Built environment as interface: a relation-based framework for the intersections between built, biotic, social, and health processes during COVID-19 and beyond

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By broadening disciplinary perspectives to architecture and design, philosophy of science, and systems biology, this paper aims to explore the interconnections between built, social, biotic, and health processes with key attention to the moderating roles of the built environment. The focus is part diagnostic and part prescriptive. Initially, we specify failures in COVID-19 representational infrastructure and practice in accounting for built environment and social process impacts on public health factors. By presenting three intertwined problems with scientific representation in COVID-19 modeling and data-gathering, we examine to what extent current scientific practices fail to robustly account for the complex intersections between built, biotic, social, and health processes. We suggest that resolving the presented problems requires the development of new conceptual precedents for the analysis of causal relations in changing contexts. The second focal point is prescriptive. By discussing conceptual developments that spotlight relations—e.g., ‘context’, ‘nudge’, ‘affordance’, and ‘interface’—we organize the numerous moderating roles of built environment contexts, and we suggest practical applications to ongoing public health practices—such as, cautioning against nudge policies. Ultimately, we argue that the built environment can be represented not only as a single variable (or handful of discrete variables) but also as an interface that reorganizes multiple causal landscapes—concurrently, deregulating factors and leaving others unaffected. Because of the difficulty of representing emergent properties, relevant to differential built environment burden and inequitable health outcomes, we provide ways to visualize the built environment as interface in multidimensional form. We conclude that adequately representing the various moderating roles of the built environment goes a step beyond how to represent complexity, and it requires asking a deeper normative question: who ought to be involved in representing complexity.