The COVID-19 pandemic is a serious global issue that requires effective control and prevention measures. Understanding how the virus spreads is crucial in implementing non-pharmaceutical measures. Previous studies have focused on the effects of urban socio-political measures on the contagion rate, but the fine-grained geographic urban spreading pattern remains an open question. To address this, we analyzed the trajectory data of 197,808 smartphone users (including 17,808 anonymous confirmed cases) in nine cities in China. Our analysis revealed that the spatial distribution of confirmed cases in all cities followed a power-law-like model and the spreading centroid human mobility remained constant over time. We also found that long average traveling distance resulted in a high growth rate of spreading radius and wide spatial diffusion of confirmed cases in the fine-grained geographic model. Using the Kendall model, we simulated the urban spreading of COVID-19, which matched the real spreading process well. The COVID-19 vaccines have been associated with several side effects, including systemic events like fever, muscle pain, and headache, and injection site events like swelling, pain, and redness. This study focused on analyzing the side effects of three vaccines: BNT162b2 (Pfizer/BioNTech), mRNA-1273 (Moderna), and JNJ-78436735 vaccines through both experimental and survey methods. By comparing the side effects of the vaccines during their design phase and after their release, we observed improvements in alleviating fever side effects. However, the results were inconclusive, and more research is needed to better understand and solve the long-term side effects of the COVID-19 vaccines. This paper targets SARS-CoV-2 treatments by understanding viral replication. We examine viral entry and infection, develop monoclonal antibodies for COVID-19 treatment, and assess PVP-I mouthwash for inactivating the virus and lowering transmission risks. Both methods exhibit potential for COVID-19 treatment and prevention.