itflows

ITFLOWS

Overview

Reliable prediction of migrants is crucial for better allocation of resources at the borders and ultimately, from a humanitarian point of view, for the experience of the migrants. Yet, to date, there are no accurate large-scale studies that can reliably predict new migrants arriving in Europe. The majority of data-driven approaches for prediction so far have focused solely on one specific country of origin or destination in each study. For instance, predictions have been made on the Haitian migration to the United States and the US/Mexico border. There are also models predicting forced displacement trends from Mali, African Central Africa, Burundi and South Sudan.

In the EU, some Member States, such as the United Kingdom and Sweden are using their own individual models to forecast the number of migrants arriving in their territories but each of them uses different data sources and timeframes for prediction. Similarly, some early warning models have been able to predict which countries have the potential to create refugee outflows but they have not included movements driven primarily by environmental causes, such as natural disasters, weather changes, or other unexpected conditions.

The general problem is a lack of cohesion between the tools and data platforms in the field of migration and asylum in Europe, with numerous international, national, and non-governmental organisations (NGO’s) gathering data on migratory movements, the number of refugees and available resources, but doing it independently from each other and with limited scope. As a consequence, policy designs in the area of migration, asylum and integration management often lack appropriate foresight.

One of the most evident outcomes of the lack of effective migration management and integration strategies in some Member States is the gradual increase in the risk of tension arising between migrants and EU citizens. Law enforcement authorities, NGOs and the media have already reported a high number of incidents of racist violence against migrants and refugees in 2019, with several cases resulting in severe injury.

Negative sentiments towards migrants are one of the main reasons of tensions between migrants and EU citizens, which may lead to discriminatory acts, abuses or other hate crimes. ITFLOWS will identify potential risks of tension and establish adequate multidisciplinary solutions in the Member States that will safeguard the rights of both EU citizens and migrants, while contributing to cohesiveness and inclusiveness of European societies. ITFLOWS will study such risks from a bottom-up approach with existing data on sentiments linked to migration. The study will identify the causes of variation of sentiments and their connection to risks of tension, and will propose solutions to minimise such tensions through a) social-economic strategies and recommendations for national/ EU policy makers and b) operational decisions of allocation of refugees for practitioners and municipalities. Policy solutions should go in the direction of condemning potential radical/racist attitudes from EU citizens, whereas solutions for practitioners will focus on helping migrants integrate in favourable environments for them.

ITFLOWS will propose tailor-made solutions for practitioners and policy makers for managing migration. On the one hand, the EUMigraTool targets first-line-practitioners, second-level reception organisations and municipalities. It will provide modular solutions based on the prediction of migration flows and the identification of risks of tensions between migrants and EU citizens. On the other hand, an in-depth analysis on drivers, patterns and choices of migration as well as public sentiment towards migration will lead to the drafting of adequate recommendations and good practices for policy makers, governments and EU institutions.

MPC researchers associated with this project:

Lenka Dražanová and Jerome Gonnot.

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