Geospatial Analysis of Child Leprosy Cases and Block-Level Endemicity in Raigad District, Maharashtra (2018-19 to 2023-24)
DOI:
https://doi.org/10.32677/ijch.v11i10.4843Keywords:
GIS, PB Child, MB Child, Grade II disability, Geospatial analysisAbstract
Background: Leprosy remains a public health Problem in few pockets of India, including the Raigad district, where prevalence rate exceeds 1/10000 population and child proportion is notably high. Understanding its spatial distribution is a crucial guide for targeted public health interventions as it reflects the community's ongoing case transmission especially in endemic areas due to possibility of close contact transmission and high exposure levels in community. Aims: The study aimed to analyse the spatial distribution and geographical patterns of child leprosy in Raigad district, Maharashtra to identify high-risk areas. Methods: A retrospective data analysis of 3,927 leprosy cases, including 572 children aged ≤14 years was conducted using open-source GIS software (Version 3.8) from April 2018 to March 2024. Results: Children constituted 12% of the cases, with a child rate of 3.3 per 100,000 population. The spatial analysis identified Karjat and Panvel as hotspots with over 100 new cases annually. Other blocks exhibited varying levels of endemicity with uneven distribution of Child leprosy cases. Kernel density estimation revealed high-density hotspots of PB and MB child leprosy cases in multiple habitats. Conclusion: The study highlights the heterogeneity in the spatial distribution of child leprosy, emphasizing that GIS mapping and spatial analysis can be essential tools for devising targeted strategies to reduce the incidence of child leprosy.
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Copyright (c) 2024 Sunil Vilasrao Gitte, Sunil Nakhate, Suchitra Vishwambhar Surve, Ramji Adkekar, Suparna Khera, Zenab Alihusain Damaniya, Rajaram Gavade
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.