Spatial characterization of the targeting's worst-off au Burkina Faso. (13th November 2019) - Bonnet, E; Nikiéma, A; Roy, F A; Ridde, V
Abstract: Introduction: In 2014, the Government of Burkina Faso received technical and financial support from the World Bank to test the PBF project with various equity measures. Health equity measures included community based selection of worst-off and user fee exemption for them at the point of service. This selection was carried out in 8 health districts. More than 110, 000 worst-off have been selected. Several analyses show that their use of care remains low. Our study aims to characterize the selection of the indigent by considering geographical determinants in order to better understand the weakness of access to care. Methods: We have mapped the selection of the indigent based on the geolocation data collected with a GIS. We carried out spatial analyses to measure access to localities, health center and the main access roads. We have also integrated population data and geo-environmental characteristics. All these data were aggregated in 500 m cells to provide all variables on a single scale. A total of 9 variables were generated to characterize the spatial targeting's worst-of. We combined two cluster analyses, i.e., k-means, and hierarchical clustering. Results: We obtain a characterization of the selection into four classes. These classes highlight that the community-based selection of the worst-off is unequal in terms of distances to localities, health centres, and isolation. The results refine our knowledge of geographical accessibility to health centres by illustrating that distances to the health care centre are not the only geographical determinants to be considered. Conclusions: This study is a contribution to the analysis of the characterization of the targeting of the worst-off. The results suggest that it is important to strengthen support for the most isolated worst-off for an access care. More broadly, this study shows that it is necessary to integrate the geographical dimension into the definition of targeting the worst-off. Key messages: It is necessary to integrate the geographical dimension into the definition of targeting the worst-off. It is important to strengthen support for the most isolated worst-off for an access care.