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To provide a comprehensive view for dynamics of and on many real-worldtemporal networks, we investigate the interplay of temporal connectivitypatterns and spreading phenomena, in terms of the susceptible-infected-removed(SIR) model on the modified activity-driven temporal network (ADTN) withmemory. In particular, we focus on how the epidemic threshold of the SIR modelis affected by the heterogeneity of nodal activities and the memory strength intemporal and static regimes, respectively. While strong ties (memory) betweennodes inhibit the spread of epidemic to be localized, the heterogeneity ofnodal activities enhances it to be globalized initially. Since the epidemicthreshold of the SIR model is very sensitive to the degree distribution ofnodes in static networks, we test the SIR model on the modified ADTNs with thepossible set of the activity exponents and the memory exponents that generatesthe same degree distributions in temporal networks. We also discuss the role ofspatiotemporal scaling properties of the largest cluster and the maximum degreein the epidemic threshold. It is observed that the presence of highly activenodes enables to trigger the initial spread of epidemic in a short period oftime, but it also limits its final spread to the entire network. This impliesthat there is the trade-off between the spreading time of epidemic and itsoutbreak size. Finally, we suggest the phase diagram of the SIR model on ADTNsand the optimal condition for the spread of epidemic under the circumstances.

Impact of temporal connectivity patterns on epidemic process