ArticleThe West Indian medical journal2015
Spatial Distribution of Epidemiological Cases of Dengue Fever in Suriname, 2001-2012.
Article in The West Indian medical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The trial behind it
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Who cites it
6 citing papers in PubMed.
- Public health informatics tools for dengue risk management: A systematic review.PLOS digital health · 2026Article
- Two Decades of Dengue in Indonesia: Long-Term Trends in Incidence, Mortality, and Disability-Adjusted Life Years, 2005-2024.Pathogens (Basel, Switzerland) · 2026Article
- Dengue, chikungunya and Zika virus infections among Dutch travellers to Suriname: a prospective study during the introduction of chikungunya and Zika virus, 2014 to 2017.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2023Article
- A Privacy-Preserved Internet-of-Medical-Things Scheme for Eradication and Control of Dengue Using UAV.Micromachines · 2022Article
- A retrospective study on the socio-demographic factors and clinical parameters of dengue disease and their effects on the clinical course and recovery of the patients in a tertiary care hospital of Bangladesh.PLoS neglected tropical diseases · 2022Article
- Epidemiological Characteristics and Spatial-Temporal Clusters of Mumps in Shandong Province, China, 2005-2014.Scientific reports · 2017Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo characterize the frequency, incidence and severity of dengue fever in Suriname and to detect historic clusters of disease by integrating epidemiological data into a spatial visualization platform.
methodsThe frequency, incidence and severity of all reported dengue fever (DF) and dengue haemorrhagic fever (DHF) cases in Suriname from 2001 to 2012 were calculated and stratified by demographic factors. Using a geographic information systems (GIS) platform, we visualized the distribution of DF cases and used Moran's I to detect autocorrelation. Furthermore, a retrospective spatial Poisson probability model was used to identify local clusters of DF within Suriname. Local clusters were divided into neighborhoods and individual DF cases were mapped to the street level.
resultsIn Suriname, cases of DF emerge in cyclical patterns (three to five years) with seasonal peaks following the short and the long rainy season. Chi-square analysis indicated a statistically significant (p < 0.05) difference between age group, ethnicity and district and the onset of DHF. The spatial analysis detected spatial autocorrelation and four statistically significant (p < 0.05) clusters were identified in the two most populated districts of Paramaribo and Wanica.
conclusionIn Suriname, identification of demographic and environmental risk factors that contribute to the development of DHF is essential to determine how preventive action can be more effectively allocated. The integration of epidemiological data into a GIS platform allowed for the identification of historic epidemiological clusters of dengue which will be used to guide environmental health studies in Suriname.
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