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Updated: Mar 7, 2026

Monitoring Influenza Virus Survival Outside the Host Using Real-Time Cell Analysis
Published on: February 20, 2021
Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza
Jianhua Liu1,2, Hongbo Jiang3, Hao Zhang2
1Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
Abstract:
In the summer of 2014, an influenza A(H3N2) outbreak occurred in Yichang city, Hubei province, China. A retrospective study was conducted to collect and interpret hospital and epidemiological data on it using social network analysis and global sensitivity and uncertainty analyses. Results for degree (χ2=17.6619, P<0.0001) and betweenness(χ2=21.4186, P<0.0001) centrality suggested that the selection of sampling objects were different between traditional epidemiological methods and newer statistical approaches. Clique and network diagrams demonstrated that the outbreak actually consisted of two independent transmission networks. Sensitivity analysis showed that the contact coefficient (k) was the most important factor in the dynamic model. Using uncertainty analysis, we were able to better understand the properties and variations over space and time on the outbreak. We concluded that use of newer approaches were significantly more efficient for managing and controlling infectious diseases outbreaks, as well as saving time and public health resources, and could be widely applied on similar local outbreaks.
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