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10.1016/j.compchemeng.2020.106945 http://scihub22266oqcxt.onion/10.1016/j.compchemeng.2020.106945 C7271874!7271874 !32565584     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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\32565584 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Comput+Chem+Eng 2020 ; 140 (ä): 106945 Nephropedia Template TP {{tp|p=32565584 |t=2020. A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic |pdf=|usr=}}{{32565584 }} gab.com Text A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic JO: Comput Chem Eng http://www.kidney.de/pget.php?&tw=1&pmid=32565584 #FOAvip The different stages of Covid-19 pandemic can be described by two key-variables: ICU patients and deaths in hospitals. We propose simple models that can be used by medical doctors and decision makers to predict the trends on both short-term and long-term horizons. Daily updates of the models with real data allow forecasting some key indicators for decision-making (an Excel file in the Supplemental material allows computing them). These are beds allocation, residence time, doubling time, rate of renewal, maximum daily rate of change (positive/negative), halfway points, maximum plateaus, asymptotic conditions, and dates and time intervals when some key thresholds are overtaken. Doubling time of ICU beds for Covid-19 emergency can be as low as 2-3 days at the outbreak of the pandemic. The models allow identifying the possible departure of the phenomenon from the predicted trend and thus can play the role of early warning systems and describe further outbreaks. Twit Text FOAVip A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic ????Comput Chem Eng http://www.kidney.de/pget.php?&tw=1&pmid=32565584 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32565584 #FOAvip English Wikipedia <ref>{{Cite pmid|32565584 }}</ref> A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic #MMPMID32565584 Manca D ; Caldiroli D ; Storti E Comput Chem Eng 2020[Sep]; 140 (ä): 106945 PMID32565584 show ga The different stages of Covid-19 pandemic can be described by two key-variables: ICU patients and deaths in hospitals. We propose simple models that can be used by medical doctors and decision makers to predict the trends on both short-term and long-term horizons. Daily updates of the models with real data allow forecasting some key indicators for decision-making (an Excel file in the Supplemental material allows computing them). These are beds allocation, residence time, doubling time, rate of renewal, maximum daily rate of change (positive/negative), halfway points, maximum plateaus, asymptotic conditions, and dates and time intervals when some key thresholds are overtaken. Doubling time of ICU beds for Covid-19 emergency can be as low as 2-3 days at the outbreak of the pandemic. The models allow identifying the possible departure of the phenomenon from the predicted trend and thus can play the role of early warning systems and describe further outbreaks. äA simplified math approach to predict ICU beds and mortality rate for (epmc).pdf DeepDyve Pubget Overpricing