Evidence map›Paper›PMID 33791189›Full record

ArticleCurrent epidemiology reports2020

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

Ellen C Caniglia, Eleanor J Murray

Abstract read
In one paragraph

Article in Current epidemiology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Causal Inference in Clinical Research: A Primer.Journal of periodontal research · 2026
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  13. Evaluating Effects of Multilevel Interventions on Disparity in Health and Healthcare Decisions.Prevention science : the official journal of the Society for Prevention Research · 2024
    Article
  14. Single proxy control.Biometrics · 2024
    Article
  15. Article
  16. Article
  17. Review
  18. WIC benefits and evaluation challenges.Paediatric and perinatal epidemiology · 2022
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ellen C CanigliaDepartment of Population Health, New York University Langone Medical Center.
Eleanor J MurrayDepartment of Epidemiology, Boston University School of Public Health.

Funding

Iron and folic acid supplementation strategies during pregnancy and adverse pregnancy outcomes in Botswana - Resubmission - 1K01HD100222 · NICHD · UNIVERSITY OF PENNSYLVANIA · PI CANIGLIA, ELLEN CHRISTINA · 2020 to 2024
$632k
NICHD NIH HHS K01 HD100222
6 · The paper itself

Abstract

purpose of reviewThe 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

findingsWhile 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.

Indexed as

causal inferencechange scoresdifference in differenceJohn Snow

Identifiers

PMID33791189
PMCPMC8006863

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.