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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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Sandmann, F., van Leeuwen, E., Bernard-Stoecklin, S., Casado, I., Castilla, J., Domegan, L. M., Gherasim, A., Hooiveld, M., Kislaya, I., Larrauri, A., et al. (2022) · Vaccine · doi:10.1016/j.vaccine.2022.01.015 · Cited by 23
Non-pharmaceutical interventions and COVID-19 vaccination strategies in Senegal: a modelling study
Diarra, M., Kebir, A., Talla, C., Barry, A., Faye, J., Louati, D., Opatowski, L., Diop, M. M., White, L. J., Loucoubar, C., et al. (2022) · BMJ Global Health · doi:10.1136/bmjgh-2021-007236 · Cited by 23
Rahmani, A., Dini, G., Leso, V., Montecucco, A., Vitturi, B. K., Iavicoli, I., & Durando, P. (2022) · La Medicina del Lavoro · doi:10.23749/mdl.v113i2.12724 · Cited by 23
“An extensive search strategy was designed ( Appendix A) in order to retrieve all research articles other respiratory pathogens, SARS-CoV-2 spreads mainly through close human contact, particularly via the droplet/airborne route, and, accordingly, groups that have higher contact intensities are at increased risk of infe…”
Tong, X., Deng, Y. L., Liu, L., Tang, X., Yu, T., Gan, J., Cai, Q., Luo, R., & Xiao, N. (2022) · Seizure · doi:10.1016/j.seizure.2022.04.015 · Cited by 23
van Zandvoort, K., Bobe, M. O., Hassan, A. I., Abdi, M. I., Ahmed, M. S., Soleman, S. M., Warsame, M. Y., Wais, M. A., Diggle, E., McGowan, C. R., et al. (2022) · Epidemics · doi:10.1016/j.epidem.2022.100625 · Cited by 23
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Optimizing agent-based transmission models for infectious diseases
Willem, L., Stijven, S., Tijskens, E., Beutels, P., Hens, N., & Broeckhove, J. (2015) · BMC Bioinformatics · doi:10.1186/s12859-015-0612-2 · Cited by 23
Self-citationCritical Review and Uncertainty Analysis of Factors Influencing Influenza Transmission
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An online spatiotemporal prediction model for dengue fever epidemic in K aohsiung ( T aiwan)
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Contact Heterogeneity and Phylodynamics: How Contact Networks Shape Parasite Evolutionary Trees
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Re–evaluation of the cost–effectiveness and effects of childhood rotavirus vaccination in Norway
Edwards, C. H., de Blasio, B. F., Salamanca, B. V., & Flem, E. (2017) · PLoS ONE · doi:10.1371/journal.pone.0183306 · Cited by 22
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Spatial‐SIR with network structure and behavior: Lockdown rules and the Lucas critique
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Vaccinating children against SARS-CoV-2
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“Q3 [16, 28, 68] Histogram of the frequency of contact between A and B, if A infected B SELECT HISTO(SUM(edge.”
BackgroundInfluentialTrentini, F., Manna, A., Balbo, N., Marziano, V., Guzzetta, G., O’Dell, S., Kummer, A. G., Litvinova, M., Merler, S., Ajelli, M., et al. (2022) · Epidemics · doi:10.1016/j.epidem.2022.100601 · Cited by 23
Validating and Testing an Agent-Based Model for the Spread of COVID-19 in Ireland
Hunter, E., & Kelleher, J. D. (2022) · Algorithms · doi:10.3390/a15080270 · Cited by 22
“As Ireland is not one of the eight countries, we use the data from the Netherlands to estimate the Irish contact rates [27].”
MethodInfluential
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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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