Who mixes with whom? A method to determine the contact patterns of adults that may lead to the spread of airborne infections
- PMID: 9263464
- PMCID: PMC1688546
- DOI: 10.1098/rspb.1997.0131
Who mixes with whom? A method to determine the contact patterns of adults that may lead to the spread of airborne infections
Abstract
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.
Similar articles
-
Social contact patterns relevant to the spread of respiratory infectious diseases in Hong Kong.Sci Rep. 2017 Aug 11;7(1):7974. doi: 10.1038/s41598-017-08241-1. Sci Rep. 2017. PMID: 28801623 Free PMC article.
-
A household-based study of contact networks relevant for the spread of infectious diseases in the highlands of Peru.PLoS One. 2015 Mar 3;10(3):e0118457. doi: 10.1371/journal.pone.0118457. eCollection 2015. PLoS One. 2015. PMID: 25734772 Free PMC article.
-
Social contacts and mixing patterns relevant to the spread of infectious diseases.PLoS Med. 2008 Mar 25;5(3):e74. doi: 10.1371/journal.pmed.0050074. PLoS Med. 2008. PMID: 18366252 Free PMC article.
-
Perspective: human contact patterns and the spread of airborne infectious diseases.Trends Microbiol. 1999 Sep;7(9):372-7. doi: 10.1016/s0966-842x(99)01546-2. Trends Microbiol. 1999. PMID: 10470046 Review.
-
Common infectious diseases.Dent Clin North Am. 1996 Apr;40(2):385-93. Dent Clin North Am. 1996. PMID: 8641528 Review.
Cited by
-
Simulating COVID-19 in a university environment.Math Biosci. 2020 Oct;328:108436. doi: 10.1016/j.mbs.2020.108436. Epub 2020 Aug 3. Math Biosci. 2020. PMID: 32758501 Free PMC article.
-
Characterizing the transmission potential of zoonotic infections from minor outbreaks.PLoS Comput Biol. 2015 Apr 10;11(4):e1004154. doi: 10.1371/journal.pcbi.1004154. eCollection 2015 Apr. PLoS Comput Biol. 2015. PMID: 25860289 Free PMC article.
-
Using GIS to create synthetic disease outbreaks.BMC Med Inform Decis Mak. 2007 Feb 14;7:4. doi: 10.1186/1472-6947-7-4. BMC Med Inform Decis Mak. 2007. PMID: 17300714 Free PMC article.
-
Using contact tracing from interlocking diaries to map mood contagion along network chains.Sci Rep. 2022 Mar 1;12(1):3400. doi: 10.1038/s41598-022-07402-1. Sci Rep. 2022. PMID: 35233037 Free PMC article.
-
Modeling seasonal influenza outbreak in a closed college campus: impact of pre-season vaccination, in-season vaccination and holidays/breaks.PLoS One. 2010 Mar 4;5(3):e9548. doi: 10.1371/journal.pone.0009548. PLoS One. 2010. PMID: 20209058 Free PMC article.
References
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Medical