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On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics

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 closed populations using Susceptible-Infection-Rec...

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Autores principales: So, Mike K. P., Chu, Amanda M. Y., Tiwari, Agnes, Chan, Jacky N. L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933279/
https://www.ncbi.nlm.nih.gov/pubmed/33664280
http://dx.doi.org/10.1038/s41598-021-84094-z
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author So, Mike K. P.
Chu, Amanda M. Y.
Tiwari, Agnes
Chan, Jacky N. L.
author_facet So, Mike K. P.
Chu, Amanda M. Y.
Tiwari, Agnes
Chan, Jacky N. L.
author_sort So, Mike K. P.
collection PubMed
description 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 closed populations using Susceptible-Infection-Recovered modeling, the investigation of the effect from worldwide pandemic cannot be neglected. This study proposes a network analysis to assess global pandemic risk by linking 164 countries in pandemic networks, where links between countries were specified by the level of ‘co-movement’ of newly confirmed COVID-19 cases. More countries showing increase in the COVID-19 cases simultaneously will signal the pandemic prevalent over the world. The network density, clustering coefficients, and assortativity in the pandemic networks provide early warning signals of the pandemic in late February 2020. We propose a preparedness pandemic risk score for prediction and a severity risk score for pandemic control. The preparedness risk score contributed by countries in Asia is between 25% and 50% most of the time after February and America contributes around 40% in July 2020. The high preparedness risk contribution implies the importance of travel restrictions between those countries. The severity risk score of America and Europe contribute around 90% in December 2020, signifying that the control of COVID-19 is still worrying in America and Europe. We can keep track of the pandemic situation in each country using an online dashboard to update the pandemic risk scores and contributions.
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spelling pubmed-79332792021-03-08 On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics So, Mike K. P. Chu, Amanda M. Y. Tiwari, Agnes Chan, Jacky N. L. Sci Rep Article 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 closed populations using Susceptible-Infection-Recovered modeling, the investigation of the effect from worldwide pandemic cannot be neglected. This study proposes a network analysis to assess global pandemic risk by linking 164 countries in pandemic networks, where links between countries were specified by the level of ‘co-movement’ of newly confirmed COVID-19 cases. More countries showing increase in the COVID-19 cases simultaneously will signal the pandemic prevalent over the world. The network density, clustering coefficients, and assortativity in the pandemic networks provide early warning signals of the pandemic in late February 2020. We propose a preparedness pandemic risk score for prediction and a severity risk score for pandemic control. The preparedness risk score contributed by countries in Asia is between 25% and 50% most of the time after February and America contributes around 40% in July 2020. The high preparedness risk contribution implies the importance of travel restrictions between those countries. The severity risk score of America and Europe contribute around 90% in December 2020, signifying that the control of COVID-19 is still worrying in America and Europe. We can keep track of the pandemic situation in each country using an online dashboard to update the pandemic risk scores and contributions. Nature Publishing Group UK 2021-03-04 /pmc/articles/PMC7933279/ /pubmed/33664280 http://dx.doi.org/10.1038/s41598-021-84094-z Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
So, Mike K. P.
Chu, Amanda M. Y.
Tiwari, Agnes
Chan, Jacky N. L.
On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title_full On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title_fullStr On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title_full_unstemmed On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title_short On topological properties of COVID-19: predicting and assessing pandemic risk with network statistics
title_sort on topological properties of covid-19: predicting and assessing pandemic risk with network statistics
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7933279/
https://www.ncbi.nlm.nih.gov/pubmed/33664280
http://dx.doi.org/10.1038/s41598-021-84094-z
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