Arbeitsbereich

Migration und Mobilität

Auf einen Blick Projekte Publikationen Team

Projekt

Migration, Displacement, and Health Relationships in Crisis-Affected Populations (Dissertation)

Jackson Anthony Mason-Mackay, Emilio Zagheni, Asli Ebru Sanlitürk, Arkadiusz Wiśniowski (The University of Manchester, Vereinigtes Königreich von Großbritannien und Nordirland)

Ausführliche Beschreibung

This dissertation develops approaches for measuring forced displacement and population mobility in data-scarce environments, where conventional demographic data collection may be constrained or unavailable. The project's central focus is the use of digital trace data (i.e., records of online behavior generated by individuals as a byproduct of internet use) as a proxy for population dynamics in crisis settings. This approach is motivated by a growing recognition that traditional migration statistics are often incomplete or untimely, particularly in conflict-affected areas where displacement is most acute.

The first empirical chapter examines the case of Sudan, which has been experiencing the world's largest displacement crisis since the outbreak of armed conflict in April 2023. Over three million refugees have fled to neighboring countries, while more than eight million remain internally displaced. Sudan's displacement patterns reflect wider global trends in which forced migrants largely remain within their region, with the majority hosted by low- and middle-income countries. The Sudan context presents an opportunity to test whether digital trace data can detect displacement signals in a low-income setting with limited internet penetration, extending a methodological literature that has predominantly focused on upper-middle- or high-income host countries.

The chapter focuses on two migration corridors: southeastward movement from Sudan into Ethiopia and northward movement from Sudan into Egypt. For the Sudan-Ethiopia corridor, the study draws on daily border crossing records from the International Organisation for Migration (IOM) from April 2023 to June 2025. For the Sudan-Egypt corridor, migration patterns are estimated using UNHCR refugee stock data.

Trends in cross-border migration are analyzed alongside daily Wikipedia page view counts for geographically relevant locations – including major cities, Sudanese state capitals, and border towns – disaggregated by language (Arabic, Amharic, English, and Russian). The use of language as a proxy for user population follows methodology developed by Vieira, Şanlıtürk, and Zagheni (2025), which may be applicable to the case of Arabic-speaking Sudanese entering Ethiopia, where Arabic is not widely spoken. Google Trends data are used to test whether search intensity for migration-related information aligns with the timing and scale of cross-border migration, using keywords such as "refugee," "visa," and “Egyptian pound,” as well as the names of border towns and cities.

Preliminary results show positive associations between Arabic-language Wikipedia page views for migration route locations and weekly border crossings into Ethiopia, compared to near-zero correlations for the same Wikipedia pages in languages like Russian and Amharic. For northward migration into Egypt, Google search intensity for migration-related terms within Sudan similarly rose in tandem with UNHCR-recorded refugee arrivals following the outbreak of the conflict in April 2023. Google search intensity for keywords related to Ethiopia may be too low for the purposes of this study. It is hoped that when these findings are further developed, they can contribute evidence on the feasibility and limitations of digital trace data as a near-real-time monitoring tool for forced displacement in the Global South.