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Innovative tools and strategies for surveillance and control of dengue (DengueTools)

Research project Dengue fever is a mosquito-borne viral disease estimated to cause about 50-100 million infections worldwide every year, of which 25,000 are fatal. Global incidence has risen rapidly in recent decades: some 2.5 billion people – two fifths of the world's population – are now at risk, mainly in the tropics and sub-tropics, but climate change and travel patterns have also contributed to the introduction of Dengue fever even in Europe.

Current surveillance systems and control efforts are clearly insufficient to combat dengue in endemic countries and to prevent spread to previously uninfected areas (including Europe). We will focus on the following aspects of the call: better diagnosis, surveillance, prevention as well as prediction and/or prevention of the spread of Dengue fever to previously uninfected regions (including Europe) in the context of climate change. We will develop a rapid diagnostic assay for resource limited settings that can be used as point-of-care, is portable, provides rapid results and is inexpensive. Novel tools for vector monitoring will be tested. We propose to develop a comprehensive, early warning, laboratory-based sentinel surveillance system that integrates clinical, entomological, environmental, socio-economic, and weather/climate indices to evaluate predictive capability for epidemic dengue. The aim is to translate this information directly into improved tools for surveillance (early diagnostic assays, early warning systems and predictive models, risk maps, improved tools for vector surveillance). Furthermore, we will test the impact of a novel community-based strategy on the reduction of dengue incidence in school aged children. Lastly, the integrated information on trends of importation of dengue, global mobility patterns, and vector distribution under changing climate conditions will improve our current understanding of the risk of introduction into previously uninfected areas, in particular Europe. Web based predictive tools, models and maps will be produced. The information will be disseminated to relevant agencies, academia and policy makers and will translate into improved surveillance and control.

Project overview

Project period:

2011-09-01 2016-02-28

Funding

Finansår , 2011

huvudman: Peter Byass, finansiar: European Commission, y2011: 50676,

Participating departments and units at Umeå University

Department of Epidemiology and Global Health

Research area

Public health and health care science

Project description

Current surveillance systems and control efforts are clearly insufficient to combat dengue in endemic countries and to prevent spread to previously uninfected areas (including Europe). We will focus on the following aspects of the call: better diagnosis, surveillance, prevention as well as prediction and/or prevention of the spread of Dengue fever to previously uninfected regions (including Europe) in the context of climate change. We will develop a rapid diagnostic assay for resource limited settings that can be used as point-of-care, is portable, provides rapid results and is inexpensive. Novel tools for vector monitoring will be tested. We propose to develop a comprehensive, early warning, laboratory-based sentinel surveillance system that integrates clinical, entomological, environmental, socio-economic, and weather/climate indices to evaluate predictive capability for epidemic dengue.

The aim is to translate this information directly into improved tools for surveillance (early diagnostic assays, early warning systems and predictive models, risk maps, improved tools for vector surveillance). Furthermore, we will test the impact of a novel community-based strategy on the reduction of dengue incidence in school aged children. Lastly, the integrated information on trends of importation of dengue, global mobility patterns, and vector distribution under changing climate conditions will improve our current understanding of the risk of introduction into previously uninfected areas, in particular Europe. Web based predictive tools, models and maps will be produced. The information will be disseminated to relevant agencies, academia and policy makers and will translate into improved surveillance and control.

Latest update: 2018-06-20