Computational models for enhanced crisis preparedness

The likelihood and impact of complex, compound social crises are expected to grow. Societies must therefore become effective at understanding and preventing crises, and/or mitigating their effects. Crisis models and modelling methods offer a straightforward means to address the challenge of preventing, anticipating, preparing for, reacting to, mitigating, and recovering from crises. These same models can also provide responsible authorities or responder agencies with a virtual experience of a situation prior to its occurrence in the real world.

While crisis models have shown a strong relevance for responding to crises, an array of challenges remains to be addressed for these models to reach their full potential: how to adequately model the richness and adaptiveness of human behavior when facing crises and their extraordinary contexts? What emerging societal behavior may result from such contexts and individual responses? How to explain behaviour and develop reasonable potential trajectories? How to adapt existing modelling practices for such simulations to make them relevant for crisis stakeholders?

This Lorentz workshop brings together a collection of agent-based modelers, social scientists, disaster experts, and policy-makers in an attempt to create better modeling processes and better crisis models. The unique contribution of this workshop consists in bolstering scientific advancements in inter- and trans disciplinary methods, but also in establishing a new research tradition centered on computational models for enhanced crisis preparedness and response.

The workshop will be conducted along 4 scientific themes exemplified by some open questions that the participants will collaboratively address:

1) Trade-off between urgency and accuracy: How can agent-based modeling and simulation contribute to preventing public health crises?

2) Psychological and behavioural realism: How should agents and agent interactions be modeled in ways that generate transparent, explanatory, and predictive behaviour with regard to crisis preparedness and management?

3) Data, evidence and tools: What kind of data is already available to validate and calibrate models of humans in crises and what does the advancement of modeling platforms and computational power have in store for social simulation? 

4) Meaningful interactions with policy makers: How can greater trust between modelers, domain experts, policy-makers, and decision-makers be created that overcomes existing communication barriers and enhances the status of computational social science in crisis planning and management?