Publication
Title
A systematic review of social contact surveys to inform transmission models of close-contact infections
Author
Abstract
Background: Researchers 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. Methods: We 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. Results: In 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. Conclusions: We 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.
Language
English
Source (journal)
Epidemiology. - Cambridge, Mass.
Publication
Philadelphia : Lippincott williams & wilkins , 2019
ISSN
1044-3983
DOI
10.1097/EDE.0000000000001047
Volume/pages
30 :5 (2019) , p. 723-736
ISI
000479309600016
Pubmed ID
31274572
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
Translational and Transdisciplinary research in Modeling Infectious Diseases (TransMID).
DECIDE: The impact of DEmographic Changes on Infectious DisEases transmission and control in middle/low income countries
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 10.09.2019
Last edited 02.10.2024
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