Jul 2026· Jurnal Ilmu Kesehatan Masyarakat· Vol 17, pp. 208-229· 0 citations
TL;DR
Assessment of spatial vulnerability and temporal trends in dengue cases in Yogyakarta City, Indonesia supports evidence-based surveillance, risk-based vector control, and targeted resource allocation for urban dengue prevention.
Abstract
Dengue hemorrhagic fever (DHF) remains a major public health concern in urban areas due to its increasing incidence and heterogeneous spatial distribution. Most previous studies have focused on either spatial or temporal analyses separately, limiting a comprehensive understanding of dengue dynamics. This study aimed to assess spatial vulnerability and analyze temporal trends in dengue cases in Yogyakarta City, Indonesia. A total of 1,227 confirmed dengue cases reported during 2020–2025 were obtained from the Yogyakarta City Health Office, with villages as the unit of analysis. Spatial vulnerability was assessed using Multi-Criteria Decision Analysis (MCDA), with variable weights derived from Ordinary Least Squares (OLS) analysis. Spatial data were processed in a Geographic Information System (GIS) using overlay techniques, while temporal trends were evaluated using the nonparametric Mann–Kendall trend test. Spatial analysis showed that 69.93% of Yogyakarta City was classified as moderately vulnerable and 10.67% as highly vulnerable, with high-risk areas concentrated in the city center. Population density was the strongest determinant of dengue vulnerability. Mann–Kendall analysis indicated no significant temporal trends across subdistricts, although dengue incidence fluctuated throughout the study period, with a marked increase in 2024. Umbulharjo Subdistrict consistently reported the highest number of dengue cases despite being predominantly classified as having low to moderate vulnerability, suggesting that environmental characteristics alone cannot fully explain dengue transmission in highly urbanized settings. Integrating spatial vulnerability mapping with temporal trend analysis provides a more comprehensive understanding of dengue dynamics and supports evidence-based surveillance, risk-based vector control, and targeted resource allocation for urban dengue prevention.
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.
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