Viewing Social Isolation as a Complex Dynamical System

Social isolation is a major public health concern linked to increased risk for both psychiatric and physical health conditions. Yet despite the potential consequences of social isolation, our understanding of its nature and how it emerges and evolves over time remains limited. We propose that social isolation should be understood and analyzed as a complex dynamical system. First, we introduce core principles of dynamical systems theory and describe how they can be applied to better understand social isolation. Second, we formalize a dynamical systems model using differential equations. Third, we present simulations showing how changes in system dynamics may increase or decrease the likelihood of individuals entering a socially isolated state. Finally, we offer an illustrative example of how intensive longitudinal data could be used to identify early warning signs of transitions between healthy and isolated states. Overall, this approach may ultimately help inform personalized interventions capable of detecting early warning signs of social isolation.