Shengjie Lai, Elisabeth zu Erbach-Schoenberg, Carla Pezzulo, Nick W. Ruktanonchai, Alessandro Sorichetta, Jessica Steele, Tracey Li, Claire Dooley, and Andy Tatem.
Statistics on internal migration are important for keeping estimates of subnational population numbers up-to-date, as well as urban planning, infrastructure development, and impact assessment, among other applications. However, migration flow statistics typically remain constrained by the logistics of infrequent censuses or surveys. The penetration rate of mobile phones is now high across the globe with rapid recent increases in ownership in low-income countries. Analyzing the changing spatiotemporal distribution of mobile phone users through anonymized call detail records (CDRs) offers the possibility to measure migration at multiple temporal and spatial scales. Based on a dataset of 72 billion anonymized CDRs in Namibia from October 2010 to April 2014, we explore how internal migration estimates can be derived and modeled from CDRs at subnational and annual scales, and how precision and accuracy of these estimates compare to census-derived migration statistics. We also demonstrate the use of CDRs to assess how migration patterns change over time, with a finer temporal resolution compared with censuses. Moreover, we show how gravity-type spatial interaction models built using CDRs can accurately capture migration flows. The results highlight that estimates of migration flows made using mobile phone data is a promising avenue for complementing more traditional national migration statistics and obtaining more timely and local data.