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Scientific knowledge and advances are a cornerstone of modern society. Theyimprove our understanding of the world we live in and help us navigate globalchallenges including emerging infectious diseases, climate change and thebiodiversity crisis. For any scientist, whether they work primarily infundamental knowledge generation or in the applied sciences, it is important tounderstand how science fits into a decision-making framework. Decision scienceis a field that aims to pinpoint evidence-based management strategies. Itprovides a framework for scientists to directly impact decisions or tounderstand how their work will fit into a decision process. Decision science ismore than undertaking targeted and relevant scientific research or providingtools to assist policy makers; it is an approach to problem formulation,bringing together mathematical modelling, stakeholder values and logisticalconstraints to support decision making. In this paper we describe decisionscience, its use in different contexts, and highlight current gaps inmethodology and application. The COVID-19 pandemic has thrust mathematicalmodels into the public spotlight, but it is one of innumerable examples inwhich modelling informs decision making. Other examples include models of stormsystems (eg. cyclones, hurricanes) and climate change. Although the decisiontimescale in these examples differs enormously (from hours to decades), theunderlying decision science approach is common across all problems. Bridgingcommunication gaps between different groups is one of the greatest challengesfor scientists. However, by better understanding and engaging with thedecision-making processes, scientists will have greater impact and makestronger contributions to important societal problems.

From climate change to pandemics: decision science can help scientists have impact