Adegboye OA(1), Adekunle AI(2), Pak A(2), Gayawan E(3), Leung DH(4), Rojas DP(2), Elfaki F(5), McBryde ES(2), Eisen DP(2). Author information:
(1)Public Health & Tropical Medicine, College of Public Health, Medical and
Veterinary Sciences, James Cook University, Australia; Australian Institute of
Tropical Health and Medicine, James Cook University, Townsville, Australia.
Electronic address: [Email]
(2)Australian Institute of Tropical Health and Medicine, James Cook University,
Townsville, Australia.
(3)Biostatistics and Spatial Statistics Research Group, Department of
Statistics, Federal University of Technology, Akure, Nigeria.
(4)School of Economics, Singapore Management University, Singapore, Singapore.
(5)Department of Mathematics, Statistics and Physics, Qatar University, Doha,
Qatar.
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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