In broad terms, this new emerging field aims at developing mathematics to support rational decision making. On the one hand, the EF focuses on optimal approaches to generate consensus statements, for example in “decision theatres” composed either of experts or laymen. On the other hand, the emerging field focuses on mathematical topics that are relevant to situations in which rational decision support in response to an emerging crisis, such as public health treats (e.g. pandemics), is required.
The SARS-2 epidemic painfully taught us that the required mathematical expertise needs to be in place before a crisis hits. Characteristic to emerging crises is the fact that decisions need to be made while data and knowledge is incomplete, i.e. under uncertainty.
Idiosyncratic to emerging crisis is the fact that while comprehensive data-integration and explainability strengthen the trustworthiness and impact of any mathematically-derived decision support, at the same time, relevant data and -models are only being derived as the situation unfolds. This setting requires uncertainty quantification and -communication, as well as robust decision support in the light of these shortcomings. Ideally, the decision support can be adjusted with new incoming data, as a crisis unfolds.
The EF aims to develop mathematical results that interface between data-science, data integration, uncertainty quantification, analysis & control. Central research questions evolve around:
Scientists in Charge: Max von Kleist, Claudia Schillings