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An Investigation of Containment Measures Against the COVID-19 Pandemic in Mainland China (2007.08254v2)

Published 16 Jul 2020 in physics.soc-ph and cs.SI

Abstract: As the recent COVID-19 outbreak rapidly expands all over the world, various containment measures have been carried out to fight against the COVID-19 pandemic. In Mainland China, the containment measures consist of three types, i.e., Wuhan travel ban, intra-city quarantine and isolation, and inter-city travel restriction. In order to carry out the measures, local economy and information acquisition play an important role. In this paper, we investigate the correlation of local economy and the information acquisition on the execution of containment measures to fight against the COVID-19 pandemic in Mainland China. First, we use a parsimonious model, i.e., SIR-X model, to estimate the parameters, which represent the execution of intra-city quarantine and isolation in major cities of Mainland China. In order to understand the execution of intra-city quarantine and isolation, we analyze the correlation between the representative parameters including local economy, mobility, and information acquisition. To this end, we collect the data of Gross Domestic Product (GDP), the inflows from Wuhan and outflows, and the COVID-19 related search frequency from a widely-used Web mapping service, i.e., Baidu Maps, and Web search engine, i.e., Baidu Search Engine, in Mainland China. Based on the analysis, we confirm the strong correlation between the local economy and the execution of information acquisition in major cities of Mainland China. We further evidence that, although the cities with high GDP per capita attracts bigger inflows from Wuhan, people are more likely to conduct the quarantine measure and to reduce going out to other cities. Finally, the correlation analysis using search data shows that well-informed individuals are likely to carry out containment measures.

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Authors (8)
  1. Ji Liu (285 papers)
  2. Xiakai Wang (1 paper)
  3. Haoyi Xiong (98 papers)
  4. Jizhou Huang (26 papers)
  5. Siyu Huang (50 papers)
  6. Haozhe An (13 papers)
  7. Dejing Dou (112 papers)
  8. Haifeng Wang (194 papers)
Citations (12)

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