happened. Set the model up with data that goes to 2010, say, and then see if it “explains” what happened between 2010 and now.
The Johns Hopkins authors were right to include in their meta-analysis only papers that had been tested empirically, not those that had only made theoretical predictions. Whether their conclusion about the effect of mandates is correct only time will tell. Future studies will determine which theories are correct or not. That’s how the scientific method works.