Fig. 2

Maps, graphs, and scatter plots for Factor 4 in the 4th wave, Factor 4 in the 5th wave, Factor 10 in the 6th wave, and Factor 7 in the 7th wave. The left figures in items A, B, C and D are maps plotting the factor loadings for each mesh for Factor 4 in the 4th wave, Factor 4 in the 5th wave, Factor 10 in the 6th wave, and Factor 7 in the 7th wave. For each factor, the factor loadings represent the strength of involvement in the incoming population. In other words, the influx to meshes with high positive factor loadings is suggested to be greater than that to other meshes. Note that the colour bars are reversed for Factor 4 in the 4th wave and Factor 10 in the 6th wave. The middle figures in items A, B, C and D are graphs that show the time series fluctuations of the effective reproduction number in the 23 wards of Tokyo over the periods of the 4th, 5th, 6th and 7th waves and the composite loading for Factor 4 in the 4th wave, Factor 4 in the 5th wave, Factor 10 in the 6th wave, and Factor 7 in the 7th wave. The right figures in items A, B, C and D are scatter diagrams plotting the effective reproduction number of the 23 wards of Tokyo in the 4th, 5th, 6th and 7th waves and the composite loading for Factor 4 in the 4th wave, Factor 4 in the 5th wave, Factor 10 in the 6th wave, and Factor 7 in the 7th wave. r and p are the correlation coefficient and p value, respectively, between the effective reproduction number and the composite loading. Each value of p is less than 0.05; thus, their correlations are assumed to be significant. These maps are created using the Python library ‘Plotly’ version 5.9.0 (https://plotly.com/). The base map is from OpenStreetMap (https://www.openstreetmap.org/), which is available under the Open Data Commons Open Database Licence. The map style is from CARTO (https://carto.com/), which is available under the Creative Commons Attribution 4.0 Licence.