Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pcbi.1005697
Title: Projecting social contact matrices in 152 countries using contact surveys and demographic data
Authors: Prem K. 
Cook A.R. 
Jit M.
Keywords: adult
Article
Asia
child
controlled study
disease transmission
epidemic
Europe
female
groups by age
health survey
home
household
human
low income country
male
middle aged
preschool child
school
social behavior
social distance
social interaction
social network
social structure
workplace
adolescent
aged
biology
Communicable Diseases
demography
family size
global health
infant
newborn
questionnaire
statistical model
transmission
very elderly
young adult
Adolescent
Adult
Aged
Aged, 80 and over
Child
Child, Preschool
Communicable Diseases
Computational Biology
Demography
Europe
Family Characteristics
Global Health
Humans
Infant
Infant, Newborn
Middle Aged
Models, Statistical
Social Behavior
Surveys and Questionnaires
Young Adult
Issue Date: 2017
Citation: Prem K., Cook A.R., Jit M. (2017). Projecting social contact matrices in 152 countries using contact surveys and demographic data. PLoS Computational Biology 13 (9) : e1005697. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pcbi.1005697
Abstract: Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models? realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available. ? 2017 Prem et al.
Source Title: PLoS Computational Biology
URI: https://scholarbank.nus.edu.sg/handle/10635/161891
ISSN: 1553734X
DOI: 10.1371/journal.pcbi.1005697
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