ArticleFrontiers in public health2021
Work Resumption Rate and Migrant Workers' Income During the COVID-19 Pandemic.
Article in Frontiers in public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Article
- Post COVID-19 pandemic recovery of intracity human mobility in Wuhan: Spatiotemporal characteristic and driving mechanism.Travel behaviour & society · 2023Article
- Point and interval prediction of crude oil futures prices based on chaos theory and multiobjective slime mold algorithm.Annals of operations research · 2022Article
- Differences in service and antibiotics use following symptomatic respiratory tract infections between 2016 and 2021 in rural Anhui, China.Epidemiology and infection · 2022Article
- Social Integration and Health Among Young Migrants in China: Mediated by Social Mentality and Moderated by Gender.Frontiers in psychology · 2022Article
- Spatiotemporal patterns of the COVID-19 control measures impact on industrial production in Wuhan using time-series earth observation data.Sustainable cities and society · 2021Article
- Incentive Preferences and Its Related Factors Among Primary Medical Staff in Anhui Province, China: A Cross-Sectional Study.Frontiers in public health · 2021Article
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6 authors.
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Abstract
The COVID-19 public health crisis has quickly led to an economic crisis, impacting many people and businesses in the world. This study examines how the pandemic affects workforces and workers' income. We quantify the impact of staggered resumption of work, after the coronavirus lockdowns, on the migrant workers' income. Using data on population movements of 366 Chinese cities at the daily level from the Baidu Maps-Migration Big Data Platform and historical data on the average monthly income of migrant workers, we find that the average work resumption rate (WRR) during the period of the Chinese Lantern Festival was 25.25%, which was only 30.67% of that in the same matched lunar calendar period in 2019. We then apply Gray Model First Order One Variable [GM (1, 1)] to predict the monthly income of migrant workers during the period of the COVID-19 pandemic. We show that, if without the influence of the COVID-19 pandemic, the average monthly income of migrant workers in 2020 will be expected to increase by 12% compared with 2019. We further conduct scenario analysis and show that the average monthly income of migrant workers in 2020 under the conservative scenario (COS), medium scenario (MES), and worse scenario (WOS) will be predicted to decrease by 2, 21, and 44%, respectively. Through testing, our prediction error is <5%. Our findings will help policymakers to decide when and how they implement a plan to ease the coronavirus lockdown and related financial support policies.
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