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Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases
Open accessAbstract
BACKGROUND: Mathematical modelling of infectious diseases transmitted by the respiratory or close-contact route (e.g., pandemic influenza) is increasingly being used to determine the impact of possible interventions. Although mixing patterns are known to be crucial determinants for model outcome, researchers often rely on a priori contact assumptions with little or no empirical basis. We conducted a population-based prospective survey of mixing patterns in eight European countries using a common paper-diary methodology. METHODS AND FINDINGS: 7,290 participants recorded characteristics of 97,904 contacts with different individuals during one day, including age, sex, location, duration, frequency, and occurrence of physical contact. We found that mixing patterns and contact characteristics were remarkably similar across different European countries. Contact patterns were highly assortative with age: schoolchildren and young adults in particular tended to mix with people of the same age. Contacts lasting at least one hour or occurring on a daily basis mostly involved physical contact, while short duration and infrequent contacts tended to be nonphysical. Contacts at home, school, or leisure were more likely to be physical than contacts at the workplace or while travelling. Preliminary modelling indicates that 5- to 19-year-olds are expected to suffer the highest incidence during the initial epidemic phase of an emerging infection transmitted through social contacts measured here when the population is completely susceptible. CONCLUSIONS: To our knowledge, our study provides the first large-scale quantitative approach to contact patterns relevant for infections transmitted by the respiratory or close-contact route, and the results should lead to improved parameterisation of mathematical models used to design control strategies.
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“These younger individuals tend to have more contacts than older age groups 33,34 .”
From Spread of a SARS-CoV-2 variant through Europe in the summer of 2020 (2021) · cites this paper as [33]
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Generalized contact matrices allow integrating socioeconomic variables into epidemic models
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Self-citationHow Physical Proximity Shapes Complex Social Networks
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Incorporating household structure and demography into models of endemic disease
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Endogenous social distancing and its underappreciated impact on the epidemic curve
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Modeling the COVID-19 pandemic: a primer and overview of mathematical epidemiology
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COVICT: an IoT based architecture for COVID-19 detection and contact tracing
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“A contact at high-risk is the one that has a physical contact, at least 15 or more minutes long or that occurs regularly Mossong et al. (2008).”
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An agent-based epidemic model REINA for COVID-19 to identify destructive policiesPreprint
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Self-citationDynamic model of rotavirus transmission and the impact of rotavirus vaccination in Kyrgyzstan
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Varicella zoster virus infection occurs at a relatively young age in the Netherlands
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Self-citation
Metadata
- Authors
- Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G. S., Wallinga, J., Heijne, J., Sadkowska-Todys, M., Rosinska, M., & Edmunds, W. J.
- Affiliations
- Laboratoire National de Santé (LU)
- Hasselt University (BE)
- Health Protection Agency (GB)
- University of Antwerp (BE)
- Bielefeld University (DE)
- Istituto Superiore di Sanità (IT)
- University of Rome Tor Vergata (IT)
- National Institute for Public Health and the Environment (NL)
- Corresponding author
- Mossong, Joël
- ORCID
- Venue
- PLoS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2008-03-25
- Volume
- 5
- Issue
- 3
- Pages
- e74
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- PMC
- PMC2270306
- OpenAlex
- W2159301256
- Cited by
- 2,900
- References
- 38
- Citations by year
- 2026: 143 · 2025: 141 · 2024: 176 · 2023: 167 · 2022: 300 · 2021: 508 · 2020: 350 · 2019: 107 · 2018: 126 · 2017: 96 · 2016: 108 · 2015: 102 · 2014: 119 · 2013: 99 · 2012: 98
- FWCI
- 64.29
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Medicine (publishedVersion, cc-by)
- PubMed Central (publishedVersion, other-oa)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Figshare (submittedVersion, cc-by)
- RePEc: Research Papers in Economics (submittedVersion)
- Cineca Institutional Research Information System (Tor Vergata University) (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Document Server@UHasselt (UHasselt) (submittedVersion, other-oa)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion, other-oa)
- Rivm Repository (Netherlands National Institute for Public Health and the Environment) (submittedVersion)
- Funders
- European Commission (SSP22-CT-2004-502084, 502084)
- Topics
- Health Sciences › Medicine › Epidemiology › Influenza Virus Research Studies
- Physical Sciences › Mathematics › Applied Mathematics › Mathematical and Theoretical Epidemiology and Ecology Models
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Keywords
- social mixing, contact patterns, infectious disease transmission, respiratory transmission, close contact transmission, physical contact, pandemic influenza, elementary school students, young adults
- MeSH terms
- Adolescent, Adult, Aged, Child, Child, Preschool, Cross-Sectional Studies, Europe, Female, Humans, Infant, Male, Middle Aged, Models, Theoretical, Respiratory Tract Infections, Social Support
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