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10.1016/j.epidem.2021.100454 http://scihub22266oqcxt.onion/10.1016/j.epidem.2021.100454 33773195!7959696!33773195     free     free     free 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       Epidemics 2021 ; 35 (ä): 100454 Nephropedia Template TP {{tp|p=33773195|t=2021. Estimation of the incubation period of COVID-19 using viral load data |pdf=|usr=}}{{33773195}} gab.com Text Estimation of the incubation period of COVID-19 using viral load data JO: Epidemics http://www.kidney.de/pget.php?&tw=1&pmid=33773195 #FOAvip The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event. Twit Text FOAVip Estimation of the incubation period of COVID-19 using viral load data ????Epidemics http://www.kidney.de/pget.php?&tw=1&pmid=33773195 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33773195 #FOAvip English Wikipedia <ref>{{Cite pmid|33773195}}</ref> Estimation of the incubation period of COVID-19 using viral load data #MMPMID33773195 Ejima K; Kim KS; Ludema C; Bento AI; Iwanami S; Fujita Y; Ohashi H; Koizumi Y; Watashi K; Aihara K; Nishiura H; Iwami S Epidemics 2021[Jun]; 35 (ä): 100454 PMID33773195show ga The incubation period, or the time from infection to symptom onset, of COVID-19 has usually been estimated by using data collected through interviews with cases and their contacts. However, this estimation is influenced by uncertainty in the cases' recall of exposure time. We propose a novel method that uses viral load data collected over time since hospitalization, hindcasting the timing of infection with a mathematical model for viral dynamics. As an example, we used reported data on viral load for 30 hospitalized patients from multiple countries (Singapore, China, Germany, and Korea) and estimated the incubation period. The median, 2.5, and 97.5 percentiles of the incubation period were 5.85 days (95 % CI: 5.05, 6.77), 2.65 days (2.04, 3.41), and 12.99 days (9.98, 16.79), respectively, which are comparable to the values estimated in previous studies. Using viral load to estimate the incubation period might be a useful approach, especially when it is impractical to directly observe the infection event. |*Infectious Disease Incubation Period[MESH] |Adult[MESH] |COVID-19/*transmission/virology[MESH] |China[MESH] |Hospitalization[MESH] |Humans[MESH] |Male[MESH] |Models, Theoretical[MESH] |SARS-CoV-2[MESH]Estimation of the incubation period of COVID-19 using viral load data (epmc).pdf DeepDyve Pubget Overpricing