Geospatial Insights into Dengue: Climate Trends and Epidemic Clusters in Manipur

Dengue fever, a vector-borne disease transmitted by Aedes mosquitoes, has become a growing public health concern in India, particularly in Manipur. The interplay between climate variables—temperature, precipitation, and vegetation cover—significantly influences dengue transmission dynamics. This study employs geospatial analytics and machine learning techniques to analyse the spatiotemporal trends of dengue outbreaks in Manipur from 2018 to 2024. Dengue case data, obtained from the National Center for Vector Borne Diseases Control, were integrated with climate variables extracted from Google Earth Engine (GEE). The administrative boundary of Manipur was validated using Folium, ensuring accurate geospatial analysis. Temperature, precipitation, and NDVI data were processed to assess their correlation with dengue incidence. K-Means clustering was applied to classify districts into epidemiological risk zones, identifying dengue hotspots, while hierarchical clustering was used to analyze seasonal outbreak patterns. The findings revealed significant correlations between dengue incidence and climate factors, with moderate positive associations observed between precipitation and dengue cases, highlighting the role of monsoon-driven vector proliferation. Results indicated that high-risk districts experienced persistent outbreaks, emphasizing the need for targeted vector control strategies. The use of Google Colab enabled efficient data processing and visualization, leveraging cloud-based computational tools for advanced analytics. This study underscores the importance of integrating climatic parameters into dengue surveillance and predictive modelling to enhance early warning systems. The insights gained can inform public health policies, facilitating proactive interventions and resource allocation to mitigate dengue transmission in Manipur.