Characterizing key attributes of the epidemiology of COVID-19 in China: Model-based estimations

Houssein H Ayoub; Hiam Chemaitelly; Ghina R Mumtaz; Shaheen Seedat; Susanne F Awad; Monia Makhoul; Laith J Abu-Raddad

The model fitted the different COVID-19 empirical data such as time-series of diagnosed cases ( Figure 1A ), time-series of reported deaths ( Figure 1B) , and age-stratified attack rate as of between actual death and reported death. Figure 2 shows the predicted time evolution of COVID-19 crude case fatality rate (CFR). In the early phase of the epidemic, the crude CFR increased rapidly following the rise in incidence, but plateaued shortly after (towards the end of the first month) and remained so till incidence reached its peak. When incidence started declining (~90 days), the crude CFR grew rapidly, eventually saturating at ~150 days. The true (that is final) CFR in the total population, estimated through the 500 simulation runs, was 5.1% (95% UI=4.8-5.4%; Figure S2A of SI). Figure 4 illustrates the predicted degree of assortativeness in the age group mixing across the 500 simulation runs, which was estimated at 0.004 (95% UI=0.002-0.008)-there was virtually no assortativeness in infection transmission mixing by age. Figure 5 and Figure S2C of SI show the time evolution of 0 R , and its predicted mean and 95%