Social Distancing

Social distancing, the practice of maintaining physical space between individuals, has been a crucial public health intervention, particularly during the COVID-19 pandemic. Current research focuses on optimizing social distancing strategies through computational modeling of disease spread and the development of automated monitoring systems using computer vision techniques, including deep learning architectures like YOLO and HRNet, to detect and analyze proximity in real-time. These efforts aim to improve the effectiveness of social distancing measures, inform public health policy, and enhance pandemic preparedness through improved surveillance and risk management. The resulting insights have implications for both pandemic response and the broader field of public health, informing the design of more effective and equitable interventions.