Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1016/j.cegh.2020.08.017 http://scihub22266oqcxt.onion/10.1016/j.cegh.2020.08.017 32901227!7470821!32901227     free     free     free Deprecated: Implicit conversion from float 219.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\32901227.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Clin+Epidemiol+Glob+Health 2021 ; 9 (ä): 204-215 Nephropedia Template TP {{tp|p=32901227|t=2021. COVID-19: District level vulnerability assessment in India |pdf=|usr=}}{{32901227}} gab.com Text COVID-19: District level vulnerability assessment in India JO: Clin Epidemiol Glob Health http://www.kidney.de/pget.php?&tw=1&pmid=32901227 #FOAvip OBJECTIVES: COVID-19 Pandemic has brought a threatening challenge to the world and as well as for Indian society and economy. In India, it has become a public health disaster and its' intensity increasing continuously. For the disaster risk reduction, and capacity building against the COVID-19 pandemic understanding of the relationship between socio-environmental conditions with the pandemic is very necessary. The objective of the present work is to construct a socio-environmental vulnerability index of the potential risk of community spread of COVID-19 using socio-economic and environmental variables. METHODOLOGY: In this, cross-sectional study principal component analyses have been used to drive SoEVI. 4 uncorrelated sub-index has been extracted from 16 sub-indicators which reflects 59% of the variance. Aggregation of 4 Sub-Index has been done to obtain the final vulnerability Index. RESULTS: Results show that there is spatial variability in vulnerability based on environmental and socio-economic conditions. Districts of north and central India found more vulnerable then south India. Statistical significance has been tested using regression analysis, positive relation has been found between vulnerability index and confirmed and active cases. CONCLUSION: The vulnerability index has highlighted environmentaly and socioeconomicallybackward districts. These areas will suffer more critical problems against COVID-19 pandemic for their socio-environmental problem. Twit Text FOAVip COVID-19: District level vulnerability assessment in India ????Clin Epidemiol Glob Health http://www.kidney.de/pget.php?&tw=1&pmid=32901227 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32901227 #FOAvip English Wikipedia <ref>{{Cite pmid|32901227}}</ref> COVID-19: District level vulnerability assessment in India #MMPMID32901227 Sarkar A; Chouhan P Clin Epidemiol Glob Health 2021[Jan]; 9 (ä): 204-215 PMID32901227show ga OBJECTIVES: COVID-19 Pandemic has brought a threatening challenge to the world and as well as for Indian society and economy. In India, it has become a public health disaster and its' intensity increasing continuously. For the disaster risk reduction, and capacity building against the COVID-19 pandemic understanding of the relationship between socio-environmental conditions with the pandemic is very necessary. The objective of the present work is to construct a socio-environmental vulnerability index of the potential risk of community spread of COVID-19 using socio-economic and environmental variables. METHODOLOGY: In this, cross-sectional study principal component analyses have been used to drive SoEVI. 4 uncorrelated sub-index has been extracted from 16 sub-indicators which reflects 59% of the variance. Aggregation of 4 Sub-Index has been done to obtain the final vulnerability Index. RESULTS: Results show that there is spatial variability in vulnerability based on environmental and socio-economic conditions. Districts of north and central India found more vulnerable then south India. Statistical significance has been tested using regression analysis, positive relation has been found between vulnerability index and confirmed and active cases. CONCLUSION: The vulnerability index has highlighted environmentaly and socioeconomicallybackward districts. These areas will suffer more critical problems against COVID-19 pandemic for their socio-environmental problem. äCOVID-19: District level vulnerability assessment in India (epmc).pdf DeepDyve Pubget Overpricing