Interdisciplinary Communication and Advice under Uncertainty in a Pandemic

Communication in a pandemic is difficult and complex. It is characterized by volatile situations associated with a high degree of uncertainty and, in some cases, social divergence in groups and societies. Orientation is expected, by politicians and individuals, from science. However, sciences are only fulfilling the expectations to a limited extent. We demonstrate that there are severe weaknesses in holistic and interdisciplinary communication in the pandemic and show that established tools from management are neglected and overlooked.We then analyze the specific needs of scientific reasoning in pandemic situations such as •a rational approach integrating both estimates and explicit evidence;•expressing and quantifying uncertainty; •considering interdisciplinary aspects in advice and decision making;•the ability to deal with ethical aspects;•simple updates with new findings and evidence.In a third step we compare from literature and own experience existing methods from management science for their suitability against those needs. We find that many of the interdisciplinary tools are deterministic, like Multi Criteria Analyses, and do not support uncertainty. The frequently adopted linear computation of utility values leads to ethical issues. Foresight methods like Delphi or Scenario methods deal with uncertainty and subjectivity. But they are not designed to integrate strong evidence. Strategic planning tools like roadmaps are comprehensible but disappoint in volatile situations. Probabilistic decision making with expected utilities is too complex and suffers from missing data. Heuristics at the other hand are simple but do not allow for comprehensive reasoning. We then argue in a fourth step to use probability in communication and to apply it to decision making in the pandemic. We propose a simple one-step method with a calculus based on Bayes’ theorem and calculate the probabilities of alternative courses of action being the best un der given conditios. With examples we show how arguments from various scientific disciplines can be integrated in decision making and adjusted as new evidence appears. Furthermore, we provide a role model and show by examples how scientists, scientific consultants and decision makers can cooperate and communicate using the method.We conclude that the method fulfils the identified needs to a high degree and is worth to be further developed. We show its epistemic and scientific limitations and give an outlook how likelihood functions may be used to replace negotiated likelihoods by parametric and model based values.