Fig. 2
From: Characterizing the dynamics underlying global spread of epidemics
Validating the framework in the WAN-SPT. a, b Schema of the hub-effect and continuous seeding. In this example, the epidemic arrives at population k after population j has imported three infections from the epidemic origin, i.e., \(T_{ij}^3 < T_{ik}^1 < T_{ij}^4\). In the absence of continuous-seeding adjustment, infection trees spawned by the second and subsequent importations in population j are ignored18. c Basic network properties of the WAN-SPT with Hong Kong as the epidemic origin (WAN-SPT-HK). d–f Q–Q plots for the analytical and simulated quantiles of EATs for all 2308 populations in the WAN-SPT-HK across all 100 epidemic scenarios considered in Fig. 1 (i.e., 230,800 Q—Q plots in total). Insets show the corresponding histograms of percent error in expected EAT. d EATs for all 246 populations in Di,1 before (red) and after (blue) adjusting for the hub-effect. e EATs for all 1828 populations in Di,2 before (red) and after (blue) adjusting for continuous-seeding and path reduction; hub-effect has been adjusted for the epidemic origin and all populations in Di,1. f EATs for the remaining 234 populations in Di,3 and Di,4 after adjusting for the hub-effect, continuous seeding and path reduction. Supplementary Figures 3–5 provide analogous results for the WAN-SPT with other major hubs as the epidemic origin
