LAUSR

Abstract Objectives The largely resolved first wave of the COVID-19 epidemic in China provides a unique opportunity to investigate how the early characteristics of the COVID-19 outbreak predicts its subsequent size. Methods We collected publicly available COVID-19 epidemiological data from 436 Chinese cities during 16th January-15th March 2020. Based on 45 cities which reported >100 confirmed cases, we examined the correlation between early-stage epidemic characteristics and subsequent epidemic size. Results We identified a transition point from a slow- to a fast-growing phase for COVID-19 at 5.5 (95% CI, 4.6-6.4) days after the first report, and 30 confirmed cases marked a critical threshold for this transition. The average time for the number of confirmed cases to increase from 30 to 100 (time from 30-to-100) was 6.6 (5.3-7.9) days, and the average case-fatality rate in the first 100 confirmed cases (CFR-100) was 0.8% (0.2-1.4%). The subsequent epidemic size per million population was significantly associated with both of these indicators. We predict a ranking of epidemic size in the cities based on these two indicators and found it highly correlated with the actual ranking of epidemic size. Conclusions Early epidemic characteristics are important indicators for the size of the entire epidemic.