Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modeling tools for dengue risk mapping - a systematic review
Show others and affiliations
2014 (English)In: International Journal of Health Geographics, E-ISSN 1476-072X, Vol. 13, article id 50Article, review/survey (Refereed) Published
Abstract [en]

INTRODUCTION: The global spread and the increased frequency and magnitude of epidemic dengue in the last 50 years underscore the urgent need for effective tools for surveillance, prevention, and control. This review aims at providing a systematic overview of what predictors are critical and which spatial and spatio-temporal modeling approaches are useful in generating risk maps for dengue.

METHODS: A systematic search was undertaken, using the PubMed, Web of Science, WHOLIS, Center for Disease Control (CDC) and OvidSP databases for published citations, without language or time restrictions. A manual search of the titles and abstracts was carried out using predefined criteria, notably the inclusion of dengue cases. Data were extracted for pre-identified variables, including the type of predictors and the type of modeling approach used for risk mapping.

RESULTS: A wide variety of both predictors and modeling approaches was used to create dengue risk maps. No specific patterns could be identified in the combination of predictors or models across studies. The most important and commonly used predictors for the category of demographic and socio-economic variables were age, gender, education, housing conditions and level of income. Among environmental variables, precipitation and air temperature were often significant predictors. Remote sensing provided a source of varied land cover data that could act as a proxy for other predictor categories. Descriptive maps showing dengue case hotspots were useful for identifying high-risk areas. Predictive maps based on more complex methodology facilitated advanced data analysis and visualization, but their applicability in public health contexts remains to be established.

CONCLUSIONS: The majority of available dengue risk maps was descriptive and based on retrospective data. Availability of resources, feasibility of acquisition, quality of data, alongside available technical expertise, determines the accuracy of dengue risk maps and their applicability to the field of public health. A large number of unknowns, including effective entomological predictors, genetic diversity of circulating viruses, population serological profile, and human mobility, continue to pose challenges and to limit the ability to produce accurate and effective risk maps, and fail to support the development of early warning systems.

Place, publisher, year, edition, pages
2014. Vol. 13, article id 50
Keywords [en]
Dengue, Systematic review, Risk mapping, Prediction, Surveillance, Dengue control, Remote sensing, GIS, Spatial, Land cover
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-97509DOI: 10.1186/1476-072X-13-50ISI: 000346931400001PubMedID: 25487167Scopus ID: 2-s2.0-84924869057OAI: oai:DiVA.org:umu-97509DiVA, id: diva2:773470
Available from: 2014-12-19 Created: 2014-12-19 Last updated: 2023-03-23Bibliographically approved

Open Access in DiVA

fulltext(1716 kB)2422 downloads
File information
File name FULLTEXT01.pdfFile size 1716 kBChecksum SHA-512
16b85506e6fa534dc64f083de9a0101273146ef9a09aeb295bad6c0de1e1e1ef905e93c7c9ee8affd860d5b4750b47dbece5e8910c4e11f3711e45ba68209231
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMedScopus

Search in DiVA

By author/editor
Wilder-Smith, Annelies
By organisation
Epidemiology and Global Health
In the same journal
International Journal of Health Geographics
Public Health, Global Health, Social Medicine and Epidemiology

Search outside of DiVA

GoogleGoogle Scholar
Total: 2422 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 219 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf