The Characteristics of Middle Eastern Respiratory Syndrome Coronavirus Transmission Dynamics in South Korea

Kim, Yunhwan; Lee, Sunmi; Chu, Chaeshin; Choe, Seoyun; Hong, Saeme; Shin, Youngseo

The parameter estimation of system (1) to the incidence data of MERS-CoV in South Korea from May 6, 2015 to July 1, 2015 is conducted using the least-square method for this nonlinear system. Since the primary case was exposed to MERS-CoV during their stay in the Middle East, the patient and his wife are assumed to be in the exposed class of our system before the confirmation day (May 20, 2015). In Figure 1 , the data of MERS-CoV incidence (+) and its best fit (solid curve) of incidence Eq. (1) are plotted from May 6, 2015 to July 4, 2015. The MERS-CoV incidence is defined as the number of newly infected individuals per day. The figure demonstrates that our fitted MERS-CoV model fits well to the reported incidence data. In the figure, we can see the trend of logistic curve; thus, we split up the time into two periods (May 6, June 7 and June 7, July 1) where the rate of change is in its increasing and decreasing trend respectively. Due to the implementation of intensive interventions at June 7, each period has its own remarkable trend, thus, parameters are estimated in each period. Two kinds of transmission rates are estimateddtransmission rate b and transmissibility of hospitalized patients ldbecause many MERS-CoV patients are infected in hospitals and it is assumed that the value of hospitalized transmissibility l is bigger than transmission rate b. Parameter values used for simulation are listed in Table 2 .