Geospatial methodology for determining the regional prevalence of hospital-reported childhood intussusception in patients from India

• Published in: Scientific reports Vol. 14; no. 1; p. 6664
• Main Authors: Dixit, Shikha, Das, Manoja Kumar, Ramadugu, Durga Chitra, Arora, Narendra Kumar
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 20.03.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/699; 692/699/1503; 692/700/1720; Children; Developing countries; Epidemiology; Geospatial; GIS; Hospital proximity; Hospitals; Humanities and Social Sciences; Intestinal obstruction; Intussusception; LDCs; Moran’s I; multidisciplinary; Patients; Pediatrics; Science; Science (multidisciplinary); Spatial clustering; Statistical analysis; Surveillance; India; GIS; Spatial clustering; Intussusception; Hospital proximity; Geospatial; Moran’s I; Children; India
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-57187-8

Both developed and developing countries carry a large burden of pediatric intussusception. Sentinel site surveillance-based studies have highlighted the difference in the regional incidence of intussusception. The objectives of this manuscript were to geospatially map the locations of hospital-confirmed childhood intussusception cases reported from sentinel hospitals, identify clustering and dispersion, and reveal the potential causes of the underlying pattern. Geospatial analysis revealed positive clustering patterns, i.e., a Moran’s I of 0.071 at a statistically significant ( p  value < 0.0010) Z score of 16.14 for the intussusception cases across India (cases mapped n = 2221), with 14 hotspots in two states (Kerala = 6 and Tamil Nadu = 8) at the 95% CI. Granular analysis indicated that 67% of the reported cases resided < 50 km from the sentinel hospitals, and the average travel distance to the sentinel hospital from the patient residence was calculated as 47 km (CI 95% min 1 km–max 378 km). Easy access and facility referral preferences were identified as the main causes of the existing clustering pattern of the disease. We recommend designing community-based surveillance studies to improve the understanding of the prevalence and regional epidemiological burden of the disease.