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10.3390/ijerph17103705 http://scihub22266oqcxt.onion/10.3390/ijerph17103705 32456346!7277812!32456346     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       Int+J+Environ+Res+Public+Health 2020 ; 17 (10): ä Nephropedia Template TP {{tp|p=32456346|t=2020. Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China |pdf=|usr=}}{{32456346}} gab.com Text Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32456346 #FOAvip COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54-0.84) and 0.25 (95% CI: 0.13-0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors. Twit Text FOAVip Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32456346 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32456346 #FOAvip English Wikipedia <ref>{{Cite pmid|32456346}}</ref> Evaluating Transmission Heterogeneity and Super-Spreading Event of COVID-19 in a Metropolis of China #MMPMID32456346 Zhang Y; Li Y; Wang L; Li M; Zhou X Int J Environ Res Public Health 2020[May]; 17 (10): ä PMID32456346show ga COVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics, including heterogeneity and the emergence of super spreading events (SSEs) where certain individuals infect large numbers of secondary cases, is of vital importance for prediction and intervention of future epidemics. Here, we collected information of all infected cases (135 cases) between 21 January and 26 February 2020 from official public sources in Tianjin, a metropolis of China, and grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of four generations. Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k (lower value indicating higher heterogeneity) to be 0.67 (95% CI: 0.54-0.84) and 0.25 (95% CI: 0.13-0.88), respectively. A super-spreader causing six infections was identified in Tianjin. In addition, our simulation allowing for heterogeneity showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since 28 January. Our results highlighted more efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors. |Betacoronavirus/*isolation & purification[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus Infections/epidemiology/*transmission/virology[MESH] |Disease Outbreaks[MESH] |Humans[MESH] |Pandemics[MESH] |Pneumonia, Viral/epidemiology/*transmission/virology[MESH]Evaluating Transmission Heterogeneity and Super-Spreading Event of COV(epmc).pdf DeepDyve Pubget Overpricing