Assessing differences in work intensity resilience to pandemic outbreaks using large-scale mobile phone data

Pandemic outbreaks significantly disrupt human work activity, which is a crucial aspect of urban daily life, potentially causing reduced income or unemployment. These disruptions often vary across different population groups and regions. However, most existing studies focus on general human mobility patterns with limited attention specific to work activity, and conduct separate analyses on population groups and regions, overlooking intra-population differences across regions and inter-population variations within the same region. To this end, we first introduce the concept of work intensity to quantify the work activity. Using large-scale mobile phone data, we then estimate an individual’s work intensity, and characterize the changes in work intensity based on the concept of resilience, i.e., the ability to withstand and recover from a disaster. Finally, we propose a novel analytical framework that integrates both population groups and regions to assess differences in resilience. Herein, we take the pandemic outbreak in Beijing after the sudden relaxation of dynamic zero-COVID policy as a case study due to less policy intervention. Results reveal that females and younger people exhibit lower work intensity resilience, respectively. We also find significant regional differences and several negative features for resilience: short distance to city center, long home-to-work distance, high density of high-paying jobs, low road density, and high density of subway stations. By integrating both population group and region perspectives, we identify vulnerable population groups in specific regions. This integrated perspective can help design more targeted response and recovery strategies, and thereby promote health-related urban resilience and sustainability.