Evidence map›Paper›PMID 31274572›Full record

SynthesisEpidemiology (Cambridge, Mass.)2019

A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.

Thang Hoang, Pietro Coletti, Alessia Melegaro, Jacco Wallinga, Carlos G Grijalva, John W Edmunds, Philippe Beutels, Niel Hens

Abstract readSystematic Review
In one paragraph

Synthesis in Epidemiology (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed, 4 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

117 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  7. Informing quarantine policy for measles control in primary school and daycare settings: insights from a simulation study, Flanders, Belgium.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2026
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57 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

8 authors.

Thang HoangFrom the Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Agoralaan Gebouw D, Diepenbeek, Belgium.
Pietro ColettiFrom the Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Agoralaan Gebouw D, Diepenbeek, Belgium.
Alessia MelegaroCarlo F. Dondena Centre for Research on Social Dynamics and Public Policy, Bocconi University, Milano, Italy.
Jacco WallingaCentre for Infectious Disease Control, National Institute for Public Health, Bilthoven, The Netherlands.
Carlos G GrijalvaDepartment of Health Policy, Vanderbilt University School of Medicine, Nashville, TN.
John W EdmundsDepartment of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Philippe BeutelsCentre for Health Economics Research and Modelling Infectious Diseases, Vaccine and Infectious Disease Institute, University of Antwerp, Antwerp, Belgium.
Niel HensFrom the Interuniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Agoralaan Gebouw D, Diepenbeek, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundResearchers increasingly use social contact data to inform models for infectious disease spread with the aim of guiding effective policies about disease prevention and control. In this article, we undertake a systematic review of the study design, statistical analyses, and outcomes of the many social contact surveys that have been published.

methodsWe systematically searched PubMed and Web of Science for articles regarding social contact surveys. We followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines as closely as possible.

resultsIn total, we identified 64 social contact surveys, with more than 80% of the surveys conducted in high-income countries. Study settings included general population (58%), schools or universities (37%), and health care/conference/research institutes (5%). The largest number of studies did not focus on a specific age group (38%), whereas others focused on adults (32%) or children (19%). Retrospective (45%) and prospective (41%) designs were used most often with 6% using both for comparison purposes. The definition of a contact varied among surveys, e.g., a nonphysical contact may require conversation, close proximity, or both. We identified age, time schedule (e.g., weekday/weekend), and household size as relevant determinants of contact patterns across a large number of studies.

conclusionsWe found that the overall features of the contact patterns were remarkably robust across several countries, and irrespective of the study details. By considering the most common approach in each aspect of design (e.g., sampling schemes, data collection, definition of contact), we could identify recommendations for future contact data surveys that may be used to facilitate comparison between studies.

Indexed as

Contact TracingModels, BiologicalCommunicable Disease ControlCommunicable DiseasesEpidemiologic Research DesignHumans

Identifiers

PMID31274572
PMCPMC6684224

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.