Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Jacky N.L. Chan"'
Publikováno v:
International Journal of Infectious Diseases, Vol 103, Iss , Pp 97-101 (2021)
Objectives: 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. Methods: Time series plots of the network density, togeth
Externí odkaz:
https://doaj.org/article/d1a7e09fd20b4d03a64ae927310731ab
Publikováno v:
International Journal of Infectious Diseases, Vol 96, Iss , Pp 558-561 (2020)
With the domestic and international spread of the coronavirus disease 2019 (COVID-19), much attention has been given to estimating pandemic risk. We propose the novel application of a well-established scientific approach – the network analysis –
Externí odkaz:
https://doaj.org/article/ea210505af0f478c9fce23ccb44a2848
Publikováno v:
International Journal of Infectious Diseases
International Journal of Infectious Diseases, Vol 103, Iss, Pp 97-101 (2021)
International Journal of Infectious Diseases, Vol 103, Iss, Pp 97-101 (2021)
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
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c1a9cf011a25a73241feafcdb405820d
Publikováno v:
Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
Scientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
The spread of coronavirus disease 2019 (COVID-19) has caused more than 80 million confirmed infected cases and more than 1.8 million people died as of 31 December 2020. While it is essential to quantify risk and characterize transmission dynamics in
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4868543ed2b1a09073bd74e91a714f63
https://pubmed.ncbi.nlm.nih.gov/33664280
https://pubmed.ncbi.nlm.nih.gov/33664280
The spread of coronavirus disease 2019 (COVID-19) has caused more than 24 million confirmed infected cases and more than 800,000 people died as of 28 August 2020. While it is essential to quantify risk and characterize transmission dynamics in closed
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::859717e60aca1aec83abc513538a7607
https://doi.org/10.1101/2020.09.17.20197020
https://doi.org/10.1101/2020.09.17.20197020
Publikováno v:
Journal of Travel Medicine
We analyze the COVID-19 pandemic development in Latin America by network analysis to demonstrate the effectiveness of air travel restriction in reducing pandemic risk and provide risk analysis for air travel reopening in Latin America. We reinforce t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1d2261da613152a1d1c34514234f976d
https://pubmed.ncbi.nlm.nih.gov/32970124
https://pubmed.ncbi.nlm.nih.gov/32970124
Publikováno v:
International Journal of Infectious Diseases
International Journal of Infectious Diseases, Vol 96, Iss, Pp 558-561 (2020)
International Journal of Infectious Diseases, Vol 96, Iss, Pp 558-561 (2020)
Highlights • A novel application of network analysis in healthcare • Providing a direct visualisation of the COVID-19 pandemic risk • Visualisation of the pandemic risk through the degree of connectedness • Presenting a general network concep
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb249ccb87156ff96bf2475c3d46d40e
Publikováno v:
JMIR Public Health and Surveillance
JMIR Public Health and Surveillance, Vol 7, Iss 3, p e27317 (2021)
JMIR Public Health and Surveillance, Vol 7, Iss 3, p e27317 (2021)
Communicable diseases including COVID-19 pose a major threat to public health worldwide. To curb the spread of communicable diseases effectively, timely surveillance and prediction of the risk of pandemics are essential. The aim of this study is to a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::49f323379690bb8d9d740f3be2ee3d82
https://doi.org/10.2196/27317
https://doi.org/10.2196/27317