Fig. 4.

Analysis of the monthly impact of inter- and intra-national borders on the EBOV dispersal frequency. The plot depicts the predictive odds ratio (POR) estimates per month and per data set (d = 250, 350 and 450 km). POR estimates for within-country administrative borders are also included as a negative control as we do not expect any significant impact of within-country administrative borders on dispersal frequency. PORs >3 and >20 can be considered as ‘positive’ and ‘strong’ evidence for the impact of borders on the dispersal frequency, and PORs >19 and >99 correspond to posterior predictive p-values <0.05 and <0.01, respectively. Vertical-dashed lines indicate the time at which Sierra Leone, Liberia and Guinea announced their border closures. See Supplementary Fig. 4 for a more detailed representation of the monthly differences in crossing border events between inferred and simulated diffusion processes