A Highly Granular Temporary Migration Dataset Derived From Mobile Phone Data in Senegal

TL;DR

This paper presents a detailed, open-access dataset derived from mobile phone data in Senegal that captures temporary migration with high spatial and temporal resolution, addressing data gaps in developing countries.

Contribution

It introduces a novel methodology for detecting temporary migration events from digital traces and provides a comprehensive dataset for Senegal from 2013 to 2015.

Findings

Dataset covers 151 locations with half-month resolution

Methodological tools improve detection of temporary migration events

Addresses key challenges in aggregating individual trajectories

Abstract

Understanding temporary migration is crucial for addressing various socio-economic and environmental challenges in developing countries. However, traditional surveys often fail to capture such movements effectively, leading to a scarcity of reliable data, particularly in sub-Saharan Africa. This article introduces a detailed and open-access dataset that leverages mobile phone data to capture temporary migration in Senegal with unprecedented spatio-temporal detail. The dataset provides measures of migration flows and stock across 151 locations across the country and for each half-month period from 2013 to 2015, with a specific focus on movements lasting between 20 and 180 days. The article presents a suite of methodological tools that not only include algorithmic methods for the detection of temporary migration events in digital traces, but also addresses key challenges in aggregating individual trajectories into coherent migration statistics. These methodological advancements are not only pivotal for the intrinsic value of the dataset but also adaptable for generating systematic migration statistics from other digital trace datasets in other contexts.