Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study
Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the in...
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sg-smu-ink.soe_research-34622021-04-08T07:45:36Z Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study Adegboye, Oyelola A. Adekunle, Adeshina I. Pak, Anton Gayawan, Ezra LEUNG, Denis H. Y. Rojas, Diana P. McBryde, Emma S. Eisen, Damon P. Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 worldwide. Methods: Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19. Pearson's correlation, semi-variogram, and Moran's Index were used to examine the association and spatial autocorrelation between the number of COVID-19 cases and travel influx (and arrival time) from the source country. Results: We found significant negative association between disease arrival time and number of cases imported from Italy (r = −0.43, p = 0.004) and significant positive association between the number of COVID-19 cases and daily travel influx from Italy (r = 0.39, p = 0.011). Using bivariate Moran's Index analysis, we found evidence of spatial interaction between COVID-19 cases and travel influx (Moran's I = 0.340). Asia-Pacific region is at higher/extreme risk of disease importation from the Chinese epicentre, whereas the rest of Europe, South-America and Africa are more at risk from the Italian epicentre. Conclusion: We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities. 2021-03-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/soe_research/2463 info:doi/10.1016/j.tmaid.2021.101988 https://ink.library.smu.edu.sg/context/soe_research/article/3462/viewcontent/ChangeInOutbreak_Epicentre_pvoa.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Economics eng Institutional Knowledge at Singapore Management University China Coronavirus COVID-19 Epicentre Health security Italy One health Spatial proximity Travel Econometrics Health Economics Public Health |
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China Coronavirus COVID-19 Epicentre Health security Italy One health Spatial proximity Travel Econometrics Health Economics Public Health Adegboye, Oyelola A. Adekunle, Adeshina I. Pak, Anton Gayawan, Ezra LEUNG, Denis H. Y. Rojas, Diana P. McBryde, Emma S. Eisen, Damon P. Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
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Background: The outbreak of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that was first detected in the city of Wuhan, China has now spread to every inhabitable continent, but now the attention has shifted from China to other epicentres. This study explored early assessment of the influence of spatial proximities and travel patterns from Italy on the further spread of SARS-CoV-2 worldwide. Methods: Using data on the number of confirmed cases of COVID-19 and air travel data between countries, we applied a stochastic meta-population model to estimate the global spread of COVID-19. Pearson's correlation, semi-variogram, and Moran's Index were used to examine the association and spatial autocorrelation between the number of COVID-19 cases and travel influx (and arrival time) from the source country. Results: We found significant negative association between disease arrival time and number of cases imported from Italy (r = −0.43, p = 0.004) and significant positive association between the number of COVID-19 cases and daily travel influx from Italy (r = 0.39, p = 0.011). Using bivariate Moran's Index analysis, we found evidence of spatial interaction between COVID-19 cases and travel influx (Moran's I = 0.340). Asia-Pacific region is at higher/extreme risk of disease importation from the Chinese epicentre, whereas the rest of Europe, South-America and Africa are more at risk from the Italian epicentre. Conclusion: We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities. |
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text |
author |
Adegboye, Oyelola A. Adekunle, Adeshina I. Pak, Anton Gayawan, Ezra LEUNG, Denis H. Y. Rojas, Diana P. McBryde, Emma S. Eisen, Damon P. |
author_facet |
Adegboye, Oyelola A. Adekunle, Adeshina I. Pak, Anton Gayawan, Ezra LEUNG, Denis H. Y. Rojas, Diana P. McBryde, Emma S. Eisen, Damon P. |
author_sort |
Adegboye, Oyelola A. |
title |
Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
title_short |
Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
title_full |
Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
title_fullStr |
Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
title_full_unstemmed |
Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |
title_sort |
change in outbreak epicentre and its impact on the importation risks of covid-19 progression: a modelling study |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2021 |
url |
https://ink.library.smu.edu.sg/soe_research/2463 https://ink.library.smu.edu.sg/context/soe_research/article/3462/viewcontent/ChangeInOutbreak_Epicentre_pvoa.pdf |
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1770575646665211904 |