Analysis on Action Tracking Reports of COVID-19 Informs Control Strategies and Vaccine Delivery in Post-Pandemic Era

Understanding the spread of SARS-CoV-2 provides important insights for control policies such as social-distancing interventions and vaccine delivery in the post-pandemic era. In this work, we take the advantage of action tracking reports of confirmed COVID-19 patients, which contain the mobility trajectory of patients. We analyzed reports of patients from April 2020 to January 2021 in China, a country where the residents are well-prepared for the "new normal" world following COVID-19 spread. We developed natural language processing (NLP) tools to transform the unstructured text of action-tracking reports to a structured network of social contacts. An epidemiology model was built on top of the network. Our analysis provides important insights for the development of control policies. Under the "new normal" conditions, we find that restaurants, locations less protected by mask-wearing, have a greater risk than any other location categories, including locations where people are present at higher densities (e.g., flight). We find that discouraging railway transports is crucial to avoid another wave of breakout during the Chunyun season (a period of travel in China with extremely high traffic load around the Chinese New Year). By formalizing the challenge of finding the optimal vaccine delivery among various different population groups as an optimization problem, our analysis helps to maximize the efficiency of vaccine delivery under the general situation of vaccine supply shortage. We are able to reduce the numbers of infections and deaths by 7.4% and 10.5% respectively with vaccine supply for only 1% of the population. Furthermore, with 10% vaccination rate, the numbers of infections and deaths further decrease by 52.6% and 78.1% respectively. Our work will be helpful in the design of effective policies regarding interventions, reopening, contact tracing and vaccine delivery in the "new normal" world following COVID-19 spread.