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Social encounter networks: characterizing Great Britain

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Social encounter networks : characterizing Great Britain. / Danon, Leon; Read, Jonathan M.; House, Thomas A.; Vernon, Matthew C.; Keeling, Matt J.

In: Proceedings of the Royal Society B: Biological Sciences, Vol. 280, No. 1765, 20131037, 22.08.2013.

Research output: Contribution to journalJournal article

Harvard

Danon, L, Read, JM, House, TA, Vernon, MC & Keeling, MJ 2013, 'Social encounter networks: characterizing Great Britain', Proceedings of the Royal Society B: Biological Sciences, vol. 280, no. 1765, 20131037. https://doi.org/10.1098/rspb.2013.1037

APA

Danon, L., Read, J. M., House, T. A., Vernon, M. C., & Keeling, M. J. (2013). Social encounter networks: characterizing Great Britain. Proceedings of the Royal Society B: Biological Sciences, 280(1765), [20131037]. https://doi.org/10.1098/rspb.2013.1037

Vancouver

Danon L, Read JM, House TA, Vernon MC, Keeling MJ. Social encounter networks: characterizing Great Britain. Proceedings of the Royal Society B: Biological Sciences. 2013 Aug 22;280(1765). 20131037. https://doi.org/10.1098/rspb.2013.1037

Author

Danon, Leon ; Read, Jonathan M. ; House, Thomas A. ; Vernon, Matthew C. ; Keeling, Matt J. / Social encounter networks : characterizing Great Britain. In: Proceedings of the Royal Society B: Biological Sciences. 2013 ; Vol. 280, No. 1765.

Bibtex

@article{6e364eb0198a4a06b21715f8ce5fd883,
title = "Social encounter networks: characterizing Great Britain",
abstract = "A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact.",
keywords = "social contact, survey, epidemic, infectious disease, network, SPATIAL STRUCTURE, MIXING PATTERNS, DISEASE, INFECTIONS, INFLUENZA, SPREAD, TRANSMISSION, CONTACTS, MODELS, WEB",
author = "Leon Danon and Read, {Jonathan M.} and House, {Thomas A.} and Vernon, {Matthew C.} and Keeling, {Matt J.}",
year = "2013",
month = aug
day = "22",
doi = "10.1098/rspb.2013.1037",
language = "English",
volume = "280",
journal = "Proceedings of the Royal Society B: Biological Sciences",
issn = "0962-8452",
publisher = "Royal Society of Chemistry Publishing",
number = "1765",

}

RIS

TY - JOUR

T1 - Social encounter networks

T2 - characterizing Great Britain

AU - Danon, Leon

AU - Read, Jonathan M.

AU - House, Thomas A.

AU - Vernon, Matthew C.

AU - Keeling, Matt J.

PY - 2013/8/22

Y1 - 2013/8/22

N2 - A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact.

AB - A major goal of infectious disease epidemiology is to understand and predict the spread of infections within human populations, with the intention of better informing decisions regarding control and intervention. However, the development of fully mechanistic models of transmission requires a quantitative understanding of social interactions and collective properties of social networks. We performed a cross-sectional study of the social contacts on given days for more than 5000 respondents in England, Scotland and Wales, through postal and online survey methods. The survey was designed to elicit detailed and previously unreported measures of the immediate social network of participants relevant to infection spread. Here, we describe individual-level contact patterns, focusing on the range of heterogeneity observed and discuss the correlations between contact patterns and other socio-demographic factors. We find that the distribution of the number of contacts approximates a power-law distribution, but postulate that total contact time (which has a shorter-tailed distribution) is more epidemiologically relevant. We observe that children, public-sector and healthcare workers have the highest number of total contact hours and are therefore most likely to catch and transmit infectious disease. Our study also quantifies the transitive connections made between an individual's contacts (or clustering); this is a key structural characteristic of social networks with important implications for disease transmission and control efficacy. Respondents' networks exhibit high levels of clustering, which varies across social settings and increases with duration, frequency of contact and distance from home. Finally, we discuss the implications of these findings for the transmission and control of pathogens spread through close contact.

KW - social contact

KW - survey

KW - epidemic

KW - infectious disease

KW - network

KW - SPATIAL STRUCTURE

KW - MIXING PATTERNS

KW - DISEASE

KW - INFECTIONS

KW - INFLUENZA

KW - SPREAD

KW - TRANSMISSION

KW - CONTACTS

KW - MODELS

KW - WEB

U2 - 10.1098/rspb.2013.1037

DO - 10.1098/rspb.2013.1037

M3 - Journal article

VL - 280

JO - Proceedings of the Royal Society B: Biological Sciences

JF - Proceedings of the Royal Society B: Biological Sciences

SN - 0962-8452

IS - 1765

M1 - 20131037

ER -