TY - JOUR
T1 - Inferring a district-based hierarchical structure of social contacts from census data
AU - Yu, Zhiwen
AU - LIU, Jiming
AU - Zhu, Xianjun
N1 - Publisher Copyright:
© 2015 Yu et al.
Copyright:
Copyright 2015 Elsevier B.V., All rights reserved.
PY - 2015/2/13
Y1 - 2015/2/13
N2 - Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual's social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.
AB - Researchers have recently paid attention to social contact patterns among individuals due to their useful applications in such areas as epidemic evaluation and control, public health decisions, chronic disease research and social network research. Although some studies have estimated social contact patterns from social networks and surveys, few have considered how to infer the hierarchical structure of social contacts directly from census data. In this paper, we focus on inferring an individual's social contact patterns from detailed census data, and generate various types of social contact patterns such as hierarchical-district-structure-based, cross-district and age-district-based patterns. We evaluate newly generated contact patterns derived from detailed 2011 Hong Kong census data by incorporating them into a model and simulation of the 2009 Hong Kong H1N1 epidemic. We then compare the newly generated social contact patterns with the mixing patterns that are often used in the literature, and draw the following conclusions. First, the generation of social contact patterns based on a hierarchical district structure allows for simulations at different district levels. Second, the newly generated social contact patterns reflect individuals social contacts. Third, the newly generated social contact patterns improve the accuracy of the SEIR-based epidemic model.
UR - http://www.scopus.com/inward/record.url?scp=84923233706&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0118085
DO - 10.1371/journal.pone.0118085
M3 - Article
C2 - 25679787
AN - SCOPUS:84923233706
SN - 1932-6203
VL - 10
JO - PLoS ONE
JF - PLoS ONE
IS - 2
M1 - e0118085
ER -