Zero Hunger Lab and WCDI publish report on how data can help to foresee food crises
Zero Hunger Lab and WCDI have worked together on quantitative forecasting techniques for Integrated Phase Classification (IPC) phases of regions and this research is an introduction to the worlds of both food and nutrition security and data science, linking the two were possible. IPC describes the severity of food emergencies, indicating levels of acute food insecurity.
The analysis has been taken further by applying machine learning techniques to analyze the predicting value of satellite imagery and (social) media publications.
The report is important for two reasons. The innovations in data science that we describe have the potential to transform assessments and forecasts, support the localisation agenda, and take a food systems approach. This improved use of data offers ways to enable much more effective and efficient relief and development programs. Secondly, this improved use of data supports programs moving from mainly reactive to preventive actions.