Migration Methods: Lessons from Following A Highly Mobile Population

Authors: Michael White*, Brown University, mark Gross, Brown University , Rebecca Wang, Brown University , Carren Ginsburg, University of the Witwatersrand
Topics: Population Geography, Geography and Urban Health, Quantitative Methods
Keywords: migration, health, methods, South Africa, survey
Session Type: Paper
Day: 4/4/2019
Start / End Time: 9:55 AM / 11:35 AM
Room: Council Room, Omni, West
Presentation File: No File Uploaded

It is well-established that human migration can rapidly and radically alter population geography. At the same time, our knowledge about the spatiotemporal patterns of human resettlement—especially in rapidly urbanizing low and middle-income countries—is woefully inadequate. This paper aims to shed more light on those spatiotemporal patterns within South Africa, as a window on a more generalizable phenomenon. The paper exploits new results from the ongoing Migrant Health Follow Up Study, a 5-year cohort study of 3000 individuals, which follows migrants out of a rural origin district, and which notably builds upon a prior 20-year observation scaffold: the Agincourt Health and Demographic Surveillance System. The rich combination of demographic surveillance augmented by a new migration-and-health focused survey is positioned to better understand population resettlement, urbanization, and health in a transition setting, as well as how migrant selectivity contributes to biases in other forms of data collection. Through the process of the early stages of data collection, it has been observed that respondents in our sample are potentially much more mobile than initially anticipated and in frequent and shorter-term ways. From our initial sample of 2142 non-migrants and 909 migrants, we discover frequent return and onward moves, but more importantly, we can analyze the correlates of different movement patterns, the origin-destination links they manifest, and some of the key health consequences that emerge from differential patterns.

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