Spatial Analysis of Predisposition to Dengue Hemorrhagic Fever (DHF) Incidence in Timor Tengah Utara Regency in 2020-2022
Dengue Hemorrhagic Fever (DHF) is a potentially fatal infectious disease caused by the dengue virus, which is transmitted through the bites of Aedes aegypti and Aedes albopictus mosquitoes. In 2022, the Timor Tengah Utara Regency recorded 44 cases of DHF, with the highest incidence (31 cases) conce...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Perkumpulan Alumni dan Santri Mahyajatul Qurro'
2025-02-01
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| Series: | Ascarya |
| Subjects: | |
| Online Access: | https://journal.ascarya.or.id/index.php/iscs/article/view/732 |
| Summary: | Dengue Hemorrhagic Fever (DHF) is a potentially fatal infectious disease caused by the dengue virus, which is transmitted through the bites of Aedes aegypti and Aedes albopictus mosquitoes. In 2022, the Timor Tengah Utara Regency recorded 44 cases of DHF, with the highest incidence (31 cases) concentrated in the Sasi Public Health Center.Historical data revealed 56 cases in 2021, including one fatality, and 124 cases in 2020, with two deaths. This study aimed to analyze the influence of age, occupation, mobility, residence, income, and education on DHF incidence and examine the spatial distribution of DHF cases in the region using GeoDa software. Employing a descriptive-exploratory design, this study analyzed data from 224 patients with DHF. Bivariate LISA analysis revealed significant spatial autocorrelation for mobility (p = 0.0000), income (p = 0.0061), residence (p = 0.0003), and education (p = 0.0000), whereas age (p = 0.2774) and occupation (p = 0.9260) showed no significant relationships. Further testing with the Lagrange Multiplier (LM) model (p = 0.0000) confirmed spatial dependence, and the Spatial Autoregressive Model (SAR) was identified as the best model because of its highest R² (0.974420) and lowest AIC (329.606). These findings underscore the importance of considering spatial factors in DHF management and provide a foundation for targeted interventions, such as improving community awareness and resource allocation in high-risk areas. The results demonstrate the potential of spatial analysis tools to enhance public health strategies for infectious disease control.
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| ISSN: | 2798-5083 2775-4243 |