How can data models help us improve decision making in exit strategies?

The decisions shaping our transition to 'the new normal' are made under great uncertainty, on the basis of limited evidence, and while new insights are constantly becoming available. However, these decisions can lead to major interventions in our systems, and we will have to deal with interdependencies that were impossible to foresee. Asking the right questions, choosing the right data, and combining those data in complex models and simulations enable us to make well-informed decisions on our way to the new normal.

The role of, and impact on, mobility on the course of the virus

The COVID-19 pandemic has a profound effect on travel worldwide. The effects range from a dramatic decrease in air travel to an unprecedented share of the workforce who are teleworking. This is caused by both governmental measures such as travel restrictions and the closing-down of whole sectors of the economy), and travellers’ choices to refrain from travelling in order to reduce their exposure to other people and thereby the risk of contamination.

How COVID-19 spreads

Virus spread on networks is scientifically understood. It is a beautiful example of Network Science. The relatively new field of Network Science is based upon the fundamental duality in any complex system: the interplay between “function” (process, service) and “structure” (graph, topology). If the dynamic transmission process and the contact graph are known, then the spread of an item can be computed, the impact of interventions can be assessed and future scenario’s may be predicted.