It aims to facilitate country-specific situation analysis as a consequence of the COVID-19 outbreak, but is also a continuation of the previous assignment (May 1^st-Nov 30^th 2019); hence, it provides a basis for improvements and adjustments of the current version of the Integrated Demand Analysis Platform (IDAP), as well.

This project adjusts the current platform by introducing COVID-19 related scenarios within the LEWIE model. It develops and implements a stylized version of IDAP to provide timely output given the rapidly evolving pandemic. This stylized model builds on an extensive body of research modeling general-equilibrium impacts on heterogeneous household groups, and it derives micro-econometric estimates from a number of countries in which LEWIE models exist. These estimates have been aggregated to represent different groups of countries with certain common features, including food-import dependency, trade openness, strength of local supply chains and income level, optimally classified using a clustering algorithm programmed in Python, an open-source platform. We explore the use of remote continuous food security and market monitoring data to inform scenarios simulated in the model as the COVID-19 situation evolves in different countries. The model was built to be informative enough to support decision making but lean enough to require no additional microdata besides what the WFP normally collects. The latter is to ensure scalability.

Funding Agency: United Nations World Food Programme (WFP)