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

• Published in: International journal of infectious diseases Vol. 103; pp. 97 - 101
• Main Authors: Tiwari, Agnes, So, Mike K.P., Chong, Andy C.Y., Chan, Jacky N.L., Chu, Amanda M.Y.
• Format: Journal Article
• Language: English
• Published: Canada Elsevier Ltd 01-02-2021; The Author(s). Published by Elsevier Ltd on behalf of International Society for Infectious Diseases; Elsevier
• Subjects: Air traffic; Air Travel; Community transmission; Coronavirus; COVID-19 - epidemiology; Disease Outbreaks; Humans; Network analysis; Pandemic connectedness; SARS-CoV-2; United States - epidemiology; United States; Pandemic connectedness; Coronavirus; Air traffic; Network analysis; Community transmission
• ISSN: 1201-9712; 1878-3511
• DOI: 10.1016/j.ijid.2020.11.143

The 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.
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.
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 an early stage of the outbreak while more focus of local public health measures can be addressed after community spread.
The study demonstrates the application of network density on detection of 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.