By Brian Castellani, Professor of Sociology (University of Durham)
20th March 2020 (originally published on the Sociology and Complexity Science Blog)
Of the various things to get clear first is that there is a fuzzy divide between those who think public health models are created to make accurate predictions about the future; while others (myself included) who see them more as learning tools that can help us think better about a topic -- albeit with data forecasting still being incredibly important! And the latter -- that is modelling to learn -- which works even better when 'learning' is done through a participatory and co-production approach. (For more on participatory approaches, see the INVOLVE project.)
However, they do seem rather good at telling us what sorts of public health outcomes might happen and how we might respond to these outcomes and so forth. In other words, they seem better when used as learning tools (albeit as well as forms of cautious prediction). And that is, it seems to me, exactly what a lot of the public health models these past several weeks (circa March 2020) have done: they have challenged a certain way of thinking in the government of focusing on mitigation alone, and probably really helped to put us in the right direction, even if their predictions on mortality and rate of spread are not (or will not be) exact.
(For more on this point, see (1) Computational Modelling of Public Policy: Reflections on Practice; (2) Ideal, Best, and Emerging Practices in Creating Artificial Societies; (3) Using Agent-Based Modelling to Inform Policy – What Could Possibly Go Wrong? See also, the Journal of Artificial Societies and Social Simulation and also, relative to policy, the Centre for the Evaluation of Complexity Across the Nexus.)
I am sure there are other points that my fellow modellers would add. And perhaps they can in the comments section below. But I think, overall, you get the basic points!
So, how do our two key models work and what do they tell us?
Now that we have a good sense of the challenges of modelling (POST 1) and also a good sense of what an effective model of COVID-19 looks like, it is time, finally, to review two of the incredible models getting the most attention. The first is the simulation model by Ferguson and colleagues at Imperial College London; the second is complex network model by Alessandro Vespignani and colleagues at Northeastern University in the States.
This is the focus of my third blog post!