Astha
Vol. 14, Issue 1, Jul-Dec 2022
Abstract:
Spatial Data Science offers a powerful framework to analyze the spatiotemporal dynamics of COVID-19. This paper discusses methodologies, tools, and applications of spatial data in understanding the spread, impact, and management of COVID-19. It integrates Geographic Information Systems (GIS), machine learning, and public health data to show how spatial data has informed policy decisions, enhanced epidemiological models, and guided vaccination strategies. This study depicts the role of geospatial technologies in response to pandemics by analyzing spatial patterns, predictive modelling, and optimizing resource allocation. The research identifies key challenges, such as data privacy concerns, limitations in accuracy, and difficulties in integrating heterogeneous data sources. Addressing these challenges can strengthen the utility of spatial data science in combating public health crises at present and in the future. The findings of this paper provide actionable insights for researchers, policymakers, and healthcare professionals that can help make more robust and informed decisions during pandemics and other public health emergencies.
DOI: http://doi.org/10.37648/ijrmst.v14i01.023
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