ReviewRisk management and healthcare policy2022
Dengue Early Warning System as Outbreak Prediction Tool: A Systematic Review.
Review in Risk management and healthcare policy, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 4 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
25 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- Pooled it
- Quantitative modelling for dengue and Aedes mosquitoes in Africa: A systematic review of current approaches and future directions for Early Warning System development.PLoS neglected tropical diseases · 2024Pooled it
- Projecting non-communicable diseases attributable to air pollution in the climate change era: a systematic review.BMJ open · 2024Pooled it
- Effectiveness of early warning systems in the detection of infectious diseases outbreaks: a systematic review.BMC public health · 2022Pooled it
- Environmental and epidemiological drivers of dengue forecasting across heterogeneous transmission settings in Brazil and Panama.One health (Amsterdam, Netherlands) · 2026Article
- Predictive association between control measures and chikungunya fever incidence based on random forest and SHAP analysis.PLoS neglected tropical diseases · 2026Article
- The Impact of Climate Change on the Emergence and Reemergence of Diseases Transmitted by Mosquitoes in Temperate Regions: An Umbrella Review.Portuguese journal of public health · 2026Article
- Spatiotemporal patterns and forecasted trends of dengue in Saudi Arabia: a national surveillance study, 2012-2024.BMC infectious diseases · 2026Article
- Establishment of multiple predictive models for early identification of the dengue cases in outpatient healthcare systems.Scientific reports · 2026Article
- Forecasting and Early Warning Systems for Dengue Outbreaks: Updated Narrative Review.Revista da Sociedade Brasileira de Medicina Tropical · 2026Review
- Horizons of the Future: Preparedness and Response.Current topics in microbiology and immunology · 2026Review
- Molecular xenosurveillance ofMicrobiology spectrum · 2025Article
- Multi-model approach to understand and predict past and future dengue epidemic dynamics.Royal Society open science · 2025Article
- Investigating linkages between human movement and meteorological variables on dengue outbreaks in the Pacific Islands.PLoS neglected tropical diseases · 2025Article
- Forecasting Dengue: Evaluating the Role of Hydroclimate Information in Subseasonal to Seasonal Prediction.GeoHealth · 2025Article
- Primary health care data-based early warning system for dengue outbreaks: a nationwide case study in Brazil.Lancet regional health. Americas · 2025Article
- Effects of environmental factors on dengue incidence in the Central Region, Burkina Faso: A time series analyses.PLoS neglected tropical diseases · 2025Article
- Proceedings of the 7Vaccines · 2025Article
- Molecular epidemiology of dengue in Southeast Asia (SEA): Protocol of systematic review and meta-analysis.BMJ open · 2025Article
- Understanding local determinants of dengue: a geographically weighted panel regression approach in Yogyakarta, Indonesia.Tropical medicine and health · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early warning system (EWS) for vector-borne diseases is incredibly complex due to numerous factors originating from human, environmental, vector and the disease itself. Dengue EWS aims to collect data that leads to prompt decision-making processes that trigger disease intervention strategies to minimize the impact on a specific population. Dengue EWS may have a similar structural design, functions, and analytical approaches but different performance and ability to predict outbreaks. Hence, this review aims to summarise and discuss the evidence of different EWSs, their performance, and their ability to predict dengue outbreaks. A systematic literature search was performed of four primary databases: Scopus, Web of Science, Ovid MEDLINE, and EBSCOhost. Eligible articles were evaluated using a checklist for assessing the quality of the studies. A total of 17 studies were included in this systematic review. All EWS models demonstrated reasonably good predictive abilities to predict dengue outbreaks. However, the accuracy of their predictions varied greatly depending on the model used and the data quality. The reported sensitivity ranged from 50 to 100%, while specificity was 74 to 94.7%. A range between 70 to 96.3% was reported for prediction model accuracy and 43 to 86% for PPV. Overall, meteorological alarm indicators (temperatures and rainfall) were the most frequently used and displayed the best performing indicator. Other potential alarm indicators are entomology (female mosquito infection rate), epidemiology, population and socioeconomic factors. EWS is an essential tool to support district health managers and national health planners to mitigate or prevent disease outbreaks. This systematic review highlights the benefits of integrating several epidemiological tools focusing on incorporating climatic, environmental, epidemiological and socioeconomic factors to create an early warning system. The early warning system relies heavily on the country surveillance system. The lack of timely and high-quality data is critical for developing an effective EWS.
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