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.

10.3934/mbe.2020173 http://scihub22266oqcxt.onion/10.3934/mbe.2020173 32987516!ä!32987516 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 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\32987516.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Math+Biosci+Eng 2020 ; 17 (4): 3052-3061 Nephropedia Template TP {{tp|p=32987516|t=2020. Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis |pdf=|usr=}}{{32987516}} gab.com Text Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis JO: Math Biosci Eng http://www.kidney.de/pget.php?&tw=1&pmid=32987516 #FOAvip The novel coronavirus disease 2019 (COVID-19) infection broke out in December 2019 in Wuhan, and rapidly overspread 31 provinces in mainland China on 31 January 2020. In the face of the increasing number of daily confirmed infected cases, it has become a common concern and worthy of pondering when the infection will appear the turning points, what is the final size and when the infection would be ultimately controlled. Based on the current control measures, we proposed a dynamical transmission model with contact trace and quarantine and predicted the peak time and final size for daily confirmed infected cases by employing Markov Chain Monte Carlo algorithm. We estimate the basic reproductive number of COVID-19 is 5.78 (95%CI: 5.71-5.89). Under the current intervention before 31 January, the number of daily confirmed infected cases is expected to peak on around 11 February 2020 with the size of 4066 (95%CI: 3898-4472). The infection of COVID-19 might be controlled approximately after 18 May 2020. Reducing contact and increasing trace about the risk population are likely to be the present effective measures. Twit Text FOAVip Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis ????Math Biosci Eng http://www.kidney.de/pget.php?&tw=1&pmid=32987516 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32987516 #FOAvip English Wikipedia <ref>{{Cite pmid|32987516}}</ref> Current trends and future prediction of novel coronavirus disease (COVID-19) epidemic in China: a dynamical modeling analysis #MMPMID32987516 Wang K; Lu ZZ; Wang XM; Li H; Li HL; Lin DD; Cai YL; Feng X; Song YT; Feng ZW; Ji WD; Wang XY; Yin Y; Wang L; Peng ZH Math Biosci Eng 2020[Apr]; 17 (4): 3052-3061 PMID32987516show ga The novel coronavirus disease 2019 (COVID-19) infection broke out in December 2019 in Wuhan, and rapidly overspread 31 provinces in mainland China on 31 January 2020. In the face of the increasing number of daily confirmed infected cases, it has become a common concern and worthy of pondering when the infection will appear the turning points, what is the final size and when the infection would be ultimately controlled. Based on the current control measures, we proposed a dynamical transmission model with contact trace and quarantine and predicted the peak time and final size for daily confirmed infected cases by employing Markov Chain Monte Carlo algorithm. We estimate the basic reproductive number of COVID-19 is 5.78 (95%CI: 5.71-5.89). Under the current intervention before 31 January, the number of daily confirmed infected cases is expected to peak on around 11 February 2020 with the size of 4066 (95%CI: 3898-4472). The infection of COVID-19 might be controlled approximately after 18 May 2020. Reducing contact and increasing trace about the risk population are likely to be the present effective measures. |*Betacoronavirus[MESH] |*Models, Biological[MESH] |Algorithms[MESH] |Basic Reproduction Number/statistics & numerical data[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Computer Simulation[MESH] |Contact Tracing/statistics & numerical data[MESH] |Coronavirus Infections/*epidemiology/prevention & control/transmission[MESH] |Epidemics/prevention & control/statistics & numerical data[MESH] |Geographic Mapping[MESH] |Humans[MESH] |Markov Chains[MESH] |Mathematical Concepts[MESH] |Monte Carlo Method[MESH] |Pandemics/prevention & control/*statistics & numerical data[MESH] |Pneumonia, Viral/*epidemiology/prevention & control/transmission[MESH] |Quarantine/statistics & numerical data[MESH]Current trends and future prediction of novel coronavirus disease (COV(epmc).pdf DeepDyve Pubget Overpricing