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10.4081/gh.2021.985 http://scihub22266oqcxt.onion/10.4081/gh.2021.985 34000790!ä!34000790 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Geospat+Health 2021 ; 16 (1): ä Nephropedia Template TP {{tp|p=34000790|t=2021. Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach |pdf=|usr=}}{{34000790}} gab.com Text Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach JO: Geospat Health http://www.kidney.de/pget.php?&tw=1&pmid=34000790 #FOAvip Local, bivariate relationships between coronavirus 2019 (COVID-19) infection rates and a set of demographic and socioeconomic variables were explored at the district level in Oman. To limit multicollinearity a principal component analysis was conducted, the results of which showed that three components together could explain 65% of the total variance that were therefore subjected to further study. Comparison of a generalized linear model (GLM) and geographically weighted regression (GWR) indicated an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local coefficient of determination (R2) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, including percentages of Omani and non-Omani population at various age levels; spatial interaction; population density; number of hospital beds; total number of households; purchasing power; and purchasing power per km2. No direct correlation between COVID- 19 rates and health facilities distribution or tobacco usage. This study suggests that Poisson regression using GWR and GLM can address unobserved spatial non-stationary relationships. Findings of this study can promote current understanding of the demographic and socioeconomic variables impacting the spatial patterns of COVID-19 in Oman, allowing local and national authorities to adopt more appropriate strategies to cope with this pandemic in the future and also to allocate more effective prevention resources. Twit Text FOAVip Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach ????Geospat Health http://www.kidney.de/pget.php?&tw=1&pmid=34000790 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34000790 #FOAvip English Wikipedia <ref>{{Cite pmid|34000790}}</ref> Demographic and socioeconomic determinants of COVID-19 across Oman - A geospatial modelling approach #MMPMID34000790 Al Kindi KM; Al-Mawali A; Akharusi A; Alshukaili D; Alnasiri N; Al-Awadhi T; Charabi Y; El Kenawy AM Geospat Health 2021[May]; 16 (1): ä PMID34000790show ga Local, bivariate relationships between coronavirus 2019 (COVID-19) infection rates and a set of demographic and socioeconomic variables were explored at the district level in Oman. To limit multicollinearity a principal component analysis was conducted, the results of which showed that three components together could explain 65% of the total variance that were therefore subjected to further study. Comparison of a generalized linear model (GLM) and geographically weighted regression (GWR) indicated an improvement in model performance using GWR (goodness of fit=93%) compared to GLM (goodness of fit=86%). The local coefficient of determination (R2) showed a significant influence of specific demographic and socioeconomic factors on COVID-19, including percentages of Omani and non-Omani population at various age levels; spatial interaction; population density; number of hospital beds; total number of households; purchasing power; and purchasing power per km2. No direct correlation between COVID- 19 rates and health facilities distribution or tobacco usage. This study suggests that Poisson regression using GWR and GLM can address unobserved spatial non-stationary relationships. Findings of this study can promote current understanding of the demographic and socioeconomic variables impacting the spatial patterns of COVID-19 in Oman, allowing local and national authorities to adopt more appropriate strategies to cope with this pandemic in the future and also to allocate more effective prevention resources. |*COVID-19[MESH] |Humans[MESH] |Oman/epidemiology[MESH] |Pandemics[MESH] |SARS-CoV-2[MESH]Demographic and socioeconomic determinants of COVID-19 across Oman - A(epmc).pdf DeepDyve Pubget Overpricing