期刊
PHYSICAL REVIEW E
卷 94, 期 2, 页码 -出版社
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevE.94.022305
关键词
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资金
- Basic Science Research Program through the National Research Foundation of Korea (NRF) - Ministry of Education [2016R1D1A1B01007774]
- National Research Foundation of Korea [2016R1D1A1B01007774] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
We investigate disease spreading on eight empirical data sets of human contacts (mostly proximity networks recording who is close to whom, at what time). We compare three levels of representations of these data sets: temporal networks, static networks, and a fully connected topology. We notice that the difference between the static and fully connected networks-with respect to time to extinction and average outbreak size-is smaller than between the temporal and static topologies. This suggests that, for these data sets, temporal structures influence disease spreading more than static-network structures. To explain the details in the differences between the representations, we use 32 network measures. This study concurs that long-time temporal structures, like the turnover of nodes and links, are the most important for the spreading dynamics.
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