title: Insights into the transmission of respiratory infectious diseases through empirical human contact networks.
abstract: In this study, we present representative human contact networks among Chinese college students. Unlike schools in the US, human contacts within Chinese colleges are extremely clustered, partly due to the highly organized lifestyle of Chinese college students. Simulations of influenza spreading across real contact networks are in good accordance with real influenza records; however, epidemic simulations across idealized scale-free or small-world networks show considerable overestimation of disease prevalence, thus challenging the widely-applied idealized human contact models in epidemiology. Furthermore, the special contact pattern within Chinese colleges results in disease spreading patterns distinct from those of the US schools. Remarkably, class cancelation, though simple, shows a mitigating power equal to quarantine/vaccination applied on ~25% of college students, which quantitatively explains its success in Chinese colleges during the SARS period. Our findings greatly facilitate reliable prediction of epidemic prevalence, and thus should help establishing effective strategies for respiratory infectious diseases control.
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Chunlin
authors.initials: C
authors.lastname: Huang
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
authors.forename: Xingwu
authors.initials: X
authors.lastname: Liu
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
authors.forename: Shiwei
authors.initials: S
authors.lastname: Sun
authors.affiliation: City University of Hong Kong, China.
authors.forename: Shuai Cheng
authors.initials: SC
authors.lastname: Li
authors.affiliation: School of Mathematical Sciences, Center of Quantitative Biology, Center of Statistical Sciences, Peking University, Beijing, China.
authors.forename: Minghua
authors.initials: M
authors.lastname: Deng
authors.affiliation: Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Guangxue
authors.initials: G
authors.lastname: He
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Haicang
authors.initials: H
authors.lastname: Zhang
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|University of Chinese Academy of Sciences, Beijing, China.
authors.forename: Chao
authors.initials: C
authors.lastname: Wang
authors.affiliation: Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Zhou
authors.affiliation: Chinese Center for Disease Control and Prevention, Beijing, China.
authors.forename: Yanlin
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|State Key Laboratory of Theoretical Physics, Chinese Academy of Sciences, Beijing, China.
authors.forename: Dongbo
authors.initials: D
authors.lastname: Bu
mesh_terms: D002681:China; D003140:Communicable Disease Control / Q000379:methods*; D018562:Disease Transmission, Infectious; D006801:Humans; D012141:Respiratory Tract Infections / Q000517:prevention & control / Q000635:transmission*; D013334:Students