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10.34172/ijhpm.2020.115 http://scihub22266oqcxt.onion/10.34172/ijhpm.2020.115 32654431!7719203!32654431     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Health+Policy+Manag 2020 ; 9 (11): 469-474 Nephropedia Template TP {{tp|p=32654431|t=2020. How to Minimize the Impact of Pandemic Events: Lessons From the COVID-19 Crisis |pdf=|usr=}}{{32654431}} gab.com Text How to Minimize the Impact of Pandemic Events: Lessons From the COVID-19 Crisis JO: Int J Health Policy Manag http://www.kidney.de/pget.php?&tw=1&pmid=32654431 #FOAvip Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current pandemic of coronavirus disease 2019 (COVID-19). This pandemic is characterized by a high variability in death rate (defined as the ratio between the number of deaths and the total number of infected people) across world countries. Several possible explanations have been proposed, but it is not clear whether this variability is due to a single predominant factor or instead to multiple causes. Here we addressed this issue using multivariable regression analysis to test the impact of the following factors: the hospital stress (defined as the ratio between the number of infected cases and the total number of hospital beds), the population median age, and the quality of the National Health System (NHS). For this analysis, we chose countries of the world with over 3000 infected cases as of April 1, 2020. Hospital stress was found to be the crucial factor in explaining the variability of death rate, while the others had negligible relevance. Different procedures for quantifying cases of infection and death for COVID-19 could affect the variability in death rate across countries. We therefore applied the same statistical approach to Italy, which is divided into 20 Regions that share the same protocol for counting the outcomes of this pandemic. Correlation between hospital stress and death rate was even stronger than that observed for countries of the world. Based on our findings and the historical trend for the availability of hospital beds, we propose guidelines for policy-makers to properly manage future pandemics. Twit Text FOAVip How to Minimize the Impact of Pandemic Events: Lessons From the COVID-19 Crisis ????Int J Health Policy Manag http://www.kidney.de/pget.php?&tw=1&pmid=32654431 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32654431 #FOAvip English Wikipedia <ref>{{Cite pmid|32654431}}</ref> How to Minimize the Impact of Pandemic Events: Lessons From the COVID-19 Crisis #MMPMID32654431 Bigiani L; Bigiani S; Bigiani A Int J Health Policy Manag 2020[Nov]; 9 (11): 469-474 PMID32654431show ga Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current pandemic of coronavirus disease 2019 (COVID-19). This pandemic is characterized by a high variability in death rate (defined as the ratio between the number of deaths and the total number of infected people) across world countries. Several possible explanations have been proposed, but it is not clear whether this variability is due to a single predominant factor or instead to multiple causes. Here we addressed this issue using multivariable regression analysis to test the impact of the following factors: the hospital stress (defined as the ratio between the number of infected cases and the total number of hospital beds), the population median age, and the quality of the National Health System (NHS). For this analysis, we chose countries of the world with over 3000 infected cases as of April 1, 2020. Hospital stress was found to be the crucial factor in explaining the variability of death rate, while the others had negligible relevance. Different procedures for quantifying cases of infection and death for COVID-19 could affect the variability in death rate across countries. We therefore applied the same statistical approach to Italy, which is divided into 20 Regions that share the same protocol for counting the outcomes of this pandemic. Correlation between hospital stress and death rate was even stronger than that observed for countries of the world. Based on our findings and the historical trend for the availability of hospital beds, we propose guidelines for policy-makers to properly manage future pandemics. |Bed Occupancy/*statistics & numerical data[MESH] |COVID-19/*epidemiology[MESH] |Humans[MESH] |Internationality[MESH] |Pandemics/*statistics & numerical data[MESH]How to Minimize the Impact of Pandemic Events: Lessons From the COVID-(epmc).pdf DeepDyve Pubget Overpricing