(Press-News.org)
Thousands of dengue forecasting models have been published, but few have been tested in real public-health settings. Now, researchers from the US and Australia are launching a field evaluation in Vietnam to see whether a new early-warning platform can support earlier interventions against a disease that WHO says puts nearly half the world’s population at risk.
Southern Cross University (Aus) is leading the second phase of this multi-year collaboration, working alongside the University of Queensland (Aus), Yale University (USA) and Vietnam’s National Institute of Hygiene and Epidemiology. This phase has focused on translating predictive modelling into E-Dengue* – an open-source, user-friendly software system tailored for district-level decision-making.
WATCH the E-Dengue video explainer.
Southern Cross University researcher Dr Vinh Bui said the team’s priority has been creating a tool that frontline staff can use in real-world conditions.
“There are thousands of published studies on dengue prediction models, but very few become tools that are practical for local teams,” said Dr Bui.
“Our goal in this stage has been to build a tool that is reliable, actionable, fast and intuitive – something that supports, rather than complicates, routine public health work.”
With the predictive models developed and the E-Dengue platform built, the project is now entering its most critical stage: integrating the tool into Vietnam’s routine dengue surveillance and beginning a large cluster randomised controlled trial to test whether earlier warnings lead to earlier action and fewer outbreaks.
“We’ve built a tool with strong potential, but the critical test is ahead of us,” said Dr Bui
“The next three years will tell us whether early warnings lead to earlier, better-targeted interventions – and whether this improves health outcomes.”
Although interest in disease early-warning systems is growing, very few have been adopted into routine practice anywhere in the world. The research team says understanding why is just as important as building the technology.
This work is guided by the project teams' recently published “Useful, Usable, Used (3U) Framework” in Nature Communications, which examines how digital prediction tools can move from innovation to real-world adoption.
Yale University researcher Dr Robert Dubrow said the next stage of the collaboration will provide crucial evidence on whether early-warning systems can shift dengue control from a reactive to a proactive approach.
“Our team at Yale has led the development of the predictive model underpinning the platform,” Dr Dubrow said.
“We now look forward to working with our Vietnamese and Australian partners to rigorously evaluate whether early warnings change outcomes in practice.”
Interest in the approach is emerging from neighbouring countries, including Thailand, Laos and Cambodia, where dengue risk is rising under climate and population pressures.
Full deployment of the tool across selected districts in Vietnam’s Mekong Delta region will begin in early 2026. During 2026–2028, E-Dengue will be used in real public health decision-making while the research team conducts the randomised controlled trial and associated studies.
“This is a challenging and complex process,” said University of Queensland Associate Professor Dung Phung.
“Our long-term aim is to develop a tool that Vietnam’s Ministry of Health sees value in maintaining beyond the life of the project.”
*Please note the link to the E-Dengue site shows a simulation of the platform.
MEDIA INVITATION TO VIRTUAL BRIEFING
Media are invited to attend a virtual briefing on 18 December 2025 at 10.30am AEDT (Sydney, Australia), featuring the researchers leading the project. A recording of the briefing will be available following the event, and additional assets – including video and images – can be requested through the Southern Cross University media team at scumedia@scu.edu.au.
Register to attend the virtual briefing at Webinar Registration - Zoom
The E-Dengue platform is part of a Wellcome Trust –funded initiative focused on climate-informed disease preparedness.
END
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