PT  - JOURNAL ARTICLE
AU  - Hiba N Kouser
AU  - Ruby Barnard-Mayers
AU  - Eleanor Murray
TI  - Complex systems models for causal inference in social epidemiology
AID  - 10.1136/jech-2019-213052
DP  - 2020 Nov 10
TA  - Journal of Epidemiology and Community Health
PG  - jech-2019-213052
4099  - http://jech.bmj.com/content/early/2020/12/09/jech-2019-213052.short
4100  - http://jech.bmj.com/content/early/2020/12/09/jech-2019-213052.full
AB  - 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.