Mapping dengue vulnerability: spatial cluster analysis reveals patterns in Central Java, Indonesia - Fithriyyah, Anisahtul; Purwaningsih, Tuti; Konate, Siaka; Abdalla, Modawy Adam Ali (Science in Information Technology Letters, 2023)
In Indonesia, where the interplay between climate variability and infectious diseases is pronounced, Dengue Fever poses a significant threat, particularly in Central Java, ranking as the province with the third-highest incidence of Dengue cases nationwide. This study adopts a proactive approach, employing cluster analysis techniques—single linkage, average linkage, and Ward’s method—to categorize cities and regencies in Central Java based on their susceptibility to Dengue outbreaks. The comparative analysis, facilitated by standard deviation values, reveals nuanced vulnerability patterns, with the single linkage method presenting the most refined categorization, yielding four distinct vulnerability clusters: very low (0.097), low (0.150), medium (0.205), and high (0.303). Furthermore, spatial analysis utilizing Moran’s Index indicates a positive spatial autocorrelation among Dengue cases (Moran’s I = 0.62, p 0.05), underscoring the spatial homogeneity in case distribution across regions. These findings emphasize the critical need for targeted interventions and evidence-based policymaking to effectively combat Dengue transmission in Central Java and mitigate its public health impact.