Evidence map›Paper›PMID 34991764›Full record

ArticleEpidemiology and infection2022

Use of a non-probabilistic online panel as a control group for case-control studies to investigate food and waterborne outbreaks in Lower Saxony, Germany.

Delphine Perriat, Elke Mertens, Johannes Dreesman

Abstract read
In one paragraph

Article in Epidemiology and infection, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. 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

3 authors.

Delphine PerriatEuropean Programme for Intervention Epidemiology Training (EPIET), European Centre for Disease Control and Prevention (ECDC), Solna, Sweden.ORCID 0000-0001-7498-1700
Elke MertensDepartment for Infectious Disease Epidemiology, Public Health Agency of Lower Saxony, Hannover, Germany.
Johannes DreesmanDepartment for Infectious Disease Epidemiology, Public Health Agency of Lower Saxony, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Established methods of recruiting population controls for case-control studies in infectious disease outbreak investigations are resource- and time-intensive, and are often subject to bias. The online panel have recently gained interest as an easy and timely method to select controls. We examined the feasibility, suitability and reliability of using an online panel to select controls for case-control studies as part of investigations of diffuse food and waterborne outbreaks. In January 2019, we deployed a web survey by email to the 277 members of a non-probabilistic online panel in Lower Saxony, Germany. We questioned them on basic sociodemographic characteristics and eating habits. They were frequency matched to cases on sex and age. Their food exposures were compared to those of traditionally recruited controls of four historical case-controls studies, which successfully investigated food and waterborne outbreaks. We used logistic regressions to assess the association between the food exposures and the disease (odds ratios). The use of a control panel successfully led to the identification of the food items in three of the four historical outbreak investigations, and their recruitment benefitted from increased speed and limited costs. Timely outbreak investigations would enable rapidly implementing control measures. We recommend the further evaluation of using panellists as controls in parallel case-control studies and case-panel studies.

Indexed as

Disease OutbreaksCase-Control StudiesControl GroupsGermanyReproducibility of Resultscase-control studiesEpidemiological study designgastrointestinal infectiononline paneloutbreaks

Identifiers

PMID34991764
PMCPMC8915193

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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.