Imas Masturoh, Ida Sugiarti, Fery Fadly, Mujiyanto Mujiyanto, Endang Puji Astuti
Spatial clustering of dengue cases was identified in several urban villages, particularly around Cipedes and Tugujaya. Bivariate LISA revealed significant spatial co-occurrence between high dengue incidence and high population density. Spatio-temporal analysis detected three statistically significant clusters during 2023, indicating that dengue transmission was concentrated in specific geographic areas during distinct periods rather than being uniformly distributed over time.
BACKGROUND OBJECTIVES: Dengue is a major vector-borne disease in tropical and subtropical regions, including Indonesia, where recurrent outbreaks remain a significant public health concern. Understanding the spatial and temporal distribution of dengue transmission is essential for effective surveillance and targeted control strategies. This study aimed to map the spatio-temporal hotspots of dengue transmission in Tasikmalaya City, West Java, Indonesia, using Geographic Information Systems (GIS) and spatial statistical analysis.
METHODS: Village-level spatial analyses were conducted using reported dengue cases from the complete calendar year of 2022 and 279 cases reported between January and September 2023. Of the 279 cases reported in 2023, 275 had valid residential coordinates and were included in the space-time cluster analysis. The space-time analysis was based on symptom onset dates ranging from 27 December 2022 to 30 September 2023. Global Moran's I, Local Indicators of Spatial Association (LISA), bivariate LISA, and the spatial scan statistic implemented in SaTScan were used to assess the spatial distribution and spatio-temporal clustering of dengue cases.
RESULTS: Spatial clustering of dengue cases was identified in several urban villages, particularly around Cipedes and Tugujaya. Bivariate LISA revealed significant spatial co-occurrence between high dengue incidence and high population density. Spatio-temporal analysis detected three statistically significant clusters during 2023, indicating that dengue transmission was concentrated in specific geographic areas during distinct periods rather than being uniformly distributed over time.
INTERPRETATION CONCLUSION: The findings highlight distinct spatio-temporal hotspots of dengue transmission and emphasize the role of population density and seasonal factors in shaping dengue risk. Spatial mapping and cluster detection can support targeted vector control and public health interventions.