With natural hazards striking at an unprecedented rate and global investment in infrastructure expected to be about US$94 trillion by 2040, it is evident that immediate and serious measures need to be taken on both fronts to combat disaster and restrict human and economic loss.
The most impactful way would be to predict disasters before they happen and detect weaknesses in infrastructure before they worsen. Early Warning Systems do precisely this. The United Nations defines ‘early warning’ as "provision of timely and effective information, through identified institutions, that allows individuals exposed to hazards to take action to avoid or to reduce their risk and prepare for effective response".
Early Warning Systems (EWS) use technology to signal vulnerability in infrastructure and issue alerts in the event of any oncoming disaster. To be effective, these systems should be able to recognize risks well in advance and with a high degree of accuracy. When a warning is issued, governments as well as the threatened communities should have the time and preparedness to respond in a way that will save lives and assets.
This means that the human as well as the technological aspects are important. Unfortunately, these systems are often designed with a sole focus on technology. Unless there is a corresponding responsive action from the government, high-tech predictions alone are ineffectual.
Countries seeking to build an effective EWS must, therefore, successfully incorporate all the technical, technological and human angles that comprise an early warning.
The Coalition for Disaster Resilient Infrastructure will work in partnership with governments, national institutions, academia, the UN and regional and local actors to assess gaps in infrastructure specific EWS.
CDRI will invest to update and enhance information on the exposure of infrastructure systems and to model climate related hazards such as droughts, heatwaves and wildfires, enabling near time response. It will make this information available to infrastructure managers and build tools for decision support.