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10.3760/cma.j.cn112338-20200609-00823 http://scihub22266oqcxt.onion/10.3760/cma.j.cn112338-20200609-00823 32683819!ä!32683819 Warning: Undefined variable $yww in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 538 Warning: Undefined variable $yww in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 538       Zhonghua+Liu+Xing+Bing+Xue+Za+Zhi 2020 ; 41 (11): 1777-1781 Nephropedia Template TP {{tp|p=32683819|t=2020. Using Markov Chain Monte Carlo methods to estimate the age-specific case fatality rate of COVID-19 |pdf=|usr=}}{{32683819}} gab.com Text Using Markov Chain Monte Carlo methods to estimate the age-specific case fatality rate of COVID-19 JO: Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32683819 #FOAvip Objectives: The COVID-19 epidemic has swept all over the world. Estimates of its case fatality rate were influenced by the existing confirmed cases and the time distribution of onset to death, and the conclusions were still unclear. This study was aimed to estimate the age-specific case fatality rate of COVID-19. Methods: Data on COVID-19 epidemic were collected from the National Health Commission and China CDC. The Gamma distribution was used to fit the time from onset to death. The Markov Chain Monte Carlo simulation was used to estimate age-specific case fatality rate. Results: The median time from onset to death of COVID-19 was M=13.77 (P(25)-P(75): 9.03-21.02) d. The overall case fatality rate of COVID-19 was 4.1% (95%CI: 3.7%-4.4%) and the age-specific case fatality rate were 0.1%, 0.4%, 0.4%, 0.4%,0.8%, 2.3%, 6.4%, 14.0 and 25.8% for 0-, 10-, 20-, 30-, 40-, 50-, 60-, 70- and >/=80 years group, respectively. Conclusions: The Markov Chain Monte Carlo simulation method adjusting censored is suitable for case fatality rate estimation during the epidemic of a new infectious disease. Early identification of the COVID-19 case fatality rate is helpful to the prevention and control of the epidemic. Twit Text FOAVip Using Markov Chain Monte Carlo methods to estimate the age-specific case fatality rate of COVID-19 ????Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32683819 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32683819 #FOAvip English Wikipedia <ref>{{Cite pmid|32683819}}</ref> Using Markov Chain Monte Carlo methods to estimate the age-specific case fatality rate of COVID-19 #MMPMID32683819 Du ZC; Hao YT; Wei YY; Zhang ZJ; Shen SP; Zhao Y; Tang JL; Chen F; Jiang QW; Li LM Zhonghua Liu Xing Bing Xue Za Zhi 2020[Nov]; 41 (11): 1777-1781 PMID32683819show ga Objectives: The COVID-19 epidemic has swept all over the world. Estimates of its case fatality rate were influenced by the existing confirmed cases and the time distribution of onset to death, and the conclusions were still unclear. This study was aimed to estimate the age-specific case fatality rate of COVID-19. Methods: Data on COVID-19 epidemic were collected from the National Health Commission and China CDC. The Gamma distribution was used to fit the time from onset to death. The Markov Chain Monte Carlo simulation was used to estimate age-specific case fatality rate. Results: The median time from onset to death of COVID-19 was M=13.77 (P(25)-P(75): 9.03-21.02) d. The overall case fatality rate of COVID-19 was 4.1% (95%CI: 3.7%-4.4%) and the age-specific case fatality rate were 0.1%, 0.4%, 0.4%, 0.4%,0.8%, 2.3%, 6.4%, 14.0 and 25.8% for 0-, 10-, 20-, 30-, 40-, 50-, 60-, 70- and >/=80 years group, respectively. Conclusions: The Markov Chain Monte Carlo simulation method adjusting censored is suitable for case fatality rate estimation during the epidemic of a new infectious disease. Early identification of the COVID-19 case fatality rate is helpful to the prevention and control of the epidemic. |*COVID-19[MESH] |China[MESH] |Humans[MESH] |Markov Chains[MESH] |Monte Carlo Method[MESH] |Pandemics[MESH] Using Markov Chain Monte Carlo methods to estimate the age-specific c(epmc).pdf DeepDyve Pubget Overpricing