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10.1111/cars.12336 http://scihub22266oqcxt.onion/10.1111/cars.12336 33942533!8206942!33942533     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Can+Rev+Sociol 2021 ; 58 (2): 146-164 Nephropedia Template TP {{tp|p=33942533|t=2021. Studying the social determinants of COVID-19 in a data vacuum |pdf=|usr=}}{{33942533}} gab.com Text Studying the social determinants of COVID-19 in a data vacuum JO: Can Rev Sociol http://www.kidney.de/pget.php?&tw=1&pmid=33942533 #FOAvip Race-based and other demographic information on COVID-19 patients is not being collected consistently across provinces in Canada. Therefore, whether the burden of COVID-19 is falling disproportionately on the shoulders of particular demographic groups is relatively unknown. In this article, we first provide an overview of the available geographic and demographic data related to COVID-19. We then make creative use of these existing data to fill the vacuum and identify key demographic risk factors for COVID-19 across Canada's health regions. Drawing on COVID-19 counts and tabular census data, we examine the association between communities' demographic composition and the number of COVID-19 infections. COVID-19 infections are higher in communities with larger shares of Black and low-income residents. Our approach offers a way for researchers and policymakers to use existing data to identify communities nationwide that are vulnerable to the pandemic in the absence of more detailed demographic and more granular geographic data. Twit Text FOAVip Studying the social determinants of COVID-19 in a data vacuum ????Can Rev Sociol http://www.kidney.de/pget.php?&tw=1&pmid=33942533 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33942533 #FOAvip English Wikipedia <ref>{{Cite pmid|33942533}}</ref> Studying the social determinants of COVID-19 in a data vacuum #MMPMID33942533 Choi KH; Denice P; Haan M; Zajacova A Can Rev Sociol 2021[May]; 58 (2): 146-164 PMID33942533show ga Race-based and other demographic information on COVID-19 patients is not being collected consistently across provinces in Canada. Therefore, whether the burden of COVID-19 is falling disproportionately on the shoulders of particular demographic groups is relatively unknown. In this article, we first provide an overview of the available geographic and demographic data related to COVID-19. We then make creative use of these existing data to fill the vacuum and identify key demographic risk factors for COVID-19 across Canada's health regions. Drawing on COVID-19 counts and tabular census data, we examine the association between communities' demographic composition and the number of COVID-19 infections. COVID-19 infections are higher in communities with larger shares of Black and low-income residents. Our approach offers a way for researchers and policymakers to use existing data to identify communities nationwide that are vulnerable to the pandemic in the absence of more detailed demographic and more granular geographic data. |Black People/statistics & numerical data[MESH] |COVID-19/*epidemiology[MESH] |Canada/epidemiology[MESH] |Ethnicity/statistics & numerical data[MESH] |Humans[MESH] |SARS-CoV-2[MESH]Studying the social determinants of COVID-19 in a data vacuum (epmc).pdf DeepDyve Pubget Overpricing