Evidence map›Paper›PMID 29106568›Full record

ArticleInternational journal of epidemiology2018

Spillover effects in epidemiology: parameters, study designs and methodological considerations.

Jade Benjamin-Chung, Benjamin F Arnold, David Berger, Stephen P Luby, Edward Miguel, John M Colford, Alan E Hubbard

Registry-linked trialAbstract read
In one paragraph

Article in International journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05154006 (Promoting Self-efficacy and Social Support to Enable Women to Reduce the Risks of Pelvic Organ Prolapse Related to Heavy Lifting in a Non-randomized Controlled Trial With a 3-arm Parallel Intervention Group Design in Rural Nepal), which is not on this map. Cited by 65 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
65citing 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.

NCT05154006 nacompletednot on this mapstarted 2022, after this paper: background citation

Promoting Self-efficacy and Social Support to Enable Women to Reduce the Risks of Pelvic Organ Prolapse Related to Heavy Lifting in a Non-randomized Controlled Trial With a 3-arm Parallel Intervention Group Design in Rural Nepal

TypeinterventionalSponsorUniversity of BernRan2022 to 2022Enrolled600ConditionsBehavior, Health, Behavior, Maternal, Work Related StressArmsInformation about benefits of the behavior, Instruction on how to perform a behavior, Self-efficacy, Social Support
3 · Its place in the literature

Who cites it

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

  1. Pooled it
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  9. Targeted Antibiotics for Trachoma: A Cluster-Randomized Trial.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2021
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  17. Institutional spillover effects of antimicrobial use on antimicrobial resistance andAntimicrobial stewardship & healthcare epidemiology : ASHE · 2026
    Article
  18. Article
  19. Article
  20. Article

5 more citing papers are in PubMed but not listed here.

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

7 authors.

Jade Benjamin-ChungDivision of Epidemiology, UC Berkeley School of Public Health, 101 Haviland Hall, Berkeley, CA 94720-7358, USA.
Benjamin F ArnoldDivision of Epidemiology, UC Berkeley School of Public Health, 101 Haviland Hall, Berkeley, CA 94720-7358, USA.
David BergerDepartment of Economics, University of California, Berkeley, CA 94720-7358, USA.
Stephen P LubyDivision of Medicine, Stanford University, Stanford, CA 94305, USA.
Edward MiguelDepartment of Economics, University of California, Berkeley, CA 94720-7358, USA.
John M ColfordDivision of Epidemiology, UC Berkeley School of Public Health, 101 Haviland Hall, Berkeley, CA 94720-7358, USA.
Alan E HubbardDivision of Biostatistics, UC Berkeley School of Public Health, 101 Haviland Hall, Berkeley, CA 94720-7358, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Many public health interventions provide benefits that extend beyond their direct recipients and impact people in close physical or social proximity who did not directly receive the intervention themselves. A classic example of this phenomenon is the herd protection provided by many vaccines. If these 'spillover effects' (i.e. 'herd effects') are present in the same direction as the effects on the intended recipients, studies that only estimate direct effects on recipients will likely underestimate the full public health benefits of the intervention. Causal inference assumptions for spillover parameters have been articulated in the vaccine literature, but many studies measuring spillovers of other types of public health interventions have not drawn upon that literature. In conjunction with a systematic review we conducted of spillovers of public health interventions delivered in low- and middle-income countries, we classified the most widely used spillover parameters reported in the empirical literature into a standard notation. General classes of spillover parameters include: cluster-level spillovers; spillovers conditional on treatment or outcome density, distance or the number of treated social network links; and vaccine efficacy parameters related to spillovers. We draw on high quality empirical examples to illustrate each of these parameters. We describe study designs to estimate spillovers and assumptions required to make causal inferences about spillovers. We aim to advance and encourage methods for spillover estimation and reporting by standardizing spillover parameter nomenclature and articulating the causal inference assumptions required to estimate spillovers.

Indexed as

Epidemiologic MethodsPublic HealthResearch DesignDisease Transmission, InfectiousHealth PromotionHumansImmunity, HerdSystematic Reviews as TopicVaccination

Identifiers

PMID29106568
PMCPMC5837695

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

Registered trials

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.