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

Background A novel coronavirus strain, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in China in late 2019. The resulting disease, Coronavirus Disease 2019 (COVID-2019), soon became a pandemic. This study aims to characterize key attributes of the epidemiology of this infection in China. Methods An age-stratified mathematical model was constructed to describe the transmission dynamics and estimate the age-specific differences in the biological susceptibility to the infection, age-assortativeness in transmission mixing, case fatality rate (CFR), and transition in rate of infectious contacts (and reproduction number R 0 ) following introduction of mass interventions. Results The model estimated the infectious contact rate in early epidemic at 0.59 contacts per day (95% uncertainty interval (UI)=0.48-0.71). Relative to those 60-69 years of age, susceptibility to the infection was only 0.06 in those ≤19 years, 0.34 in 20-29 years, 0.57 in 30-39 years, 0.69 in 40-49 years, 0.79 in 50-59 years, 0.94 in 70-79 years, and 0.88 in ≥80 years. The assortativeness in transmission mixing by age was very limited at 0.004 (95% UI=0.002-0.008). Final CFR was 5.1% (95% UI=4.8-5.4%). R 0 rapidly declined from 2.1 (95% UI=1.8-2.4) to 0.06 (95% UI=0.05-0.07) following onset of interventions. Conclusion Age appears to be a principal factor in explaining the patterns of COVID-19 transmission dynamics in China. The biological susceptibility to the infection seems limited among children, intermediate among young to mid-age adults, but high among those >50 years of age. There was no evidence for differential contact mixing by age, consistent with most transmission occurring in households rather than in schools or workplaces.