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10.2807/1560-7917.ES.2020.25.17.2000257 http://scihub22266oqcxt.onion/10.2807/1560-7917.ES.2020.25.17.2000257 32372755!7201952!32372755     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 245.2 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       Euro+Surveill 2020 ; 25 (17): ä Nephropedia Template TP {{tp|p=32372755|t=2020. Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 |pdf=|usr=}}{{32372755}} gab.com Text Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 JO: Euro Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32372755 #FOAvip BackgroundEstimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies.AimWe estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased.MethodsWe used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers.ResultsThe mean generation interval was 5.20 days (95% credible interval (CrI): 3.78-6.78) for Singapore and 3.95 days (95% CrI: 3.01-4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32-67) for Singapore and 62% (95% CrI: 50-76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information.ConclusionHigh estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals. Twit Text FOAVip Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 ????Euro Surveill http://www.kidney.de/pget.php?&tw=1&pmid=32372755 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32372755 #FOAvip English Wikipedia <ref>{{Cite pmid|32372755}}</ref> Estimating the generation interval for coronavirus disease (COVID-19) based on symptom onset data, March 2020 #MMPMID32372755 Ganyani T; Kremer C; Chen D; Torneri A; Faes C; Wallinga J; Hens N Euro Surveill 2020[Apr]; 25 (17): ä PMID32372755show ga BackgroundEstimating key infectious disease parameters from the coronavirus disease (COVID-19) outbreak is essential for modelling studies and guiding intervention strategies.AimWe estimate the generation interval, serial interval, proportion of pre-symptomatic transmission and effective reproduction number of COVID-19. We illustrate that reproduction numbers calculated based on serial interval estimates can be biased.MethodsWe used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates, we obtained the serial interval, proportions of pre-symptomatic transmission and reproduction numbers.ResultsThe mean generation interval was 5.20 days (95% credible interval (CrI): 3.78-6.78) for Singapore and 3.95 days (95% CrI: 3.01-4.91) for Tianjin. The proportion of pre-symptomatic transmission was 48% (95% CrI: 32-67) for Singapore and 62% (95% CrI: 50-76) for Tianjin. Reproduction number estimates based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Sensitivity analyses showed that estimating these quantities from outbreak data requires detailed contact tracing information.ConclusionHigh estimates of the proportion of pre-symptomatic transmission imply that case finding and contact tracing need to be supplemented by physical distancing measures in order to control the COVID-19 outbreak. Notably, quarantine and other containment measures were already in place at the time of data collection, which may inflate the proportion of infections from pre-symptomatic individuals. |Asymptomatic Infections/*epidemiology[MESH] |Betacoronavirus[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus[MESH] |Coronavirus Infections/*diagnosis/epidemiology/*prevention & control/transmission[MESH] |Disease Outbreaks/*prevention & control[MESH] |Humans[MESH] |Models, Theoretical[MESH] |Pandemics/*prevention & control[MESH] |Pneumonia, Viral/*diagnosis/epidemiology/*prevention & control/transmission[MESH] |Quarantine[MESH] |SARS-CoV-2[MESH] |Singapore/epidemiology[MESH]Estimating the generation interval for coronavirus disease (COVID-19) (epmc).pdf DeepDyve Pubget Overpricing