RT Journal Article
SR Electronic
T1 Complex systems models for causal inference in social epidemiology
JF Journal of Epidemiology and Community Health
JO J Epidemiol Community Health
FD BMJ Publishing Group Ltd
SP 702
OP 708
DO 10.1136/jech-2019-213052
VO 75
IS 7
A1 Kouser, Hiba N
A1 Barnard-Mayers, Ruby
A1 Murray, Eleanor
YR 2021
UL http://jech.bmj.com/content/75/7/702.abstract
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.