Project description
New tools to predict outbreak of mosquito-borne diseases
Warmer temperatures (thanks to climate change) help disease-carrying mosquitos breed faster. Increasing in prevalence, geographical distribution and severity, mosquito-borne diseases represent a growing societal and economic threat globally. There is a growing need for better disease intelligence to help anticipate and identify eco-epidemiological risks that could potentially result in epidemics. Such intelligence requests understanding the complex interaction between humans, pathogen-carrying mosquitoes, pathogen reservoirs (birds) and a changing environment. The EU-funded E4Warning project will combine innovative eco-epidemiological modelling tools and intelligent digital solutions, co-designed and implemented by public health administrations, connecting humans, mosquitoes and birds to deliver early warnings and potential for response to mosquito-borne disease risk.
Objective
Mosquito-borne diseases place a heavy burden on society, causing widespread suffering and driving poverty. They are increasing in prevalence, geographical distribution and severity, representing a growing threat worldwide. Hence, there is a need for better disease intelligence, capable of anticipating and identifying eco-epidemiological risks leading to explosive epidemics and emergence in previously unaffected areas. The basis of such intelligence stems from a deep understanding of the factors that drive disease circulation, emergence and spread. This requires insights into the complex interplay between humans, pathogen-carrying mosquitoes, pathogen reservoirs (e.g. birds), and a changing environment. The E4Warning consortium brings together interdisciplinary, innovative, and open science to contribute to the One Health paradigm shift that is required to tackle the spread and transmission of zoonotic deadly pathogens, and harness this shift to nowcast and forecast mosquito-borne disease risk in a constantly changing and globally connected environment. Our work aims to disrupt disease transmission pathways connecting humans, mosquitoes, and birds through innovative eco-epidemiological modelling tools and intelligent digital solutions, co-designed and implemented by public health administrations. Open innovation strategies and big data tools are the cornerstone of the next-level One Health Early Warning Systems required in the face of mounting mosquito-borne disease threats.
Fields of science
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Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
28006 Madrid
Spain