Fig. 4

The figure shows simulated characteristics and population plots from 1000 runs of the ABM for the best-fit parameters on each network for the US. The bars in the first row represent the MSE value (sum of S and Q) of ABM with the validation data, the bars in the second row show the crossover point, and the third row shows the mean population plot with a 95% CI. The green crosses on the second row on the x-axis represent the actual crossover point in the empirical data. The black bars show the number of times the S and Q curves did not cross each other. The third row shows the mean simulated population curves over time for smokers (S) and quitters (Q) from 1000 runs, with the shaded areas indicating the \(95\%\) CI. The lines with the marker \(+\) indicate the actual historical prevalence data. The grey dotted line, dividing the plot indicates the time-step till which the model was calibrated. Amongst the six networks, we see that the ABM on the FHS network reproduces the data most accurately (MSE mean = 0.01048, SD = 0.00053). The LFR (MSE mean = 0.01102, SD = 0.00091), BA (MSE mean = 0.0114, SD = 0.0013) and SW (MSE mean = 0.01151, SD = 0.0007) are again very similar to each other in terms how good it replicates the data. The ER network (MSE mean = 0.0124, SD = 0.00175) closely follows all the networks except FC. While the ABM on FC network provides the worst fit for the validation data FC (MSE mean = 0.01878, SD = 0.00622)