ArticleEnvironment and planning. B, urban analytics and city science2023
Using mobile phone big data to discover the spatial patterns of rural migrant workers' return to work in China's three urban agglomerations in the post-COVID-19 era.
Article in Environment and planning. B, urban analytics and city science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Analysis of cross-provincial healthcare utilization among hospitalized patients in a tertiary Chinese medicine hospital.Frontiers in public health · 2026Article
- A data-driven framework to assess population dynamics during novel coronavirus outbreaks: A case study on Xiamen Island, China.PloS one · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
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Abstract
Knowing how workers return to work is a key policymaking issue for economic recovery in the post-COVID-19 era. This paper uses country-wide time-series mobile phone big data (comparing monthly and annual figures), obtained between February 2019 and October 2019 and between February 2020 and October 2020, to discover the spatial patterns of rural migrant workers' (RMWs') return to work in China's three urban agglomerations (UAs): the Beijing-Tianjin-Hebei Region, the Yangtze River Delta and the Pearl River Delta. Spatial patterns of RMWs' return to work and how these patterns vary with location, city level and human attribute were investigated using the fine-scale social sensing related to post-pandemic human mobility. The results confirmed the multidimensional spatiotemporal differentiations, interaction effects between variable pairs and effects of the actual situation on the changing patterns of RMWs' return to work. The spatial patterns of RMWs' return to work in China's major three UAs can be regarded as a comprehensive and complex interaction result accompanying the nationwide population redistribution, which was affected by various hidden factors. Our findings provide crucial implications and suggestions for data-informed policy decisions for a harmonious society in the post-COVID-19 era.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.