The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Who mixes with whom? A method to determine the contact patterns of adults that may lead to the spread of airborne infections
Open accessAbstract
Although mixing patterns are thought to be important determinants of the spread of airborne infectious diseases, to our knowledge, there have been no attempts to directly quantify them for humans. We report on a preliminary study to identify such mixing patterns. A sample of 92 adults were asked to detail the individuals with whom they had conversed over the period of one, randomly assigned, day. Sixty-five (71%) completed the questionnaire, providing their age, the age of their contacts and the social context in which the contacts took place. The data were analysed using multilevel modelling. The study identified, and allowed the quantification of, contact patterns within this sample that may be of epidemiological significance. For example, the degree of assortativeness of mixing with respect to age was dependent not only on the age of participants but the number of contacts made. Estimates of the relative magnitude of contact rates between different social settings were made, with implications for outbreak potential. Simple questionnaire modifications are suggested which would yield information on the structure and dynamics of social networks and the intensity of contacts. Surveys of this nature may enable the quantification of who acquires infection from whom and from where.
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Cites
Social Network Analysis: Methods and Applications
Wasserman, S., & Faust, K. (1994) · doi:10.1017/cbo9780511815478 · Cited by 17,557
Cited by
Social Contacts and Mixing Patterns Relevant to the Spread of Infectious Diseases
Mossong, J., Hens, N., Jit, M., Beutels, P., Auranen, K., Mikolajczyk, R., Massari, M., Salmaso, S., Tomba, G. S., Wallinga, J., et al. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050074 · Cited by 2,900
“A small number of studies have attempted to directly quantify such contact patterns, but they were conducted in small or nonrepresentative populations [14, [21] [22] [23] [24] [25] .”
BackgroundSelf-citationPrem, K., Liu, Y., Russell, T. W., Kucharski, A. J., Eggo, R. M., Davies, N., Flasche, S., Clifford, S., Pearson, C. A. B., Munday, J. D., et al. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(20)30073-6 · Cited by 2,114
Self-citationDynamics and Control of Diseases in Networks with Community Structure
Salathé, M., & Jones, J. H. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000736 · Cited by 586
Modeling dynamic and network heterogeneities in the spread of sexually transmitted diseases
Eames, K. T. D., & Keeling, M. J. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.202244299 · Cited by 478
Stehlé, J., Voirin, N., Barrat, A., Cattuto, C., Colizza, V., Isella, L., Régis, C., Pinton, J.-F., Khanafer, N., Van den Broeck, W., et al. (2011) · BMC Medicine · doi:10.1186/1741-7015-9-87 · Cited by 369
Metadata
- Authors
- Edmunds, W. J., O'callaghan, C. J., & Nokes, D. J.
- Venue
- Proceedings of the Royal Society of London. Series B: Biological Sciences
- Publisher
- The Royal Society
- Published
- 1997-07-22
- Volume
- 264
- Issue
- 1384
- Pages
- 949-957
- ISSN
- 0080-4649 (ISSN-L)
- 0962-8452
- 1471-2954
- OpenAlex
- W2156158169
- Cited by
- 272
- References
- 1
- FWCI
- 4.39
- Type
- journal article
- Language
- en
- Open access
- green
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- The paper
- Edmunds, W. J., O'callaghan, C. J., & Nokes, D. J. (1997). Who mixes with whom? A method to determine the contact patterns of adults that may lead to the spread of airborne infections. Proceedings of the Royal Society of London. Series B: Biological Sciences. https://doi.org/10.1098/rspb.1997.0131
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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