Dengue Advanced Readiness Tools (DART) - integrated digital system for dengue outbreak prediction and monitoring

Grant number: 226052/Z/22/Z

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Key facts

  • Disease

    Dengue
  • Start & end year

    2022
    2025
  • Known Financial Commitments (USD)

    $616,023.88
  • Funder

    Wellcome Trust
  • Principal Investigator

    Dr. Sarah Naomi Sparrow
  • Research Location

    Viet Nam
  • Lead Research Institution

    University of Oxford
  • Research Priority Alignment

    N/A
  • Research Category

    Policies for public health, disease control & community resilience
  • Research Subcategory

    Approaches to public health interventions
  • Special Interest Tags

    N/A
  • Study Type

    Non-Clinical
  • Clinical Trial Details

    N/A
  • Broad Policy Alignment

    Pending
  • Age Group

    Not Applicable
  • Vulnerable Population

    Not applicable
  • Occupations of Interest

    Not applicable

Abstract

Dengue is the most rapidly expanding arboviral disease in the world. Epidemics of varying size occur yearly in endemic settings during rainy seasons, yet real-time and highly spatially resolved predictions of the locations, duration, and size of dengue outbreaks within cities are not currently deployed. An integrated single software package that provides probabilistic and actionable forecast information about the locations and intensity of dengue outbreaks would enable the public and decision makers to take preventative actions, better target limited resources, anticipate surge capacity in hospitals, and prioritise and evaluate vector and disease control interventions. We bring together an interdisciplinary team of weather and climate scientists, epidemiologists, clinicians, public health policy makers, and engineers to build a scalable, flexible and automated forecasting system that can integrate diverse and complex datasets collated across two cities in Vietnam, and produce forecasts at sub-city scales in Hanoi (emerging) and Ho Chi Min City (endemic). A mobile and desktop application will be built where weather and disease forecasts are integrated to establish enhanced understanding of the link between them. The platform will deliver new science evaluating disease mitigating interventions as they are deployed and provide a tool for local predictions of dengue in cities.

40 Publications linked via Europe PMC

Deep learning with multiscale spatial context improves global dengue suitability mapping

Integrating ecological and anthropogenic risk identifies emerging Ebola spillover hotspots

Scalable deep-learning-based inference of time-varying transmission dynamics from outbreak phylogenies

Federated analysis of incubation period distributions using individual-level observed data and heterogeneous summary statistics

The emergence and molecular evolution of H5N1 influenza viruses in United States dairy cattle

Dynamics and ecology of a multistage expansion of Oropouche virus in Brazil.

Combining new interventions with urban development as a path to effective, consistent, and durable control of dengue

Impact of climate-induced human migration on dengue exposure risk in Africa

A multi-scale model to evaluate airport wastewater surveillance and ICU genomic monitoring for pandemic preparedness