ArticleTropical medicine and health2021
Spatial and temporal analysis of hospitalized dengue patients in Bandung: demographics and risk.
Article in Tropical medicine and health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Public health informatics tools for dengue risk management: A systematic review.PLOS digital health · 2026Article
- Leveraging geographic information system for dengue surveillance: a scoping review.Tropical medicine and health · 2025Review
- Spatial autocorrelation of environmental factors influencing dengue outbreaks using Moran's I: A study from Nepal (2020-2023).PloS one · 2025Article
- Case Report: Dengue Fever Progressing to Acute Liver Failure and Hepatic Encephalopathy.The American journal of tropical medicine and hygiene · 2024Article
- Article
- Dengue Burden and Factors Influencing Severity in Honduras: A Descriptive and Analytical Study.Revista da Sociedade Brasileira de Medicina Tropical · 2024Article
- Understanding the spread of infectious diseases in edge areas of hotspots: dengue epidemics in tropical metropolitan regions.International journal of health geographics · 2023Article
- Spatial model of Dengue Hemorrhagic Fever (DHF) risk: scoping review.BMC public health · 2023Article
- Mapping hotspots and cluster analysis of the current dengue outbreak in Bangladesh.New microbes and new infections · 2023Article
- Optimal Validated Multi-Factorial Climate Change Risk Assessment for Adaptation Planning and Evaluation of Infectious Disease: A Case Study of Dengue Hemorrhagic Fever in Indonesia.Tropical medicine and infectious disease · 2022Article
- The application of geographic information system for dengue epidemic in Southeast Asia: A review on trends and opportunity.Journal of public health research · 2022Article
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7 authors.
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Abstract
backgroundBandung, 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.
methodsMonthly 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.
resultsThe 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.
conclusionsThis 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.
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