Figure 1. The mobility patterns extracted from mobile phone data from four countries in Sub-Saharan Africa.

(A–D) Data from four Sub-Saharan African countries were selected to characterize human mobility patterns: Namibia, Kenya, Burkina Faso, and Zambia. Travel between districts (administrative level 2) was estimated via mobile phone data from each country. A basic gravity model was fit to trip data from each country which assumes that the number of trips decreases with distance and increases with population size (E–H). Here, one rural (left panel) and one urban (right panel) destination were selected from each country to show that, while the observed trips (black) from different origins do generally follow the assumptions of the gravity model (red), the gravity model is not fully capturing the observed trip patterns. See Figure 1—figure supplements 1–8 for this comparison made for all districts in each country. (I–L) Comparisons of origin-destination matrices colored by trip proportions estimated by the basic gravity model and the mobile phone data (observed) highlight how the basic gravity model tends to overestimate many trips, particularly those that are off-diagonal (e.g., inter-regional trips). The columns and rows of the OD matrix are ordered by district ID, which were assigned such that districts within the same region (adminstrative level 1) were clustered together. The capital district is indicated by the black arrow on the x- and y-axes. The colors indicate the proportion of an origin’s trips made to each destination (with light blue representing destinations visited infrequently and dark blue representing destinations visited most frequently). (See Supplementary file 1B for the key to the origin and destination numbers and Figure 1—figure supplement 9 for district level maps).

Figure 1—figure supplement 1. Trip estimates as a function of trip distance for all districts in Namibia.

. Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 2. Trip estimates as a function of origin population for all districts in Namibia.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 3. Trip estimates as a function of trip distance for all districts in Kenya.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 4. Trip estimates as a function of origin population for all districts in Kenya.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 5. Trip estimates as a function of trip distance for all districts in Burkina Faso.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 6. Trip estimates as a function of origin population for all districts in Burkina Faso.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 7. Trip estimates as a function of trip distance for all districts in Zambia.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 8. Trip estimates as a function of origin population for all districts in Zambia.

Basic model used power distance kernel. See Supplementary file 1B for key to district numbers and Figure 1—figure supplement 9 for a map.

Figure 1—figure supplement 9. Relevant maps for Namibia, Kenya, Burkina Faso, and Zambia.

(A-D) Administrative level two units are labeled for each country. See Supplementary file 1B for key to match ID number to district name. (E-H). Districts were sorted into urban and rural categories.