A Complexity Lens on the COVID-19 Pandemic
Didier Wernli, Fabrizio Tediosi, Karl Blanchet, Kelley Lee, Chantal Morel, Didier Pittet, Nicolas Levrat, Oran R. Young
Abstract
The most striking feature of the coronavirus disease 2019 (COVID-19) pandemic and associated responses is its social and ecological complexity. Applying a complexity lens can improve our understanding of the current COVID-19 pandemic but how can this best be done? Complexity science is not a unified theory but rather a collection of concepts, theories, and methods that are increasingly influencing a range of scholarly disciplines. Complex systems can be simply defined as “co-evolving multilayer networks.”1 This definition stresses the dynamic nature of causality as well as the emergent and difficult to predict behaviour in networks that can adapt to a changing environment. Based on this definition, we describe key features of the COVID-19 pandemic, draw insights from complexity science about the nature of these features, and understand the implications for effective response and governance. This framework offers a relevant approach for shaping future research on the social ecological impact of the pandemic including comparative measures of resilience of different health systems to future events.