Fig. 5.

Performance of mobility-based spatial sampling in simulated outbreaks under various scenarios utilizing a travel network-based epidemiological model. The outbreaks were simulated with initiation in one, two, or three communities selected randomly based on the probability weight of population density or inverse population density. Different basic reproduction numbers (R₀) were considered for the original SARS-CoV-2, Delta, and Omicron variants, along with variations in the timing of interventions. The assessment focused on two optimized mobility-based spatial sampling approaches, namely CFI (case flow intensity) and CTI (case transmission intensity). The x-axis represents the fraction of sampled populations among the total populations in Guangzhou and Beijing using CFI and CTI, respectively. The y-axis presents the proportion of cases detected by different sampling approaches in Guangzhou and Beijing, respectively. The diagonal line in each panel symbolizes the performance of simple random sampling, while the shaded regions indicate the 95% confidence intervals.