Spatial Mapping of Dengue Hotspots in Lahore, Faisalabad, Karachi, and Rawalpindi

Abstract

BACKGROUND: Dengue fever remains a major public health concern in Pakistan, with recurrent outbreaks across major urban centers. Traditional epidemiological surveillance provides aggregate case counts but lacks the spatial precision necessary for targeted intervention. Geographic Information System (GIS)-based analytical modeling offers a modern approach to identify high-risk areas, enabling data-driven vector control and public health planning.

OBJECTIVE: To identify, map, and analyze dengue hotspots across Lahore using GIS-based spatial and statistical modeling, and to determine environmental and demographic factors associated with elevated dengue incidence.

METHODOLOGY: A retrospective spatial-epidemiological study was conducted using laboratory-confirmed dengue cases from Lahore’s 2023 outbreak season. Case addresses were geocoded and analyzed across 112 Union Councils. Hotspot detection was performed using Getis–Ord Gi* and SaTScan (Poisson model) to locate statistically significant clusters. Geo-climatic variablestemperature, rainfall, proximity to water bodies, and land-surface temperaturewere incorporated into regression models to assess environmental associations with dengue incidence. Data were processed in ArcGIS and R (version 4.2), and ethical approval was obtained (IRB/LH/2023/015).

RESULTS: A total of 4,562 dengue cases were mapped, yielding an average incidence of 18.3 per 10,000 population. Fifteen Union Councils were identified as significant hotspots (p < 0.01), primarily concentrated in central and southwestern Lahore. Higher land-surface temperature (IRR = 1.18; 95% CI: 1.10–1.26) and cumulative rainfall (IRR = 1.12; 95% CI: 1.05–1.20) were positively associated with dengue incidence. Kernel density maps and SaTScan clusters confirmed two high-risk zones with threefold elevated risk compared to non-hotspot areas.

CONCLUSION: GIS-based analytical modeling effectively identified spatial dengue hotspots and revealed strong associations with climatic and hydrological factors. These findings provide a robust foundation for targeted vector control and climate-adaptive dengue surveillance strategies in urban Pakistan.

KEY TERMS: Climate Factors, Dengue, Geographic Information Systems, Hotspots, Lahore, Pakistan, Spatial Analysis