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Additional file 1: Fig S1. Geographical distributions of onset-to-diagnosis interval, severe rate (SR) and case fatality rate (CFR). Fig S2. Frequency distribution of onset-to-diagnosis interval of confirmed COVID-19 cases by regions and epidemic periods. Fig S3: The onset-to-diagnosis interval-related COVID-19 disease severe rate and case fatality rate stratified by regions. Fig S4. The odds ratio and attributable fraction of COVID-19 disease severe rate resulted from onset-to-diagnosis intervals in Wuhan and outside Wuhan. Fig S5. The odds ratio and attributable fraction of COVID-19 case fatality rate resulted from onset-to-diagnosis intervals in Wuhan and outside Wuhan. Table S1. The subgroup analysis on the onset-to-diagnosis interval of patients with COVID-19 for age, sex, geographic region and epidemic period by multivariate linear regression. Table S2. Odds ratio of onset-to-diagnosis interval for the risk of severe COVID-19 by multivariate logistic regression model. Table S3. Attributable fraction of onset-to-diagnosis interval for the risk of severe COVID-19. Table S4. Odds ratio of onset-to-diagnosis interval for the risk of fatal COVID-19 by multivariate logistic regression model. Table S5. Attributable fraction of onset-to-diagnosis interval for the risk of fatal COVID-19. Table S6. The predicted and actual case number of severe and death cases according to the different cutoff value of onset-to-diagnosis interval.

Additional file 1. Additional information includes Methods, 14 Figures, 6 Tables and References. Table S1. The specific references for all 89 Bunyavirales viruses in China and Rift Valley fever virus in Africa and the Arabian Peninsula. Table S2. Search terminology used for the systematic review. Table S3. Information of explanatory covariates sources in this study. Table S4. Description of 42 potential explanatory covariates used in the modelling efforts. Table S5. Clinical characteristics of human cases infections with different viruses (species) belonging to the order Bunyavirales in China. Table S6. The model-predicted areas and population sizes at risk by monthly for RVFV occurrence in China. Fig. S1. The flow diagram of data collection for Rift Valley fever virus. Fig. S2. Recorded and predicted risk distribution of H. asiaticum presence in China. Fig. S3. Correlation matrix for 36 covariates in CCHFV model. Fig. S4. Correlation matrix for 18 covariates in RVFV model. Fig. S5. Distribution of the first identification site of 89 Bunyavirales viruses in China. Fig. S6. Geographical distributions of Bunyavirales viruses detected in animals. Fig. S7. The relationship matrix of Bunyavirales virus species and involved animals. Fig. S8. ROC curves and AUC values of CCHFV model. Fig. S9. The marginal effect of explanatory covariates for CCHFV occurrence risk in the model. Fig. S10. Recorded distribution of RVFV occurrence in Africa and the Arabian Peninsula. Fig. S11. ROC curves and AUC values of RVFV model. Fig. S12. The marginal effect of explanatory covariates for RVFV occurrence risk in the model. Fig. S13. Mean environmental suitability and monthly imported risk for RVFV from January to June in China. Fig. S14. Mean environmental suitability and monthly imported risk for RVFV from July to December in China.

Additional file 1: Figure S1. Geographical distribution of case fatality rate of the COVID-19 patients based on the surveillance database in the mainland of China as of 29 March 2020. Table S1. The hospitalized case fatality rates of COVID-19 patients in related provinces. Table S2. The mortality rate and hospitalized case fatality rate of COVID-19 in China. Table S3. The hospitalized case fatality rate and relative risk for death outcome of COVID-19 patients by location, age, and sex. Table S4. The risk factor of fatal outcome among confirmed patients with SARS-COV-2 infection in the case-control study. Table S5. The cumulative incidence probability of death over time for the COVID-19 patients. Table S6. Clinical course of fatal cases and the factors associated with death among confirmed patients with SARS-COV-2 infection. Table S7. Comparison on the characteristics of fatal cases with SARS-COV-2 infection between severe and mild cases as of 29 March 2020.

Additional file 1: Supplementary Table 1. Variance inflation factor (VIF) of each model. Supplementary Table 2. Comparison of demographic, clinical and epidemiological characteristics between COVID-19 imported cases from Hubei with an incubation period of ���14 and > 14 days. Supplementary Table 3. Factors associated with incubation period among 2341 imported cases from Hubei using accelerated failure time model. Supplementary Table 4. Factors affecting the severity of COVID-19 among 2337 imported cases from Hubei using Logistic regression model. Supplementary Table 5. Multivariate logistic regression model for local cases and imported cases after excluding outliers. Supplementary Table 6. Factors associated with the transmissibility of COVID-19 among 1035 primary imported cases from Hubei using Poisson regression model. Supplementary Figure 1. The temporal pattern of reporting date of individual COVID-19 cases in the aggregated database, compared with national surveillance data outside Hubei province in China. Supplementary Figure 2. Estimated distributions of the incubation period COVID-19 local cases based on Weibull parametric model. Supplementary Figure 3. Estimated distributions of the incubation period COVID-19 local cases based on log-normal parametric model. Supplementary Figure 4. Estimated distributions of the incubation period COVID-19 local cases based on log-logistic parametric model. Supplementary Figure 5. Estimated distributions of the incubation period COVID-19 imported cases from Hubei based on Gamma parametric model. Supplementary Figure 6. Estimated distributions of the incubation period COVID-19 imported cases from Hubei based on Weibull parametric model. Supplementary Figure 7. Estimated distributions of the incubation period COVID-19 imported cases from Hubei based on log-normal parametric model. Supplementary Figure 8. Estimated distributions of the incubation period COVID-19 imported cases from Hubei based on log-logistic parametric model. Supplementary Figure 9. The incubation period in different populations profiled along epidemic period among imported cases from Hubei.