Chronic Kidney Disease of unknown etiology (CKDu) poses a major public health challenge in Northern Yobe State, Nigeria, particularly in settings characterized by limited geocoded health records and weak disease surveillance systems. In such data-poor contexts, alternative methodological approaches are required to understand disease distribution and guide etiological investigations. This study demonstrates how CKDu spatial prevalence can be examined using a community-centric, GIS-based approach that relies on surveys of diagnosed CKD cases within victim households in a CKDu-endemic region of Yobe, integrating participatory data collection with open-source geospatial tools. Household-level data were collected through electronically administered questionnaires deployed via the KoboToolbox platform, supported by community leaders and implemented through snowball sampling over a 28-day period. Spatial
analyses, including hexagonal grid-based tessellation, hotspot mapping, kernel density analysis, and spatial autocorrelation, were employed to visualize and quantify disease clustering. CKD incidence counts were aggregated within a uniform hexagonal grid, and spatial variability was classified using standard deviation–based incidence density categories to identify statistically meaningful concentration patterns across the study area. The analysis identified three distinct hotspots categorized by disease incidence density levels: high (7–10 cases), medium (3–6 cases), and low (1–2 cases). Spatial statistics derived from Moran’s I index yielded a value of 0.1046, with a z-score of 4.95 and a p-value of 0.000001, indicating a less than 1% probability that the observed clustering of CKD incidences occurred randomly. Overall, the findings demonstrate that CKDu occurrence in Northern Yobe State is spatially non-random and can be effectively characterized through GIS-based, community-centric approaches in data constrained regions. Thus, by generating spatially explicit evidence from diagnosed household cases, this methodology provides a robust foundation for targeted exploration of environmental risk factors and supports informed public health surveillance, environmental management, and policy interventions aimed at uncovering the aetiology
of heightened CKDu prevalence in Northern Nigeria.