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Difference-in-Difference in the Time of Cholera: a Gentle Introduction for Epidemiologists

  • Epidemiologic Methods (P Howards, Section Editor)
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Abstract

Purpose of Review

The goal of this article is to provide an introduction to the intuition behind the difference-in-difference method for epidemiologists. We focus on the theoretical aspects of this tool, including the types of questions for which difference-in-difference is appropriate, and what assumptions must hold for the results to be causally interpretable.

Recent Findings

While currently under-utilized in epidemiologic research, the difference-in-difference method is a useful tool to examine effects of population level exposures, but relies on strong assumptions.

Summary

We use the famous example of John Snow’s investigation of the cause of cholera mortality in London to illustrate the difference-in-difference approach and corresponding assumptions. We conclude by arguing that this method deserves a second look from epidemiologists interested in asking causal questions about the impact of a population level exposure change on a population level outcome for the group that experienced the change.

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Notes

  1. John Snow provides population counts for 1851, and population estimates for 1849, but no population estimates for 1854. Therefore, we have used the 1851 data for both time points.

References

Papers of particular interest, published recently, have been highlighted as: • Of importance

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Acknowledgments

We thank Dr. Noah Haber & Dr. Samrachana Adhikari for thoughtful comments on an earlier draft of this manuscript. Any remaining errors are our own. EC was supported by NIH/NICHD K01 HD100222-01A1.

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Correspondence to Eleanor J. Murray.

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Caniglia, E.C., Murray, E.J. Difference-in-Difference in the Time of Cholera: a Gentle Introduction for Epidemiologists. Curr Epidemiol Rep 7, 203–211 (2020). https://doi.org/10.1007/s40471-020-00245-2

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