TY - JOUR T1 - Complex systems models for causal inference in social epidemiology JF - Journal of Epidemiology and Community Health JO - J Epidemiol Community Health DO - 10.1136/jech-2019-213052 SP - jech-2019-213052 AU - Hiba N Kouser AU - Ruby Barnard-Mayers AU - Eleanor Murray Y1 - 2020/11/10 UR - http://jech.bmj.com/content/early/2020/12/09/jech-2019-213052.abstract N2 - Systems models, which by design aim to capture multi-level complexity, are a natural choice of tool for bridging the divide between social epidemiology and causal inference. In this commentary, we discuss the potential uses of complex systems models for improving our understanding of quantitative causal effects in social epidemiology. To put systems models in context, we will describe how this approach could be used to optimise the distribution of COVID-19 response resources to minimise social inequalities during and after the pandemic. ER -