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During the congress, E-Posters will be accessible to all participants on the congress website 24/7, as well as in the E-poster stations in the congress center.
Preparing your E-Poster
Please review the E-Poster format requirements carefully when preparing your E-Poster. Should your E-Poster not meet the mentioned requirements, it may not be displayed as described above.
E-Poster Submission Deadline
Please prepare and upload your E-Poster no later than March 14, 2026 11.59PM CET. After this date, you will no longer be able to prepare and upload your E-poster and it will not be displayed and accessible on the congress website.
Please follow the instructions below to input your abstract title.
Abstract titles should be brief and reflect the content of the abstract.
Lupus nephritis (LN) is a severe manifestation of systemic lupus erythematosus (SLE), with its incidence and progression potentially influenced by structural socioeconomic inequalities. The Population Renal Health paradigm (Burgos-Calderón, Depine, and Aroca-Martínez, 2021) shifts from individual risk assessment to population and territorial vulnerability analysis by integrating social determinants of health (SDOH). To operationalize this approach, the Population Vulnerability Index (PVI) was developed as a quantitative geospatial tool that measures SDOH across the Colombian Caribbean region, enabling systematic comparison of territorial vulnerability. In parallel, the RENELUP registry collects and georeferences LN cases throughout Colombia. This study cross-references RENELUP data from the city of Barranquilla with PVI scores to examine how SDOH influence disease distribution patterns in this urban setting.
To analyze the spatial distribution of LN cases registered in RENELUP in Barranquilla, Colombia, and their relationship with social vulnerability levels defined by the PVI. A density-based clustering algorithm (DBSCAN, 500m radius) was applied for spatial cluster analysis of LN cases registered in RENELUP in Barranquilla to identify high-concentration hotspots. The PVI was created by integrating 60 variables across nine vulnerability dimensions (economic, cultural, housing, health access, educational, environmental, technological, political, and geographic) using data from official sources such as the national census, quality of life surveys, health ministry records, water quality monitoring systems, victimization risk indices, and meteorological APIs. Social vulnerability distribution was evaluated in city blocks within neighborhoods with the highest case concentrations, categorized by PVI scores as follows: high vulnerability (PVI > 0.7), moderate vulnerability (PVI 0.3-0.7), and low vulnerability (PVI < 0.3).
Spatial analysis identified significant clustering patterns of LN cases in specific urban areas. The 12 neighborhoods with the highest concentration of RENELUP-registered cases exhibited a predominant distribution of high social vulnerability, as indicated by the PVI. In neighborhoods with high LN case concentrations, the vast majority of blocks showed high vulnerability: Las Malvinas (98.3% high vulnerability), Evaristo Sourdis (96.3%), and La Chinita (87.0%). The Kernel density analysis revealed hotspots coinciding with areas of elevated PVI scores, suggesting potential spatial correlation between disease concentration and social vulnerability.
This descriptive spatial analysis revealed a pattern of LN case clustering in neighborhoods with high social vulnerability, as indicated by the PVI. While these preliminary findings suggest that SDOH may influence disease distribution, further statistical analyses are needed to establish significant associations. Nevertheless, the integration of RENELUP clinical data with PVI scores demonstrates the potential of this approach for identifying at-risk populations. Future studies should employ inferential spatial statistics to quantify the relationship between social vulnerability and LN incidence, ultimately guiding evidence-based resource allocation in areas of greater need.
