Pandemic risk of COVID-19 outbreak in the United States: An analysis of network connectedness with air travel data

Agnes TIWARI, Mike K.P. SO, Andy C.Y. CHONG, Jacky N.L. CHAN, Man Ying Amanda CHU

Research output: Contribution to journalArticlespeer-review

7 Citations (Scopus)

Abstract

Objectives: United States has become the country with the largest number of COVID-19 reported cases and deaths. This study aims to analyze the pandemic risk of COVID-19 outbreak in the US.
Methods: Time series plots of the network density, together with the daily reported confirmed COVID-19 cases and flight frequency in the five states in the US with the largest numbers of COVID-19 cases, were developed to discover the trends and patterns of the pandemic connectedness of COVID-19 among the five states.
Results: The research findings suggest that the pandemic risk of the outbreak in the US could be detected as early as the beginning of March. The signal was prior to the rapid increase of reported COVID-19 cases and flight reduction measures. Travel restriction can be strengthened at early stage of the outbreak while more focus of local public health measures can be addressed after community spread occurred.
Conclusions: The study demonstrates the application of network density on detection of the pandemic risk and its relationship with air travel restriction in order to provide useful information for policymakers to better optimize timely containment strategies to mitigate the outbreak of infectious diseases. Copyright © 2020 The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases.
Original languageEnglish
Pages (from-to)97-101
JournalInternational Journal of Infectious Diseases
Volume103
Early online date16 Nov 2020
DOIs
Publication statusPublished - Feb 2021

Citation

Tiwari, A., So, M. K. P., Chong, A. C. Y., Chan, J. N. L., & Chu, A. M. Y. (2021). Pandemic risk of COVID-19 outbreak in the United States: An analysis of network connectedness with air travel data. International Journal of Infectious Diseases, 103, 97-101. doi: 10.1016/j.ijid.2020.11.143

Keywords

  • Air traffic
  • Community transmission
  • Coronavirus
  • Network analysis
  • Pandemic connectedness

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