Author: Meredith, Hannah R; Giles, John R; Perez-Saez, Javier; Mande, Théophile; Rinaldo, Andrea; Mutembo, Simon; Kabalo, Elliot N; Makungo, Kabondo; Buckee, Caroline O; Tatem, Andrew J; Metcalf, C Jessica E; Wesolowski, Amy
                    Title: Characterizing human mobility patterns in rural settings of sub-Saharan Africa  Cord-id: uizynn94  Document date: 2021_9_17
                    ID: uizynn94
                    
                    Snippet: 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 im
                    
                    
                    
                     
                    
                    
                    
                    
                        
                            
                                Document: 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.
 
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