Pandemic risk of COVID-19 outbreak in the United States: An analysis of network connectedness with air travel data
| Autor: | Amanda M. Y. Chu, Mike K. P. So, Jacky N.L. Chan, Agnes Tiwari, Andy Chun Yin Chong |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
0301 basic medicine
Microbiology (medical) medicine.medical_specialty Coronavirus disease 2019 (COVID-19) Social connectedness 030106 microbiology Article lcsh:Infectious and parasitic diseases Disease Outbreaks 03 medical and health sciences 0302 clinical medicine Environmental health Pandemic Community transmission medicine Humans lcsh:RC109-216 030212 general & internal medicine Air travel Pandemic connectedness SARS-CoV-2 Public health Outbreak food and beverages COVID-19 General Medicine Air traffic control Research findings United States Coronavirus Geography Air Travel Infectious Diseases Air traffic Network analysis |
| Zdroj: | International Journal of Infectious Diseases International Journal of Infectious Diseases, Vol 103, Iss, Pp 97-101 (2021) |
| ISSN: | 1201-9712 |
| DOI: | 10.1016/j.ijid.2020.11.143 |
| Popis: | Highlights • Time series plot of network density can serve as early detection of pandemic development. • Pandemic progression can be tracked through the association of network density and air travel data. • The application of network density on detection of the pandemic risk and its association with the air travel data may help optimize timely containment strategies to mitigate the outbreak of infectious diseases. 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. |
| Databáze: | OpenAIRE |
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