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10.1016/j.scitotenv.2020.138998 http://scihub22266oqcxt.onion/10.1016/j.scitotenv.2020.138998 32361455!7195380!32361455     free     free     free       Sci+Total+Environ 2020 ; 729 (?): 138998 Nephropedia Template TP {{tp|p=32361455|t=2020. Modelling spatial variations of coronavirus disease (COVID-19) in Africa |pdf=|usr=}}{{32361455}} gab.com Text Modelling spatial variations of coronavirus disease (COVID-19) in Africa JO: Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32361455 #FOAvip Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed. Twit Text FOAVip Modelling spatial variations of coronavirus disease (COVID-19) in Africa ????Sci Total Environ http://www.kidney.de/pget.php?&tw=1&pmid=32361455 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32361455 #FOAvip English Wikipedia <ref>{{Cite pmid|32361455}}</ref> Modelling spatial variations of coronavirus disease (COVID-19) in Africa #MMPMID32361455 Adekunle IA; Onanuga AT; Akinola OO; Ogunbanjo OW Sci Total Environ 2020[Aug]; 729 (?): 138998 PMID32361455show ga Clinical and epidemiological evidence has been advanced for human-to-human transmission of the novel coronavirus rampaging the world since late 2019. Outliers in the human-to-human transmission are yet to be explored. In this study, we examined the spatial density and leaned statistical credence to the global debate. We constructed spatial variations of clusters that examined the nexus between COVID-19 attributable deaths and confirmed cases. We rely on publicly available data on confirmed cases and death across Africa to unravel the unobserved factors, that could be responsible for the spread of COVID-19. We relied on the dynamic system generalised method of moment estimation procedure and found a ~0.045 Covid19 deaths as a result of confirmed cases in Africa. We accounted for cross-sectional dependence and found a basis for the strict orthogonal relationship. Policy measures were discussed. |*Betacoronavirus[MESH] |*Coronavirus Infections[MESH] |*Pandemics[MESH] |*Pneumonia, Viral[MESH] |Africa[MESH] |COVID-19[MESH] |Cross-Sectional Studies[MESH] |Humans[MESH]Modelling spatial variations of coronavirus disease (COVID-19) in Afri(epmc).pdf DeepDyve Pubget Overpricing