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International Research Consortium on Dengue Risk Assessment, Management, and Surveillance

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United against dengue fever outbreaks

Around 400 million cases of dengue fever worldwide highlight the need for better disease management as well as effective transmission control and therapy. EU funding is supporting scientists in this endeavour.

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Following a recent pandemic of dengue fever in Madeira, the World Health Organisation raised an alert regarding disease incidence and outbreak frequency. Indeed the global distribution of the disease has reached unprecedented levels with more countries reporting dengue fever cases. Currently, there are no therapies or vaccines available and clinical management of the disease mainly entails careful monitoring and use of intravenous fluid therapy. The activities of the EU-funded 'International research consortium on dengue risk assessment, management, and surveillance' (IDAMS) project will address the need for new diagnostic and clinical tools for dengue fever management. The consortium will rely on clinical and laboratory parameters as well as viral and immunological biomarkers to differentiate between dengue and other common illnesses. IDAMS will also concentrate on mapping dengue disease globally and evaluating possible scenarios of spread to other regions in the future. Equally important is the development of effective and affordable early warning and outbreak response systems. IDAMS is studying patients with dengue fever to identify clinically useful correlates of severe dengue along with markers that detect disease evolution to severe forms. Innovative diagnostic tools are currently being developed to enhance the efficacy, sensitivity and speed of dengue fever detection. Active research into an effective vaccine is also underway and one of the project milestones is to delineate the mechanisms of protective immunity. Considerable efforts have gone into outbreak prediction. IDAMS members reviewed current practices in dengue surveillance systems and their impact on dengue control. By combining epidemiological data from different countries they generated a disease prediction model. Based on this model, the major risk factors seem to be the temperature, the presence of dengue cases and the age of dengue-infected individuals. Alongside vector distribution maps, climatic and socioeconomic data, this information will provide estimates on the global distribution of dengue fever up to the year 2080. Such data should also help in developing better tools, policies and guidelines to prevent or contain dengue transmission.


Dengue fever, outbreak, vaccine, biomarker, prediction model

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