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., Elfaki, Faiz, McBryde, Emma S., and Eisen, Damon P. (2021) Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: a modelling study. Travel Medicine and Infectious Disease, 40. 101988.

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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.


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.


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.


We showed that as the epicentre changes, the dynamics of SARS-CoV-2 spread change to reflect spatial proximities.

Item ID: 66028
Item Type: Article (Research - C1)
ISSN: 1873-0442
Keywords: COVID-19; Coronavirus; Epicentre; Spatial proximity; Travel; China; Italy; One health; Health security
Copyright Information: © 2021 Elsevier Ltd. All rights reserved.
Date Deposited: 19 Feb 2021 04:18
FoR Codes: 31 BIOLOGICAL SCIENCES > 3107 Microbiology > 310702 Infectious agents @ 33%
49 MATHEMATICAL SCIENCES > 4905 Statistics > 490507 Spatial statistics @ 34%
49 MATHEMATICAL SCIENCES > 4901 Applied mathematics > 490102 Biological mathematics @ 33%
SEO Codes: 20 HEALTH > 2004 Public health (excl. specific population health) > 200404 Disease distribution and transmission (incl. surveillance and response) @ 100%
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