Spatial and temporal analysis of hospitalized dengue patients in Bandung: demographics and risk

• Published in: Tropical Medicine and Health
• Main Authors: Lia Faridah, I. Gede Nyoman Mindra, Ramadhani Eka Putra, Nisa Fauziah, Dwi Agustian, Yessika Adelwin Natalia, Kozo Watanabe
• Format: Article in Journal/Newspaper
• Language: English
• Published: BMC 2021
• Subjects: Bandung; Dengue infection; Spatial pattern; Arctic medicine. Tropical medicine; RC955-962; Arctic
• Online Access: https://doi.org/10.1186/s41182-021-00329-9; https://doaj.org/article/8792d618e1074dbc969c4269eefcf5c8

Abstract Background Bandung, the fourth largest city in Indonesia and capital of West Java province, has been considered a major endemic area of dengue, and studies show that the incidence in this city could increase and spread rapidly. At the same time, estimation of incidence could be inaccurate due to a lack of reliable surveillance systems. To provide strategic information for the dengue control program in the face of limited capacity, this study used spatial pattern analysis of a possible outbreak of dengue cases, through the Geographic Information System (GIS). To further enhance the information needed for effective policymaking, we also analyzed the demographic pattern of dengue cases. Methods Monthly reports of dengue cases from January 2014 to December 2016 from 16 hospitals in Bandung were collected as the database, which consisted of address, sex, age, and code to anonymize the patients. The address was then transformed into geocoding and used to estimate the relative risk of a particular area’s developing a cluster of dengue cases. We used the kernel density estimation method to analyze the dynamics of change of dengue cases. Results The model showed that the spatial cluster of the relative risk of dengue incidence was relatively unchanged for 3 years. Dengue high-risk areas predominated in the southern and southeastern parts of Bandung, while low-risk areas were found mostly in its western and northeastern regions. The kernel density estimation showed strong cluster groups of dengue cases in the city. Conclusions This study demonstrated a strong pattern of reported cases related to specific demographic groups (males and children). Furthermore, spatial analysis using GIS also visualized the dynamic development of the aggregation of disease incidence (hotspots) for dengue cases in Bandung. These data may provide strategic information for the planning and design of dengue control programs.