Epidemic Risk Assessment by a Novel Communication Station Based Method

Zhaoquan Gu, Le Wang, Xiaolong Chen, Yunyi Tang, Xingang Wang, Xiaojiang Du, Mohsen Guizani, Zhihong Tian

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

The COVID-19 pandemic has caused serious consequences in the last few months and trying to control it has been the most important objective. With effective prevention and control methods, the epidemic has been gradually under control in some countries and it is essential to ensure safe work resumption in the future. Although some approaches are proposed to measure people's healthy conditions, such as filling health information forms or evaluating people's travel records, they cannot provide a fine-grained assessment of the epidemic risk. In this paper, we propose a novel epidemic risk assessment method based on the granular data collected by the communication stations. We first compute the epidemic risk of these stations in different intervals by combining the number of infected persons and the way they pass through the station. Then, we calculate the personnel risk in different intervals according to the station trajectory of the queried person. This method could assess people's epidemic risk accurately and efficiently. We also conduct extensive simulations and the results verify the effectiveness of the proposed method.

Original languageEnglish
Pages (from-to)332-344
Number of pages13
JournalIEEE Transactions on Network Science and Engineering
Volume9
Issue number1
DOIs
StatePublished - 2022

Keywords

  • COVID-19
  • communication station risk
  • epidemic risk assessment
  • personnel risk

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