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BMC Infect Dis. 2015 Nov 2;15:494. doi: 10.1186/s12879-015-1237-9.

Social encounter profiles of greater Melbourne residents, by location--a telephone survey.

Author information

1
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia. drolls@unimelb.edu.au.
2
Modelling and Simulation Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. nicholas.geard@unimelb.edu.au.
3
McCaughey VicHealth Community Wellbeing Unit, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. djwarr@unimelb.edu.au.
4
Modelling and Simulation Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. pmnathan@unimelb.edu.au.
5
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia. garrylr@unimelb.edu.au.
6
Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, Australia. pepatt@unimelb.edu.au.
7
Modelling and Simulation Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. jamesm@unimelb.edu.au.
8
School of Mathematics and Statistics, The University of Melbourne, Melbourne, Australia. jamesm@unimelb.edu.au.
9
Modelling and Simulation Unit, Infection and Immunity Theme, Murdoch Childrens Research Institute, Parkville, Australia. jamesm@unimelb.edu.au.
10
Modelling and Simulation Unit, Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. j.mcvernon@unimelb.edu.au.
11
Modelling and Simulation Unit, Infection and Immunity Theme, Murdoch Childrens Research Institute, Parkville, Australia. j.mcvernon@unimelb.edu.au.

Abstract

BACKGROUND:

Models of infectious disease increasingly seek to incorporate heterogeneity of social interactions to more accurately characterise disease spread. We measured attributes of social encounters in two areas of Greater Melbourne, using a telephone survey.

METHODS:

A market research company conducted computer assisted telephone interviews (CATIs) of residents of the Boroondara and Hume local government areas (LGAs), which differ markedly in ethnic composition, age distribution and household socioeconomic status. Survey items included household demographic and socio-economic characteristics, locations visited during the preceding day, and social encounters involving two-way conversation or physical contact. Descriptive summary measures were reported and compared using weight adjusted Wald tests of group means.

RESULTS:

The overall response rate was 37.6%, higher in Boroondara [n = 650, (46%)] than Hume [n = 657 (32%)]. Survey conduct through the CATI format was challenging, with implications for representativeness and data quality. Marked heterogeneity of encounter profiles was observed across age groups and locations. Household settings afforded greatest opportunity for prolonged close contact, particularly between women and children. Young and middle-aged men reported more age-assortative mixing, often with non-household members. Preliminary comparisons between LGAs suggested that mixing occurred in different settings. In addition, gender differences in mixing with household and non-household members, including strangers, were observed by area.

CONCLUSIONS:

Survey administration by CATI was challenging, but rich data were obtained, revealing marked heterogeneity of social behaviour. Marked dissimilarities in patterns of prolonged close mixing were demonstrated by gender. In addition, preliminary observations of between-area differences in socialisation warrant further evaluation.

PMID:
26525046
PMCID:
PMC4631075
DOI:
10.1186/s12879-015-1237-9
[Indexed for MEDLINE]
Free PMC Article

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