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Projecting social contact matrices in 152 countries using contact surveys and demographic data
by
Jit, Mark
, Prem, Kiesha
, Cook, Alex R.
in
Adolescent
/ Adult
/ Age
/ Aged
/ Aged, 80 and over
/ Bayesian analysis
/ Child
/ Child, Preschool
/ Communicable Diseases - epidemiology
/ Communicable Diseases - transmission
/ Computational Biology
/ Computer simulation
/ Demographics
/ Demography
/ Diaries
/ Disease transmission
/ Dynamic models
/ Epidemics
/ Epidemiology
/ Europe - epidemiology
/ Family Characteristics
/ Global Health
/ Households
/ Humans
/ Infant
/ Infant, Newborn
/ Infectious diseases
/ Markov chains
/ Mathematical models
/ Medicine and Health Sciences
/ Middle Aged
/ Models, Statistical
/ Monte Carlo method
/ Monte Carlo methods
/ Monte Carlo simulation
/ Pandemics
/ Pathogens
/ People and places
/ Polls & surveys
/ Public health
/ Simulation
/ Social Behavior
/ Social conditions
/ Social distancing
/ Social networks
/ Social research
/ Social Sciences
/ Social structure
/ Surveys
/ Surveys and Questionnaires
/ Swine flu
/ Young Adult
2017
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Projecting social contact matrices in 152 countries using contact surveys and demographic data
by
Jit, Mark
, Prem, Kiesha
, Cook, Alex R.
in
Adolescent
/ Adult
/ Age
/ Aged
/ Aged, 80 and over
/ Bayesian analysis
/ Child
/ Child, Preschool
/ Communicable Diseases - epidemiology
/ Communicable Diseases - transmission
/ Computational Biology
/ Computer simulation
/ Demographics
/ Demography
/ Diaries
/ Disease transmission
/ Dynamic models
/ Epidemics
/ Epidemiology
/ Europe - epidemiology
/ Family Characteristics
/ Global Health
/ Households
/ Humans
/ Infant
/ Infant, Newborn
/ Infectious diseases
/ Markov chains
/ Mathematical models
/ Medicine and Health Sciences
/ Middle Aged
/ Models, Statistical
/ Monte Carlo method
/ Monte Carlo methods
/ Monte Carlo simulation
/ Pandemics
/ Pathogens
/ People and places
/ Polls & surveys
/ Public health
/ Simulation
/ Social Behavior
/ Social conditions
/ Social distancing
/ Social networks
/ Social research
/ Social Sciences
/ Social structure
/ Surveys
/ Surveys and Questionnaires
/ Swine flu
/ Young Adult
2017
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Do you wish to request the book?
Projecting social contact matrices in 152 countries using contact surveys and demographic data
by
Jit, Mark
, Prem, Kiesha
, Cook, Alex R.
in
Adolescent
/ Adult
/ Age
/ Aged
/ Aged, 80 and over
/ Bayesian analysis
/ Child
/ Child, Preschool
/ Communicable Diseases - epidemiology
/ Communicable Diseases - transmission
/ Computational Biology
/ Computer simulation
/ Demographics
/ Demography
/ Diaries
/ Disease transmission
/ Dynamic models
/ Epidemics
/ Epidemiology
/ Europe - epidemiology
/ Family Characteristics
/ Global Health
/ Households
/ Humans
/ Infant
/ Infant, Newborn
/ Infectious diseases
/ Markov chains
/ Mathematical models
/ Medicine and Health Sciences
/ Middle Aged
/ Models, Statistical
/ Monte Carlo method
/ Monte Carlo methods
/ Monte Carlo simulation
/ Pandemics
/ Pathogens
/ People and places
/ Polls & surveys
/ Public health
/ Simulation
/ Social Behavior
/ Social conditions
/ Social distancing
/ Social networks
/ Social research
/ Social Sciences
/ Social structure
/ Surveys
/ Surveys and Questionnaires
/ Swine flu
/ Young Adult
2017
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Projecting social contact matrices in 152 countries using contact surveys and demographic data
Journal Article
Projecting social contact matrices in 152 countries using contact surveys and demographic data
2017
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Overview
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.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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