Fig. 3
From: Improving tobacco social contagion models using agent-based simulations on networks
The figure shows simulated characteristics and population plots from 1000 runs of the ABM for the best-fit parameters on each network for the UK. The bars in the first row represent the MSE value (sum of S and Q) of the ABM with the validation data, the bars in the second row show the crossover point between the smoker and quitter populations, and the third row shows the mean population value with a 95% confidence interval (CI) around the curve, obtained from 1000 simulation runs. The green crosseson 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 do 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. Among the six networks, we see that ER (MSE mean = 0.01984, SD = 0.00069) and the FHS (MSE mean = 0.01998, SD = 0.00071) network reproduces the data most accurately. The BA (MSE mean = 0.02076, SD = 0.00104), SW (MSE mean = 0.02081, SD = 0.00135) and LFR (MSE mean = 0.02082, SD = 0.00114) are very similar to each other in terms how good they replicate the data. While the ABM on FC network (MSE mean = 0.02617, SD = 0.00226) provides the worst fit for the validation data