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.
- Disease modelling
- Epidemiological methods
- Social epidemiology
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Acknowledgements This project was supported by the NICHD (R21HD098733).
Contributors All authors contributed to the conceptualization and drafting of the manuscript.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient consent for publication Not required.
Provenance and peer review Commissioned; externally peer reviewed.
Data availability statement Data sharing not applicable as no datasets generated and/or analysed for this study.
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