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10.1016/j.tmaid.2021.101988 http://scihub22266oqcxt.onion/10.1016/j.tmaid.2021.101988 33578044!7871106!33578044     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Travel+Med+Infect+Dis 2021 ; 40 (ä): 101988 Nephropedia Template TP {{tp|p=33578044|t=2021. Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study |pdf=|usr=}}{{33578044}} gab.com Text Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study JO: Travel Med Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=33578044 #FOAvip 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. Twit Text FOAVip Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study ????Travel Med Infect Dis http://www.kidney.de/pget.php?&tw=1&pmid=33578044 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33578044 #FOAvip English Wikipedia <ref>{{Cite pmid|33578044}}</ref> Change in outbreak epicentre and its impact on the importation risks of COVID-19 progression: A modelling study #MMPMID33578044 Adegboye OA; Adekunle AI; Pak A; Gayawan E; Leung DH; Rojas DP; Elfaki F; McBryde ES; Eisen DP Travel Med Infect Dis 2021[Mar]; 40 (ä): 101988 PMID33578044show ga 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. |*Models, Statistical[MESH] |Air Travel/statistics & numerical data[MESH] |COVID-19/*epidemiology[MESH] |China/epidemiology[MESH] |Communicable Diseases, Imported/*epidemiology[MESH] |Humans[MESH] |Italy/epidemiology[MESH] |Population Surveillance[MESH] |Risk[MESH] |SARS-CoV-2/isolation & purification[MESH]Change in outbreak epicentre and its impact on the importation risks o(epmc).pdf DeepDyve Pubget Overpricing