Environment fingerprinting via digital technology – a new paradigm in hazard forecasting and early-warning systems for health risks in Africa
Funded by: UKRI Global Challenges Fund Project information: GCRF EDGE
Effective EWS-building is multi-dimensional, requiring a holistic, integrated, whole system approach. With this in mind, we have established EDGE as a multi-stakeholder, transdisciplinary initiative exploring digital innovation between three countries (UK, South Africa and Nigeria), three universities (University of Bath, Stellenbosch University, University of Lagos), governments, the digital tech industry, NGOs, policymakers and practitioners. EDGE connects natural and social sciences and engineering to address technical and socio-ecological challenges behind multi-hazard risks in rapidly growing urban areas of Africa.
EDGE focuses on the foundational network building that will enable designing an environment fingerprinting platform for public & environmental health diagnostics and hazard forecasting using digital technology to understand and characterise key cause – effect associations resulting from natural & anthropogenic hazards (e.g. flood, infectious disease) attending to the ripple effects that may cascade through the system in the context of sustained high rates of urbanization in African cities.
As an example, flooding can lead to a power-cut that disables communal amenities. This will trigger the spread of pathogenic organisms and toxins via contaminated water, leading to (infectious) disease. The affected communities will excrete elevated levels of disease biomarkers. There will be immediate socio-economic impacts (e.g. lost livelihoods) and, if unchecked, yet wider ripple effects through withdrawal of investment and stigmatisation of the region. Applying systems thinking to these cause-effect associations, and mapping out the interactions between various social and ecological components, will help identify the feedback mechanisms that lock the system into a certain state, as well as indicating leverage points and places to intervene to increase the resilience of the system against these disturbances.
Early Warning Systems 