This paper investigates spontaneous mobility changes in Shenzhen, China, following the lifting of the "Zero-COVID" policy in late 2022. Using 148 million travel data points from public transport, the researchers identify spatial discrepancies in mobility patterns, attributing them to heterogeneous responses to the pandemic across different travel purposes and modes. A dynamic model, considering both infection rates and individual travel willingness, is proposed and successfully fits fine-grained urban mobility data. The findings offer valuable insights for informing public health strategies against future large-scale infectious diseases.
