This dissertation investigates the impact of international and local mobility of asymptomatic versus symptomatic COVID-19 cases on the pandemic in Hong Kong.The first manuscript analyzed empirical data from 11,775 confirmed COVID-19 cases in Hong Kong from January 2020 to April 2021, building a retrospective cohort. The results indicated that COVID-19 asymptomatic airport or flight crew were ten times more likely to have inbound air travel history than symptomatic airport or flight crew (adjusted RR=10.00, 95% CI: 4.00–25.00), and the median flight duration of asymptomatic cases was 4.6 person-hours shorter than that of symptomatic cases (p<0.01). The second manuscript presented a social network analysis study that build networks for the three peaks of COVID-19 diagnosis in Hong Kong. The results showed that asymptomatic cases were 1.33 times more likely to be presented in the inbound flight cabin or airport with other COVID-19 cases simultaneously than symptomatic cases (95%CI: 1.21-1.45) at the early stage of the pandemic. Additionally, the study found that network percolation simulation targeted attacks were more efficient than random failures in dismantling networks with a low level of connectedness. The third manuscript used geocoded COVID-19 cases’ travel records in Hong Kong to conduct a spatial analysis study. The findings indicated that asymptomatic cases visited locations mostly clustered in the southern part of Hong Kong, while symptomatic cases visited locations mostly clustered in the middle and southern parts of Hong Kong. This study also found that Geographically Weighted Regression models performed better among symptomatic cases than asymptomatic cases, and median local travel time was higher (p<0.01) among asymptomatic (68.09 person-minutes) than symptomatic cases (59.46 person-minutes) based on 19,568 Origin-Destination Cost Matrix least-cost paths. Overall, this dissertation highlights the importance of promoting public health prevention strategies to contain future infectious disease pandemics at the early stage, regardless of the presence of symptoms. Moreover, it suggests that travel restriction may not be effective in dismantling networks with a low-level of connectedness. Local health authorities and policymakers should tailor detection and containment strategies based on spatial variability in different areas.