The challenge to solve
The challenge is to develop a scalable, reliable, and cost-effective early-warning system prototype to forecast and monitor vector-borne diseases in order to contribute to the prevention of outbreaks, mitigating their impact on local, regional and global scales, and providing support to existing elimination efforts.
According to the World Health Organisation (WHO), vector-borne diseases such as malaria, Zika, dengue or yellow fever cause more than 1 million deaths globally each year.
Vectors are living organisms that can transmit infectious diseases between humans or from animals to humans. Vector-borne diseases are a global threat to public health and can have far-reaching economic and social impacts.
Climate and environmental phenomena contribute to creating the necessary conditions for these kinds of diseases to thrive. Variables such as rainfall, temperature and humidity affect the number and survival rate of mosquitoes and other vectors of diseases.
The 2030 Agenda for Sustainable Development, in the context of its Sustainable Development Goal 3 "Ensure healthy lives and promote well-being for all at all ages", aims to end the epidemics of malaria and neglected tropical diseases (amongst others) by 2030. It calls for strengthening the capacity of all countries, in particular developing countries, for early warning, risk reduction and management of national and global health risks.
The Earth Observation domain is changing with increasing amounts of data being generated from space-borne, air-borne, in-situ and citizen observatories.
Effective management of big data in this domain shall be an essential element in improving the 'early warning' capabilities of any system which aims to mitigate epidemics related to vector-borne diseases. The full potential of combining all the available data is not yet harnessed and innovative solutions are needed to enable the system's wider use and exploitation in this context. Such solutions would not only help to improve the 'preparedness' and response related to vector-borne disease outbreaks, but also foster the creation of a digital solution marketplace in the domain of environmental and climate health risks.
The specific rules of the contest will be published in the fourth quarter of 2017 by the European Commission, which will directly launch and manage the contest and award the prize based on the judgement of independent experts.
A reliable, cost-effective and scalable early warning system prototype to forecast and monitor vector-borne diseases, which should encompass innovative technological solutions integrating big data derived from different sources (e.g. space-borne, airborne, in-situ and citizen observations) in the Earth observation domain.
It should including climate data, vector-related modelling, meteorology, and geo-located information related to vector-borne disease outbreaks and behaviour. These should be interoperable with public health data and other socio-economic data.
The prototype should be demonstrated at local level, taking into account any relevant societal factors in the chosen geographical area.
It should be compatible for use with data coming from existing multi-disciplinary networks comprising health, humanitarian aid and emergency management actors, in order to leverage data and information from these networks, as well as to showcase the operational potential and added value of the solution.
Eligibility and award criteria
The contest is open to all legal entities (i.e. natural or legal persons, including international organisations) or groups of legal entities.
The prize will be awarded, after closure of the contest, to the contestant(s) who, in the opinion of the jury, demonstrates a solution that best meets the following cumulative criteria.
- operational capability and data integration
- demonstrated Implementation within an affected community
- scalability and sustainability of the Early-Warning Concept
- focus on European technology demonstration
- 2017 fourth quarter – contest opens
- 2020 third quarter – deadline to submit applications
- 2021 first quarter – prize awarded