Fig. 2From: Activity-driven network modeling and control of the spread of two concurrent epidemic strainsIllustrative example of the time evolution of the epidemic spreading process. Evolution of the epidemic in terms of the total infection counts for strain 1 (\(I_1(t)+{\tilde{I}}_1(t)\)) and 2 (\(I_2(t)+{\tilde{I}}_2(t)\)), averaged over 1000 independent Monte Carlo simulations for a different values of \(\lambda _1\) with \(\lambda _2 = 2\lambda _1\) being twice infectious than the first variant. Here \(\lambda _1\) is varied from 0 to 0.2, thus representing cases where both variants are in the non-epidemic regime and transition to an epidemics as \(\lambda _1\) increases. b Re-infection parameter of the second variant \(\rho _{22}\) with \(\rho _{21}=\rho _{22}\) and \(\lambda _1=\lambda _2=0.2\). c \(\lambda _1\) varies between 0 and 0.5, while \(\lambda _2 = 0.5-\lambda _1\). d Number of re-infected individuals varying the cross-strain re-infection probability \(\rho _{12}\) with \(\lambda _1=\lambda _2=0.2\)Back to article page