Burkina Faso mobility data with some noise

Human mobility is a core component of human behavior and its
quantification is critical for understanding its impact on infectious
disease transmission, traffic forecasting, access to resources and care,
intervention strategies, and migratory flows. When mobility data are
limited, spatial interaction models have been widely used to estimate
human travel, but have not been extensively validated in low- and
middle-income settings. Geographic, sociodemographic, and infrastructure
differences may impact the ability for models to capture these patterns,
particularly in rural settings. Here, we analyzed mobility patterns
inferred from mobile phone data in four Sub-Saharan African countries to
investigate the ability for variants on gravity and radiation models to
estimate travel. Adjusting the gravity model such that parameters were fit
to different trip types, including travel between more or less populated
areas and/or different regions, improved model fit in all four countries.
This suggests that alternative models may be more useful in these settings
and better able to capture the range of mobility patterns observed.