Responding to food insecurities: Detecting early signs of famine
Bo Andrée is working on an ambitious high-profile project at the World Bank: the Famine Action Mechanism (FAM). Bo is the leading data scientist at the World Bank in charge of the technical development part of the FAM, and is also working at the VU on finalizing his PhD thesis on spatial time series modeling.
During the IMF-World Bank Spring Meetings in 2017, World Bank President Jim Yong Kim and United Nations Secretary-General António Guterres committed to a “zero tolerance”. The World Bank, United Nations, ICRC and other global partners are now developing the Famine Action Mechanism (FAM)—the first global mechanism dedicated to supporting upstream interventions in famine prevention, preparedness and early action by formalizing the links between early warnings, financing and implementation arrangements.
The FAM builds on existing famine early warning systems to enhance the capacity to forecast areas most at risk of famine. By leveraging the World Bank’s analytics and partnering with global technology firms—including Microsoft, Google, Amazon Web Services and tech startups—the FAM will explore the use of state-of-the-art technologies, such as Artificial Intelligence and Machine Learning, to provide more continuous early warnings to identify when food crises threaten to turn into famines. More frequent and powerful data are critical for helping decision makers respond earlier to get ahead of escalating risks.
The project was launched at the yearly UN-summit on September 23, 2018. A 1.5 hour live stream of the UN Secretary General, World Bank president, heads of UN agencies and vice presidents of Microsoft and Google talking about the broad initiative is available here.
Last week Bo presented the outline of the project at the second Annual Symposium on Geospatial Analysis for International Development in Berkeley, California. This symposium focused on geospatial research that addresses climate- and conflict-driven migration and humanitarian response.
This is a repost of Spatial Economic’s subdepartment Spinlab.