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10.7759/cureus.8440 http://scihub22266oqcxt.onion/10.7759/cureus.8440 32523858!7273387!32523858     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cureus 2020 ; 12 (6): e8440 Nephropedia Template TP {{tp|p=32523858|t=2020. Epidemiological Determinants of COVID-19-Related Patient Outcomes in Different Countries and Plan of Action: A Retrospective Analysis |pdf=|usr=}}{{32523858}} gab.com Text Epidemiological Determinants of COVID-19-Related Patient Outcomes in Different Countries and Plan of Action: A Retrospective Analysis JO: Cureus http://www.kidney.de/pget.php?&tw=1&pmid=32523858 #FOAvip Current development around the pandemic of novel coronavirus disease 2019 (COVID-19) presents a significant healthcare resource burden threatening to overwhelm the available nationwide healthcare infrastructure. It is essential to consider, especially for resource-limited nations, strategizing the coordinated response to handle this crisis effectively and preparing for the upcoming emergence of calamity caused by this yet-to-know disease entity. Relevant epidemiological data were retrieved from currently available online reports related to COVID-19 patients. The correlation coefficient was calculated by plotting dependant variables - the number of COVID-19 cases and the number of deaths due to COVID 19 on the Y-axis and independent variables - critical-care beds per capita, the median age of the population of the country, the number of COVID-19 tests per million population, population density (persons per square km), urban population percentage, and gross domestic product (GDP) expense on health care - on the X-axis. After analyzing the data, both the fatality rate and the total number of COVID-19 cases were found to have an inverse association with the population density with the variable - the number of cases of COVID-19 - achieving a statistical significance (p-value 0.01). The negative correlation between critical care beds and the fatality rate is well-justified, as intensive care unit (ICU) beds and ventilators are the critical elements in the management of complicated cases. There was also a significant positive correlation between GDP expenses on healthcare by a country and the number of COVID-19 cases being registered (p-value 0.008), although that did not affect mortality (p-value 0.851). This analysis discusses the overview of various epidemiological determinants possibly contributing to the variation in patient outcomes across regions and helps improve our understanding to develop a plan of action and effective control measures in the future. Twit Text FOAVip Epidemiological Determinants of COVID-19-Related Patient Outcomes in Different Countries and Plan of Action: A Retrospective Analysis ????Cureus http://www.kidney.de/pget.php?&tw=1&pmid=32523858 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32523858 #FOAvip English Wikipedia <ref>{{Cite pmid|32523858}}</ref> Epidemiological Determinants of COVID-19-Related Patient Outcomes in Different Countries and Plan of Action: A Retrospective Analysis #MMPMID32523858 Roy S; Khalse M Cureus 2020[Jun]; 12 (6): e8440 PMID32523858show ga Current development around the pandemic of novel coronavirus disease 2019 (COVID-19) presents a significant healthcare resource burden threatening to overwhelm the available nationwide healthcare infrastructure. It is essential to consider, especially for resource-limited nations, strategizing the coordinated response to handle this crisis effectively and preparing for the upcoming emergence of calamity caused by this yet-to-know disease entity. Relevant epidemiological data were retrieved from currently available online reports related to COVID-19 patients. The correlation coefficient was calculated by plotting dependant variables - the number of COVID-19 cases and the number of deaths due to COVID 19 on the Y-axis and independent variables - critical-care beds per capita, the median age of the population of the country, the number of COVID-19 tests per million population, population density (persons per square km), urban population percentage, and gross domestic product (GDP) expense on health care - on the X-axis. After analyzing the data, both the fatality rate and the total number of COVID-19 cases were found to have an inverse association with the population density with the variable - the number of cases of COVID-19 - achieving a statistical significance (p-value 0.01). The negative correlation between critical care beds and the fatality rate is well-justified, as intensive care unit (ICU) beds and ventilators are the critical elements in the management of complicated cases. There was also a significant positive correlation between GDP expenses on healthcare by a country and the number of COVID-19 cases being registered (p-value 0.008), although that did not affect mortality (p-value 0.851). This analysis discusses the overview of various epidemiological determinants possibly contributing to the variation in patient outcomes across regions and helps improve our understanding to develop a plan of action and effective control measures in the future. äEpidemiological Determinants of COVID-19-Related Patient Outcomes in D(epmc).pdf DeepDyve Pubget Overpricing