Department of Biological Sciences, Eck Institute for Global Health, University of Notre Dame, Notre Dame, Indiana, United States of America.
School of Geography and Environmental Science, WorldPop, University of Southampton, Southampton, England, United Kingdom.
PLoS One. 2020 May 7;15(5):e0232702. doi: 10.1371/journal.pone.0232702. eCollection 2020.
Human mobility, both short and long term, are important considerations in the study of numerous systems. Economic and technological advances have led to a more interconnected global community, further increasing the need for considerations of human mobility. While data on human mobility are better recorded in many developed countries, availability of such data remains limited in many low- and middle-income countries around the world, particularly at the fine temporal and spatial scales required by many applications. In this study, we used 5-year census-based internal migration microdata for 32 departments in Colombia (i.e., Admin-1 level) to develop a novel spatial interaction modeling approach for estimating migration, at a finer spatial scale, among the 1,122 municipalities in the country (i.e., Admin-2 level). Our modeling approach addresses a significant lack of migration data at administrative unit levels finer than those at which migration data are typically recorded. Due to the widespread availability of census-based migration microdata at the Admin-1 level, our modeling approach opens up for the possibilities of modeling migration patterns at Admin-2 and Admin-3 levels across many other countries where such data are currently lacking.
人口流动，无论是短期还是长期，都是许多系统研究中的重要考虑因素。经济和技术的进步使全球社区更加互联互通，进一步增加了对人口流动考虑的需求。虽然在许多发达国家更好地记录了人口流动数据，但在世界各地的许多低收入和中等收入国家，这种数据的可用性仍然有限，特别是在许多应用程序所需的精细时间和空间尺度上。在这项研究中，我们使用了哥伦比亚 32 个部门（即行政一级）基于人口普查的 5 年内部迁移微观数据，开发了一种新的空间相互作用建模方法，用于在该国 1122 个市（即行政二级）之间以更精细的空间尺度估算迁移。我们的建模方法解决了在行政单位级别上缺乏迁移数据的问题，这些数据比通常记录迁移数据的级别更精细。由于在行政一级广泛提供基于人口普查的迁移微观数据，因此我们的建模方法为在许多其他目前缺乏此类数据的国家/地区在行政二级和三级建模迁移模式提供了可能性。
