A predictive model for analysing Chad’s food security

Forecasting food security is important to achieve the UN’s second sustainable development goal”,Zero Hunger”. The UN identifies climate change, conflict, and COVID-19 as the three current elements of food security. So using these three imensions to forecast food security can assist countries and organisations in making decisions and implementing humanitarian action. However, there has not been much work done on forecasting food security for specific regions in some of he most vulnerable countries in the world, like Chad. This study addresses this gap by collecting data on the climate, conflict, and COVID-19 in Chad and by utilising machine learning methods to build predictive models. We propose a feasible predicted model for food security and the study’s results offer insight into (i) food security for Chad, (ii) demonstrate how this can be achieved with a relatively small dataset and, (iii) the different features that can be used from publicly available datasets to create a reliable model.