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Additional file 1: Table S1. Initial baseline values and values used in the sensitivity analysis of the branching process model. Figure S1. Sensitivity analysis of the interval of initial case from exposure to confirmation. A, B, C, D and E was the impact of R0, proportion of asymptomatic infections, effective vaccine coverage, probability of contact traced and start time of nucleic acid test on the interval respectively. Figure S2. Sensitivity analysis of the number of potential infections for different proportions of asymptomatic infections (A), different probability of contact tracing (B), and different start time of nucleic acid testing (C). The horizontal black dotted lines indicate the baseline scenario (66.48% simulations with potential infections less than 10) using parameters in Table S1. Figure S3. Probability of cumulative cases exceeding 20 (blue), 50 (red), and 100 (green) for different values of R0 (A), different numbers of initial cases (B), different mean incubation period (C), different proportion of asymptomatic infections (D), different effective vaccine coverage (E), different probability of contact tracing (F), and different start time of nucleic acid testing (G). The vertical grey dotted lines indicate the baseline scenario, using parameters in Table S1.

Proposes an approach to extracting topic words at different levels in any specific domain. The method is based on the statistic features of terms in a large amount of text documents: term frequency and inverse document frequency. Preliminary experiments in Chinese have indicated that the words mined out are basically coincident with the objective reality. So, this approach is helpful for utilizing computers to discover the semantic relationships between words.