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10.5210/ojphi.v13i1.11621 http://scihub22266oqcxt.onion/10.5210/ojphi.v13i1.11621 33936526!8075414!33936526     free     free     free Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 227.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Online+J+Public+Health+Inform 2021 ; 13 (1): e5 Nephropedia Template TP {{tp|p=33936526|t=2021. A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States |pdf=|usr=}}{{33936526}} gab.com Text A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States JO: Online J Public Health Inform http://www.kidney.de/pget.php?&tw=1&pmid=33936526 #FOAvip Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic. Twit Text FOAVip A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States ????Online J Public Health Inform http://www.kidney.de/pget.php?&tw=1&pmid=33936526 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33936526 #FOAvip English Wikipedia <ref>{{Cite pmid|33936526}}</ref> A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States #MMPMID33936526 Arling G; Blaser M; Cailas MD; Canar JR; Cooper B; Flax-Hatch J; Geraci PJ; Osiecki KM; Sambanis A Online J Public Health Inform 2021[]; 13 (1): e5 PMID33936526show ga Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic. äA Data Driven Approach for Prioritizing COVID-19 Vaccinations in the M(epmc).pdf DeepDyve Pubget Overpricing