The impact of community structure of social contact network on epidemic outbreak and effectiveness of non-pharmaceutical interventions

  • Authors:

  • Youzhong Wang;Daniel Zeng;Zhidong Cao;Yong Wang;Hongbin Song;Xiaolong Zheng

  • Affiliations:

  • The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China and MIS Department, The University of Arizona, Tucson, Arizona;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China;Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China;Institute of Disease Control and Prevention, Academy of Military Medical Sciences, Beijing, China;The Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Sciences, Beijing, China

  • Venue:
  • PAISI'11 Proceedings of the 6th Pacific Asia conference on Intelligence and security informatics
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

The topology structure of social contacts network has a big impact on dynamic patterns of epidemic spreading and effectiveness of nonpharmaceutical interventions. Corresponding to individuals' behavioral or functional units, people are commonly organized in small communities, meaning that most of social contacts networks tend to display community structure property. Through empirical investigation and Monte-Carlo simulation on a big H1N1 outbreak in a Chinese university campus, this paper explores the impact of community structure property of social contacts network on epidemic spreading and effectiveness of interventions. A stochastic model based on social contacts networks among students is constructed to simulate this outbreak, revealing that epidemic outbreaks commonly occur in local community. Moreover, effectiveness of three quarantine-based interventions is quantitatively studied by our proposed model, finding that community structure of social networks determines the effects these measures.