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What can transport models learn from COVID-19?

Transport modelling can progress, if we are willing to learn from how models are used, perceived, presented and improved in managing the COVID pandemic

Tom van Vuren
08 April 2020

The reliance on models by governments around the world to inform their public health response to the COVID pandemic shows why modelling is important in a time of crisis, accepting that there is uncertainty in the model form, parameters and inputs.

And when trying to understand appropriate actions, there is even value in alternative models that may disagree between them how bad things could become and how tough the response needs to be. It is frustrating that in many of the media headlines this has been misinterpreted and has been presented as discrediting of modelling (Coronavirus exposes the problems and pitfalls of modelling, Guardian 26 March 2020; How can coronavirus models get it so wrong, Guardian 8 April 2020).  

What to do? To increase the acceptance of models, model results, and actions based on them, they first must become more accessible, in terms of a) theory, b) input assumptions and c) code.

Read Tom's latest article on The C-Word...modelling the counterfactual here

The problem with models is that they are generally complex (transport models certainly are!) and in the wrong hands they (intentionally or accidentally) will do more damage than good. We have struggled with this problem of access to transport models for decades, not just because of their complexity but also because they generally rely on commercial software packages that are out of reach of individuals.

Whenever there are winners and losers (as is the case in the COVID situation, and often also in transport policy and investment), it is easiest to attack the models (as the actual outcomes of the decisions will only be seen in a long time, when it is too late to change course). A healthy debate is good, though, and peer review, sensitivity testing and triangulation are good practice. Cherry-picking results definitely isn’t. We should also encourage models to be updated when new insights become available; and not present that as a failure.

Transport modelling can progress, if we are willing to learn from how models are used, perceived, presented and improved in managing the COVID pandemic. Communication has emerged as being critical. Resilience to criticism as well.

I have even seen new models emerge that simulate the spread of congestion using mechanisms borrowed from infectious disease modelling). Modelling World 2020 has been postponed till October – and I hope to see many of you there if social distancing restrictions are lifted by then. Until then, and over the next few months, Landor LINKS will publish short transport modelling pieces, to share emerging good practice, to network virtually and stimulate debate as has been the intention of the conference.

You can access our recent data and modelling stories online.

Please engage. And if you would like to contribute, please contact Juliana O’Rourke


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