Mapping the Persistent Danger Zones of Dengue Hemorrhagic Fever in Semarang City: A Spatio-Temporal Analysis Based on INLA
DOI:
https://doi.org/10.30871/jaic.v10i3.12928Keywords:
Bayesian Spatial, Dengue Hemorrhagic Fever, Exceedance Probability, INLA, Spatial SpilloverAbstract
This study maps the spatio-temporal risk dynamics of Dengue Hemorrhagic Fever (DHF) across 16 districts in Semarang City (2016–2025). Traditional epidemiological approaches using raw incidence rates often ignore spatial autocorrelation and struggle with overdispersion anomalies. To address this, we implemented a Hierarchical Bayesian framework using Integrated Nested Laplace Approximations (INLA) with a Negative Binomial distribution and a Besag-York-Mollié (BYM2) spatial architecture. We specified the spatial topology through a manually validated binary adjacency matrix to minimize subjectivity in defining regional boundaries. Our structured model improved computational performance significantly, reducing the Deviance Information Criterion (DIC) by 34.31% and the Root Mean Square Error (RMSE) by 15.30% compared to a baseline Poisson regression model. Using Geopandas and NetworkX for visualization, we identified Tembalang and Banyumanik districts as absolute Epicenter Nodes with an Exceedance Probability of 1.000. Spatial spillover network analysis demonstrated the propagation of epidemiological pressure from these epicenters to surrounding buffer zones, synchronized with the seasonal peak in the first quarter. This framework provides a precise computational foundation for vector control strategies, shifting from localized reactive approaches to preventive cluster mitigation.
Downloads
References
[1] U. N. Alfiyanti and A. Siwiendrayanti, “Analisis Spasial dan Temporal Kejadian DBD di Kota Semarang Tahun 2016-2019,” J. Kesehat. Lingkung. J. Dan Apl. Tek. Kesehat. Lingkung., vol. 18, no. 1, pp. 39–48, Jan. 2021, doi: 10.31964/jkl.v18i1.286.
[2] N. I. Ismah and A. Fahmi, “Dengue Risk Stratification in Semarang City Using a Gaussian Mixture Model Based on Multi-Dimensional Urban Indicators,” J. Electron. Electromed. Eng. Med. Inform., vol. 8, no. 1, pp. 395–408, Nov. 2025, doi: 10.35882/jeeemi.v8i1.1426.
[3] J. Simkin, T. J. B. Dummer, A. C. Erickson, M. C. Otterstatter, R. R. Woods, and G. Ogilvie, “Small area disease mapping of cancer incidence in British Columbia using Bayesian spatial models and the smallareamapp R Package,” Front. Oncol., vol. 12, Oct. 2022, doi: 10.3389/fonc.2022.833265.
[4] H. Rue, S. Martino, and N. Chopin, “Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations,” J. R. Stat. Soc. Ser. B Stat. Methodol., vol. 71, no. 2, pp. 319–392, Apr. 2009, doi: 10.1111/j.1467-9868.2008.00700.x.
[5] M. Soukavong et al., “Bayesian spatio-temporal analysis of dengue transmission in Lao PDR,” Sci. Rep., vol. 14, no. 1, p. 21327, Sep. 2024, doi: 10.1038/s41598-024-71807-3.
[6] M. F. Salim, T. B. T. Satoto, and Danardono, “Predicting spatio-temporal dynamics of dengue using INLA (integrated nested laplace approximation) in Yogyakarta, Indonesia,” BMC Public Health, vol. 25, no. 1, p. 1321, Apr. 2025, doi: 10.1186/s12889-025-22545-2.
[7] I. G. N. M. Jaya, Y. Andriyana, B. Tantular, S. S. Pangastuti, and F. Kristiani, “Spatiotemporal Dengue Forecasting for Sustainable Public Health in Bandung, Indonesia: A Comparative Study of Classical, Machine Learning, and Bayesian Models,” Sustainability, vol. 17, no. 15, p. 6777, Jan. 2025, doi: 10.3390/su17156777.
[8] A. Riebler, S. H. Sørbye, D. Simpson, and H. Rue, “An intuitive Bayesian spatial model for disease mapping that accounts for scaling,” Stat. Methods Med. Res., vol. 25, no. 4, pp. 1145–1165, Aug. 2016, doi: 10.1177/0962280216660421.
[9] M. Blangiardo, M. Cameletti, G. Baio, and H. Rue, “Spatial and spatio-temporal models with R-INLA,” Spat. Spatio-Temporal Epidemiol., vol. 4, pp. 33–49, Mar. 2013, doi: 10.1016/j.sste.2012.12.001.
[10] P. Moraga, Welcome | Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny. Accessed: Apr. 26, 2026. [Online]. Available: https://www.paulamoraga.com/book-geospatial/
[11] Mamenun, Y. Koesmaryono, A. Sopaheluwakan, R. Hidayati, B. D. Dasanto, and R. Aryati, “Spatiotemporal Characterization of Dengue Incidence and Its Correlation to Climate Parameters in Indonesia,” Insects, vol. 15, no. 5, p. 366, May 2024, doi: 10.3390/insects15050366.
[12] D. E. Kurniawan, M. A. Dzikri, S. Irawan, and M. O. Gustin, Sistem Informasi Geografis: Praktikum dan Penerapan dalam Pengambilan Keputusan. Batam, Indonesia: PolibatamPress, 2020.
[13] D. E. Kurniawan, and A. Fatulloh,“Clustering of Social Conditions in Batam, Indonesia Using K-Means Algorithm and Geographic Information System,” International Journal of Earth Sciences and Engineering (IJEE), Vol. 10 No. 05, 2017.
[14] M. F. Salim, T. B. T. Satoto, and Danardono, “Predicting spatio-temporal dynamics of dengue using INLA (integrated nested Laplace approximation) in Yogyakarta, Indonesia,” BMC Public Health, vol. 25, art. no. 1321, 2025, doi: 10.1186/s12889-025-22545-2.
[15] A. Sani, B. Abapihi, Mukhsar, R. Tosepu, I. Usman, and G. A. Rahman, “Bayesian temporal, spatial and spatio-temporal models of dengue in a small area with INLA,” International Journal of Modelling and Simulation, vol. 43, no. 6, pp. 939–951, 2023, doi: 10.1080/02286203.2022.2139108.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Natanael Anggit Wicaksono, Amiq Fahmi
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) ) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
