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10.1017/S0950268821001436 http://scihub22266oqcxt.onion/10.1017/S0950268821001436 34278986!8438516!34278986     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 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Epidemiol+Infect 2021 ; 149 (ä): e197 Nephropedia Template TP {{tp|p=34278986|t=2021. Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis |pdf=|usr=}}{{34278986}} gab.com Text Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis JO: Epidemiol Infect http://www.kidney.de/pget.php?&tw=1&pmid=34278986 #FOAvip Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the CFR using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the CFR. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID-19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2% to 20% in different countries, estimates for IFR are mostly around 0.5-0.8% for countries that experienced moderate outbreaks and 1-3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems. Twit Text FOAVip Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis ????Epidemiol Infect http://www.kidney.de/pget.php?&tw=1&pmid=34278986 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34278986 #FOAvip English Wikipedia <ref>{{Cite pmid|34278986}}</ref> Estimating the case fatality ratio for COVID-19 using a time-shifted distribution analysis #MMPMID34278986 Thomas BS; Marks NA Epidemiol Infect 2021[Jul]; 149 (ä): e197 PMID34278986show ga Estimating the case fatality ratio (CFR) for COVID-19 is an important aspect of public health. However, calculating CFR accurately is problematic early in a novel disease outbreak, due to uncertainties regarding the time course of disease and difficulties in diagnosis and reporting of cases. In this work, we present a simple method for calculating the CFR using only public case and death data over time by exploiting the correspondence between the time distributions of cases and deaths. The time-shifted distribution (TSD) analysis generates two parameters of interest: the delay time between reporting of cases and deaths and the CFR. These parameters converge reliably over time once the exponential growth phase has finished. Analysis is performed for early COVID-19 outbreaks in many countries, and we discuss corrections to CFR values using excess-death and seroprevalence data to estimate the infection fatality ratio (IFR). While CFR values range from 0.2% to 20% in different countries, estimates for IFR are mostly around 0.5-0.8% for countries that experienced moderate outbreaks and 1-3% for severe outbreaks. The simplicity and transparency of TSD analysis enhance its usefulness in characterizing a new disease as well as the state of the health and reporting systems. |COVID-19/*mortality[MESH] |Disease Outbreaks/*statistics & numerical data[MESH] |Humans[MESH] |Mortality[MESH] |Public Health/*methods[MESH]Estimating the case fatality ratio for COVID-19 using a time-shifted d(epmc).pdf DeepDyve Pubget Overpricing