TY - JOUR
T1 - Small inter-event times govern epidemic spreading on networks
AU - Masuda, Naoki
AU - Holme, Petter
N1 - Publisher Copyright:
© 2020 American Physical Society.
PY - 2020/5
Y1 - 2020/5
N2 - Many aspects of human and animal interaction, such as the frequency of contacts of an individual, the number of interaction partners, and the time between the contacts of two individuals, are characterized by heavy-tailed distributions. These distributions affect the spreading of, e.g., infectious diseases or rumors, often because of impacts of the right tail of the distributions (i.e., the large values). In this paper we show that when it comes to inter-event time distributions, it is not the tail but the small values that control spreading dynamics. We investigate this effect both analytically and numerically for different versions of the susceptible-infected-recovered model on different types of networks.
AB - Many aspects of human and animal interaction, such as the frequency of contacts of an individual, the number of interaction partners, and the time between the contacts of two individuals, are characterized by heavy-tailed distributions. These distributions affect the spreading of, e.g., infectious diseases or rumors, often because of impacts of the right tail of the distributions (i.e., the large values). In this paper we show that when it comes to inter-event time distributions, it is not the tail but the small values that control spreading dynamics. We investigate this effect both analytically and numerically for different versions of the susceptible-infected-recovered model on different types of networks.
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U2 - 10.1103/PhysRevResearch.2.023163
DO - 10.1103/PhysRevResearch.2.023163
M3 - Article
AN - SCOPUS:85095090638
VL - 2
JO - Physical Review Research
JF - Physical Review Research
SN - 2643-1564
IS - 2
M1 - 023163
ER -