Additional file 1 of Quantifying the spatial spillover effects of non-pharmaceutical interventions on pandemic risk
Creators: name: Wang, Keli
name: Han, Xiaoyi
name: Dong, Lei
name: Chen, Xiao-Jian
name: Xiu, Gezhi
name: Kwan, Mei-po
name: Liu, Yu
Publisher: name: figshare
Year: 2023
Subjects: subject: Neuroscience
subject: Biotechnology
subject: Sociology
subject: FOS: Sociology

description: Additional file 1: Table S1. Best-fit model posterior estimates of key epidemiological parameters for January 6 to March 9, 2020. Table S2. Gamma distributions for monthly reporting delay (Dr). Table S3. Comparison of the results of DIC based on different spatial weight matrices. Table S4. The contribution of direct effects and SSE of all NPIs on COVID-19 cases in 48 regions and Washington D.C. Table S5. The coefficients of different NPI estimates under the dependent variable multiplied by 100. Table S6. The coefficients estimate of direct effects under the dependent variable multiplied by 100. Table S7. The coefficients estimate of spatial spillover effects under the dependent variable multiplied by 100. Table S8. The coefficients estimate of direct effects from spatial panel durbin model. Table S9. The coefficients estimate of spatial spillover effects from spatial panel durbin model. Table S10. The coefficient estimated by our spatial panel model with different weight matrix during Phase A. Table S11. The coefficient estimated by our spatial panel model with different weight matrix during Phase B. Figure S1. The connectivity structure of different spatial weight matrix. Figure S2. Comparison of the change of human mobility estimated by our spatial panel model versus the factual human mobility change of 48 states and Washington D.C. Figure S3. The scatterplot of  the change of human mobility estimated by our spatial panel model versus the factual human mobility change in all states. Figure S4. The direct and spatial spillover effect estimates of NPIs in 48 states and Washington D.C. from the spatial panel model. Figure S5. Model fitting to daily case numbers (blue dots) by S-SEIR model in 48 states and Washington D.C. Figure S6. The estimated cases by different model in 48 states (regions) and Washington D.C. Notes: S-SEIR (Direct effects): similar to the S-SEIR model, but only the direct effects of NPIs are considered. S-SEIR (SSE): similar to the S-SEIR model, but only the spatial spillover effects of NPIs are considered. S-SEIR: both the direct and spatial spillover effects are considered. The line and shaded area represent the median and 95% CI, respectively. Figure S7. The estimated national cumulative confirmed cases by changing the intensity of all NPIs in different regions. Figure S8. The national cumulative confirmed cases estimated by changing the intensity of diffferent NPIs in different regions. Figure S9. The estimated national cumulative confirmed cases by restricting the flows of r2, r4, or r5, including all travel flow with these targeted regions (denoted as ’OD’), travel flow from these targeted regions (denoted as ’O’) and travel flow to these targeted regions (denoted as ‘D’). Figure S10. The median differences in national cumulative confirmed cases at t = 30 week are estimated by the complete lockdown (OD), origin-based lockdown (O), destination-based lockdown (D) in r4 or r5 and baseline scenario. Figure S11. The change of intrastate human mobility in each state. Figure S12. The distribution of the dependent variables in different weeks. Figure S13. Estimation results of the change of intrastate human mobility and spatial spillover effects of NPIs by panel SAR model. The matrix during introduction phase is flow weight (8 neighbors) matrix, during lifting phase is the inverse distance matrix with a cut-off distance of 600 km.  Figure S14.  Estimation results of the change of intrastate human mobility and spatial spillover effects of NPIs by panel SAR model. The matrix during introduction phase is the inverse distance matrix with a cut-off distance of 600 km, and during lifting phase is flow weight (8 neighbors). Figure S15. Estimation results of the change of intrastate human mobility and spatial spillover effects of NPIs by panel SAR model. The matrix during introduction phase is the inverse distance matrix with a cut-off distance of 600 km, and during lifting phase is the inverse distance (the max distance is 800 km). Figure S16. Estimation results from the S-SEIR model, taking changes in actual human mobility as intervention effects. Figure S17. Estimation results from the Sp-SEIR model, the initial seed is the number of cases in the five days from T0 to T0+4. Figure S18. Estimation results from the Sp-SEIR model. During initialization, symptomatic patients are not assigned an initial value. Figure S19. Estimation results from the Sp-SEIR model, the range of movement fixed factor (θ) is from 1 to 10. Figure S20. Estimation results from the Sp-SEIR model. We assume that the infection of asymptomatic patients relative to symptomatic patients also varies over time and region.