Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.3760/cma.j.cn112338-20200205-00069 http://scihub22266oqcxt.onion/10.3760/cma.j.cn112338-20200205-00069 32113196!ä!32113196 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 (4): 461-465 Nephropedia Template TP {{tp|p=32113196|t=2020. Study on assessing early epidemiological parameters of COVID-19 epidemic in China |pdf=|usr=}}{{32113196}} gab.com Text Study on assessing early epidemiological parameters of COVID-19 epidemic in China JO: Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32113196 #FOAvip Objective: To study the early dynamics of the epidemic of coronavirus disease (COVID-19) in China from 15 to 31 January, 2020, and estimate the corresponding epidemiological parameters (incubation period, generation interval and basic reproduction number) of the epidemic. Methods: By means of Weibull, Gamma and Lognormal distributions methods, we estimated the probability distribution of the incubation period and generation interval data obtained from the reported COVID-19 cases. Moreover, the AIC criterion was used to determine the optimal distribution. Considering the epidemic is ongoing, the exponential growth model was used to fit the incidence data of COVID-19 from 10 to 31 January, 2020, and exponential growth method, maximum likelihood method and SEIR model were used to estimate the basic reproduction number. Results: Early COVID-19 cases kept an increase in exponential growth manner before 26 January, 2020, then the increase trend became slower. The average incubation period was 5.01 (95%CI: 4.31-5.69) days; the average generation interval was 6.03 (95%CI: 5.20-6.91) days. The basic reproduction number was estimated to be 3.74 (95%CI: 3.63-3.87), 3.16 (95%CI: 2.90-3.43), and 3.91 (95%CI: 3.71-4.11) by three methods, respectively. Conclusions: The Gamma distribution fits both the generation interval and incubation period best, and the mean value of generation interval is 1.02 day longer than that of incubation period. The relatively high basic reproduction number indicates that the epidemic is still serious; Based on our analysis, the turning point of the epidemic would be seen on 26 January, the growth rate would be lower afterwards. Twit Text FOAVip Study on assessing early epidemiological parameters of COVID-19 epidemic in China ????Zhonghua Liu Xing Bing Xue Za Zhi http://www.kidney.de/pget.php?&tw=1&pmid=32113196 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32113196 #FOAvip English Wikipedia <ref>{{Cite pmid|32113196}}</ref> Study on assessing early epidemiological parameters of COVID-19 epidemic in China #MMPMID32113196 Song QQ; Zhao H; Fang LQ; Liu W; Zheng C; Zhang Y Zhonghua Liu Xing Bing Xue Za Zhi 2020[Apr]; 41 (4): 461-465 PMID32113196show ga Objective: To study the early dynamics of the epidemic of coronavirus disease (COVID-19) in China from 15 to 31 January, 2020, and estimate the corresponding epidemiological parameters (incubation period, generation interval and basic reproduction number) of the epidemic. Methods: By means of Weibull, Gamma and Lognormal distributions methods, we estimated the probability distribution of the incubation period and generation interval data obtained from the reported COVID-19 cases. Moreover, the AIC criterion was used to determine the optimal distribution. Considering the epidemic is ongoing, the exponential growth model was used to fit the incidence data of COVID-19 from 10 to 31 January, 2020, and exponential growth method, maximum likelihood method and SEIR model were used to estimate the basic reproduction number. Results: Early COVID-19 cases kept an increase in exponential growth manner before 26 January, 2020, then the increase trend became slower. The average incubation period was 5.01 (95%CI: 4.31-5.69) days; the average generation interval was 6.03 (95%CI: 5.20-6.91) days. The basic reproduction number was estimated to be 3.74 (95%CI: 3.63-3.87), 3.16 (95%CI: 2.90-3.43), and 3.91 (95%CI: 3.71-4.11) by three methods, respectively. Conclusions: The Gamma distribution fits both the generation interval and incubation period best, and the mean value of generation interval is 1.02 day longer than that of incubation period. The relatively high basic reproduction number indicates that the epidemic is still serious; Based on our analysis, the turning point of the epidemic would be seen on 26 January, the growth rate would be lower afterwards. |*Basic Reproduction Number[MESH] |*Infectious Disease Incubation Period[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus Infections/*epidemiology[MESH] |Humans[MESH] |Models, Statistical[MESH] |Pandemics[MESH] |Pneumonia, Viral/*epidemiology[MESH] Study on assessing early epidemiological parameters of COVID-19 epide(epmc).pdf DeepDyve Pubget Overpricing