Unknown

Dataset Information

0

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.

SUBMITTER: Huang C 

PROVIDER: S-EPMC4985757 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

altmetric image

Publications

Insights into the transmission of respiratory infectious diseases through empirical human contact networks.

Huang Chunlin C   Liu Xingwu X   Sun Shiwei S   Li Shuai Cheng SC   Deng Minghua M   He Guangxue G   Zhang Haicang H   Wang Chao C   Zhou Yang Y   Zhao Yanlin Y   Bu Dongbo D  

Scientific reports 20160816


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 diseas  ...[more]

Similar Datasets

| S-EPMC5014053 | biostudies-literature
| S-EPMC8758098 | biostudies-literature
| S-EPMC6613374 | biostudies-literature
| S-EPMC3009790 | biostudies-literature
| S-EPMC5554254 | biostudies-literature
| S-EPMC3839111 | biostudies-literature
| S-EPMC7955065 | biostudies-literature