As a member of Sage, I support public scrutiny of our scientific advice. However, once our models enter the public domain they are interpreted in many different ways and some of the crucial context can be lost.
Modelling is an important tool for epidemic management, one that has been tested against numerous infectious disease outbreaks and continues to be improved. If we knew what the future held, decisions would be easy — but we don’t know what will happen. The alternative to using models is to guess. Models mean that the assumptions and data used are clear. It’s repeatable science. Guessing is not repeatable and relies on prejudices and wishful thinking, and changes from day to day. Nobody wants government policy to be based on guessing.
The critical problem for decision-making is that the future is unpredictable — models cannot predict numbers accurately. This is mostly because of behaviour that is often completely unpredictable. Back in June this year, we were working out what the number of admissions today would be. The answer depended on what we did between then and now, both individually and collectively and what decisions the government made — all still in the future at that point. Had England been knocked out of the Euros early then we might not have seen the same rates of increase in July. And the ‘pingdemic’ might not have happened.
But what we can do is to use models to construct scenarios — ‘what ifs’ — that can be used by governments to inform their decisions. If Plan B was to be introduced, and reduced transmission, then hospital admissions will likely go lower than otherwise, but models cannot predict exactly how much lower because it depends on booster shots, variants, weather and, most importantly, behaviour. Government has to balance the harms of transmission with the harms of restrictions.