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10.1038/s41597-022-01263-z http://scihub22266oqcxt.onion/10.1038/s41597-022-01263-z 35413965!9005692!35413965     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Sci+Data 2022 ; 9 (1): 162 Nephropedia Template TP {{tp|p=35413965|t=2022. COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease |pdf=|usr=}}{{35413965}} gab.com Text COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease JO: Sci Data http://www.kidney.de/pget.php?&tw=1&pmid=35413965 #FOAvip This paper introduces the COVID-19 Open Dataset (COD), available at goo.gle/covid-19-open-data . A static copy is of the dataset is also available at https://doi.org/10.6084/m9.figshare.c.5399355 . This is a very large "meta-dataset" of COVID-related data, containing epidemiological information, from 22,579 unique locations within 232 different countries and independent territories. For 62 of these countries we have state-level data, and for 23 of these countries we have county-level data. For 15 countries, COD includes cases and deaths stratified by age or sex. COD also contains information on hospitalizations, vaccinations, and other relevant factors such as mobility, non-pharmaceutical interventions and static demographic attributes. Each location is tagged with a unique identifier so that these different types of information can be easily combined. The data is automatically extracted from 121 different authoritative sources, using scalable open source software. This paper describes the format and construction of the dataset, and includes a preliminary statistical analysis of its content, revealing some interesting patterns. Twit Text FOAVip COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease ????Sci Data http://www.kidney.de/pget.php?&tw=1&pmid=35413965 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35413965 #FOAvip English Wikipedia <ref>{{Cite pmid|35413965}}</ref> COVID-19 Open-Data a global-scale spatially granular meta-dataset for coronavirus disease #MMPMID35413965 Wahltinez O; Cheung A; Alcantara R; Cheung D; Daswani M; Erlinger A; Lee M; Yawalkar P; Le P; Navarro OP; Brenner MP; Murphy K Sci Data 2022[Apr]; 9 (1): 162 PMID35413965show ga This paper introduces the COVID-19 Open Dataset (COD), available at goo.gle/covid-19-open-data . A static copy is of the dataset is also available at https://doi.org/10.6084/m9.figshare.c.5399355 . This is a very large "meta-dataset" of COVID-related data, containing epidemiological information, from 22,579 unique locations within 232 different countries and independent territories. For 62 of these countries we have state-level data, and for 23 of these countries we have county-level data. For 15 countries, COD includes cases and deaths stratified by age or sex. COD also contains information on hospitalizations, vaccinations, and other relevant factors such as mobility, non-pharmaceutical interventions and static demographic attributes. Each location is tagged with a unique identifier so that these different types of information can be easily combined. The data is automatically extracted from 121 different authoritative sources, using scalable open source software. This paper describes the format and construction of the dataset, and includes a preliminary statistical analysis of its content, revealing some interesting patterns. |*COVID-19[MESH] |*SARS-CoV-2[MESH]COVID-19 Open-Data a global-scale spatially granular meta-dataset for (epmc).pdf DeepDyve Pubget Overpricing