Abstract

Background: Novel coronavirus disease 2019 (COVID-19) causes an immense disease burden. Only drugs or vaccines can eliminate the virus. Methods: We adopted our age-specific transmission model by susceptible-exposed-infectious -critically ill-asymptomatic-removed (SEICAR) model. Effects of different drug types were simulated by changing transmission rate (β), critical case fatality rate (fc), and disease duration of each age group. Evaluation indexes were based on outbreak duration(OD), cumulative number of cases(CNC), total attack rate(TAR), peak date(PD), number of peak cases(NPC), and case fatality rate(f). Findings: When without intervention, changing in β and disease duration, as the age increased, OD decreased, TAR increased, PD advanced, CCN and NPC initially increased and then decreased, while f decreased first and then increased. When disease duration and β remained unchanged, changing fc did not affect the epidemic. All age groups had 40% shorter disease duration but unchanged fc, while β was reduced by 60%, which reduced TAR of group 1 (≤14 years) from 2·35% to 0·09%; f of group 4 (≥65 years) was reduced from 1·04% to 0·05%. Interpretation: Drugs had different age-dependent effects. If a drug can control the disease duration or β of all age groups, younger people would have the fastest transmission control and seniors will have the best improvement in disease severity. Funding: The Bill & Melinda Gates Foundation (INV-005834); the Science and Technology Program of Fujian Province (No: 2020Y0002), and the Xiamen New Coronavirus Prevention and Control Emergency Tackling Special Topic Program (No: 3502Z2020YJ03).Declaration of Interests: The authors declare no competing interests.

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