SPATIAL ANALYSIS AND PERFORMANCE OF COMMUNITY HEALTH WORKERS IN DETECTING LEPROSY IN RISK AREAS IN PARÁ

Abstract

Objective: To evaluate the effectiveness of Community Health Workers (CHWs) in identifying suspected cases of leprosy in risk areas, using spatial analysis as a support tool in the municipality of Santarém, Pará. Methods: A cross-sectional, descriptive, and quantitative study was conducted between June and October 2019. Twenty-four CHWs from Basic Health Units (BHUs) located in low-, medium-, and high-risk areas for leprosy were included, identified through spatial analysis of data from the Notifiable Diseases Information System (SINAN, 2006-2014). The CHWs received training on leprosy and administered suspicion questionnaires during home visits (HV). Data were statistically analyzed and georeferenced in QGIS. Results: 83% of CHWs recognized leprosy as an infectious disease, but only 50% demonstrated knowledge about transmission and contact surveillance. During the HD, 19 suspected cases were identified, 17 with skin lesions and 13 with neurological changes (pain, numbness, tingling). Spatial analysis revealed a heterogeneous distribution of leprosy, with detection rates varying between census sectors, and highlighted the non-strategic location of some CHUs, limiting access for the population. Conclusion: Despite gaps in knowledge about transmission and surveillance, CHWs were effective in detecting suspected cases, reinforcing their role in expanding the capillarity of the health system. Spatial analysis proved essential for identifying priority areas and optimizing resource allocation. Continuous training of CHWs and integration of geospatial techniques into health surveillance strategies for leprosy control in endemic regions are recommended.

DOI: https://doi.org/10.56238/sevened2025.021-035