Salim, Marko Ferdian and Satoto, Tri Baskoro Tunggul and Danardono, Danardono and Daniel, D. (2024) Digital Health Interventions in Dengue Surveillance to Detect and Predict Outbreak: A Scoping Review. Open Public Health Journal, 17. ISSN 1874-9445
Full text not available from this repository. (Request a copy)Abstract
Background: Dengue fever is a global concern, with half of the population at risk. Digital Health Interventions
(DHIs) have been widely used in Dengue surveillance.
Objective: The objective of this review is to identify DHIs that have been used in Dengue surveillance.
Methods: A systematic literature search was performed on three primary databases: PubMed, Scopus, and Google
Scholar. A total of 2637 studies, including duplicates, were found to be possibly pertinent to the study topic during
the electronic search for the systematic literature review. After the screening of titles and abstracts, 51 studies
remained eligible.
Results: The study analyzed 13 main categories of DHIs in Dengue surveillance, with Brazil, India, Sri Lanka, China,
and Indonesia being the top five countries. Geographic Information System was the most used DHIs, followed by
Machine Learning, Social Media, Mobile Applications, Google Trends, and Web Applications. DHIs were integrated,
as evidenced by the deployment of many DHIs simultaneously in a single Dengue surveillance program.
Conclusion: Future research should concentrate on finding more efficient ways to combine all available data sources
and approaches to improve data completeness and predictive model precision and identify Dengue outbreaks early.
Item Type: | Article |
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Additional Information: | Cited by: 1; All Open Access, Gold Open Access |
Uncontrolled Keywords: | Dengue; Detection; Digital health interventions (DHIs); Health informatics; Outbreak; Prediction; Surveillance. |
Subjects: | R Medicine > RP Public Health and Nutrition R Medicine > R Medicine (General) |
Divisions: | Faculty of Mathematics and Natural Sciences |
Depositing User: | Sri JUNANDI |
Date Deposited: | 02 Jan 2025 03:30 |
Last Modified: | 02 Jan 2025 03:30 |
URI: | https://ir.lib.ugm.ac.id/id/eprint/12631 |