Dynamic Causal Modeling for the Coronavirus Pandemic

Laura Spinney in The Guardian:

Neuroscientist Karl Friston, of University College London, builds mathematical models of human brain function. Lately, he’s been applying his modelling to Covid-19, and using what he learns to advise Independent Sage, the committee set up as an alternative to the UK government’s official pandemic advice body, the Scientific Advisory Group for Emergencies (Sage).

How well have your predictions been borne out in this first wave of infections?

For London, we predicted that hospital admissions would peak on 5 April, deaths would peak five days later, and critical care unit occupancy would not exceed capacity – meaning the Nightingale hospitals would not be required. We also predicted that improvements would be seen in the capital by 8 May that might allow social distancing measures to be relaxed – which they were in the prime minister’s announcement on 10 May. To date our predictions have been accurate to within a day or two, so there is a predictive validity to our models that the conventional ones lack.

More here.