Author: Keisuke Ejima; Kwang Su Kim; Yusuke Ito; Shoya Iwanami; Hirofumi Ohashi; Yoshiki Koizumi; Koichi Watashi; Ana I Bento; Kazuyuki Aihara; Shingo Iwami
Title: Inferring Timing of Infection Using Within-host SARS-CoV-2 Infection Dynamics Model: Are ""Imported Cases"" Truly Imported? Document date: 2020_3_31
ID: gb9rkv9c_22
Snippet: respectively. The parameters , , and represent the rate constant for virus infection, the 136 maximum rate constant for viral replication and the death rate of infected cells, respectively. All 137 viral load data including Singapore and Zhuhai patients were simultaneously fitted using a 138 nonlinear mixed-effect modelling approach, which uses samples to estimate population 139 parameters while accounting for inter-individual variation (Table 1).....
Document: respectively. The parameters , , and represent the rate constant for virus infection, the 136 maximum rate constant for viral replication and the death rate of infected cells, respectively. All 137 viral load data including Singapore and Zhuhai patients were simultaneously fitted using a 138 nonlinear mixed-effect modelling approach, which uses samples to estimate population 139 parameters while accounting for inter-individual variation (Table 1) . Further, sampled parameter 140 sets were used to predict the estimated day of SARS-CoV-2 infection establishment, that is, the 141 start of the exponential growth phase of viral loads 9 . The infection establishment time, inf , was 142 estimated by hindcasting, when the viral load reaches the boundary. The viral load boundary for 143
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