Modelling SARS-CoV-2 Dynamics: Implications for Therapy

Kwang Su Kim; Keisuke Ejima; Yusuke Ito; Shoya Iwanami; Hirofumi Ohashi; Yoshiki Koizumi; Yusuke Asai; Shinji Nakaoka; Koichi Watashi; Robin N Thompson; Shingo Iwami

shown together with the data in Fig. 1A for SARS-CoV-2 (pink) and MERS-CoV 87 (black and grey for severe and mild case, respectively). In addition, to parameterise 88 and compare these coronaviruses infections, we calculated the following important 89 quantities ( Fig. 2) using estimated parameter values; the mean length of virus 90 production of an infected cell ( = 1/ ), the within-host basic reproduction number 91 ( 0 = / ) which is the average number of newly infected cells produced by any 92 single infected cell (9), and the critical inhibition rate ( * = 1 − 1/ 0 ) induced by 93 antivirals to prevent primary virus infection (10, 11) . We showed that is not 94 significantly different for SARS-CoV-2 and MERS-CoV. However, interestingly, we 95 found that 0 and * for SARS-CoV-2 are significantly different from analogous 96 values for mild cases of MERS-CoV ( = 8.9 × 10 −4 and 2.0 × 10 −6 by the bootstrap 97 t-test, respectively), but not for severe MERS-CoV ( = 0.41 and 0.41) (see Fig. 2) , 98 although we were unable to separate mild and severe cases of SARS-CoV-2 due to 99 limited clinical information for the cases. This demonstrates that SARS-CoV-2 100 causes infection more effectively than in mild cases of MERS-CoV, but a general 101 SARS-CoV-2 infection follows infection dynamics that are similar to severe cases 102 due to MERS-CoV. In addition, as a median estimate, 65% inhibition of the initial 103 virus expansion is required to prevent the establishment of SARS-CoV-2 infection 104 (we provide a detailed analysis later). We also calculated the duration of infection in 105 which the viral load is above the detection limit ( ) in Table 1 , showing that SARS-106