Spatial Analysis of COVID-19 Case Clusters and Vaccination Gaps in Sri Lanka: A Spatial Review of COVID-19 Trends in Colombo District, Sri Lanka
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Abstract
This review examines how spatial analysis techniques have been applied globally and locally to understand COVID-19 transmission and vaccine accessibility, with a focus on the Colombo District of Sri Lanka. The COVID-19 pandemic revealed critical vulnerabilities in public health systems, particularly in densely populated urban regions. This review examines the role of spatial analysis in understanding and addressing COVID-19 transmission and vaccination accessibility in Sri Lanka, with a specific focus on the Colombo District. Drawing on global and national literature, the study explores how Geographic Information Systems (GIS), spatial statistics, and remote sensing were employed to map infection clusters, analyze social vulnerability, and identify gaps in health service delivery. Spatial tools such as Kernel Density Estimation (KDE), Getis-Ord Gi*, and network accessibility models were instrumental in highlighting persistent clusters in socioeconomically disadvantaged neighborhoods. The review also assesses how spatial planning informed the deployment of mobile vaccination units to underserved areas, to overcome geographical and digital barriers. Finally, the paper offers strategic policy recommendations to institutionalize spatial epidemiology within Sri Lanka’s public health governance, advocating for the integration of real-time GIS dashboards, centralized geospatial health units, and capacity building for health professionals. The findings underscore the transformative potential of spatial intelligence in pandemic preparedness, response, and equity-focused health planning. This review synthesizes previously published data and findings and official dashboards.
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