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.

Publicationslinked via Europe PMC

Last Updated:32 minutes ago

View all publications at Europe PMC

Disaggregation Regression and Multi-Model Evaluation for Predicting Dengue Risk in Africa

The overlapping global distribution of dengue, chikungunya, Zika and yellow fever.

Modelling practices, data provisioning, sharing and dissemination needs for pandemic decision-making: a European survey-based modellers’ perspective

Spatiotemporal disease suitability prediction for Oropouche virus and the role of vectors across the Americas

Genomic Characterization of Circulating Dengue Virus, Ethiopia, 2022-2023.

Large-scale genomic surveillance reveals immunosuppression drives mutation dynamics in persistent SARS-CoV-2 infections

Dengue virus importation risks in Africa: a modelling study.

COVID-19 pandemic interventions reshaped the global dispersal of seasonal influenza viruses.

Toward optimal disease surveillance with graph-based active learning.