Spatial Discrepancies Between Health and Social Security Reports as Markers of Potential Underreporting of Occupational Injuries in Brazil, 2022–2023
Luiza Maria Parise Morales, Samara Carolina Rodrigues, Roberta Souza Freitas, Cristiano Barreto de Miranda, Klauss K. S. GarciaABSTRACT
Introduction
Occupational injuries remain a major public health problem in Brazil, and underreporting limits the capacity of surveillance systems to support prevention and response. This study aimed to identify spatial discrepancies between health reports and social security reports of occupational injuries in Brazil.
Methods
This cross‐sectional ecological study uses municipality‐level aggregated data for all 5570 Brazilian municipalities. Occupational injury records from health reports (Sinan system) and social security reports (CAT system) were analysed for 2022 and 2023. Spatial distribution was described, and spatial autocorrelation was assessed using global Moran's I and local indicators of spatial association. A municipality‐specific log‐ratio between health reports and social security reports was used to identify relative discrepancies between the two systems.
Results
There were 745,840 injury records from the health sector and 949,466 from the social security sector. Health reports were made in 5466 (98.1%) municipalities, whereas social security reports were present in 4509 (80.9%). A total of 3998 (71.7%) municipalities recorded more health reports than social security reports, whereas 1418 (25.4%) recorded more social security reports than health reports. Low–low log‐ratio clusters, corresponding to areas where social security reports consistently exceeded health reports, were concentrated in the central‐west and southeast regions.
Conclusion
The spatial comparison identified marked territorial discrepancies between health reports and social security reports in Brazil. Clusters where social security reports exceeded health reports may serve as operational markers of potential underreporting in workers’ health surveillance that may help guide geographically targeted surveillance strengthening.