Database and Script -

The use of a flow-based geographic centrality model examines the spatial patterns of patient travel to kidney transplant centers in the state of Paraná, with the objective of identifying territorial inequalities in accessibility; based on these patterns, a spatial optimization model is proposed to explore theoretical scenarios aimed at improving equitable access to transplant services. Geographic centrality was quantified using the Short-Distance Interaction Index (SDII) and the Long-Distance Interaction Index (LDII), where SDII represents the intensity of interactions predominating at short distances, while LDII captures the intensity of interactions associated with longer distances. The SDII and LDII values were subsequently used to compute the Global Geographic Centrality Index (GGCI) and the Local Geographic Centrality Index (LGCI).