Martell Matthew, Salazar Chris, Errett Nicole A, Miles Scott B, Wartman Joseph, Choe John Y
Industrial & Systems Engineering, University of Washington, Seattle, WA, United States of America.
Environmental & Occupational Health Sciences, University of Washington, Seattle, WA, United States of America.
PLoS One. 2024 Dec 5;19(12):e0315132. doi: 10.1371/journal.pone.0315132. eCollection 2024.
Social distancing, defined as maintaining a minimum interpersonal distance (often 6 ft or 1.83 m), is a non-pharmaceutical intervention to reduce infectious disease transmission. While numerous quantitative studies have examined people's social distancing behaviors using mobile phone data, large-scale quantitative analyses of adherence to suggested minimum interpersonal distances are lacking. We analyzed pedestrians' social distancing behaviors of using 3 years of street view imagery collected in a metropolitan city (Seattle, WA, USA) during the COVID-19 pandemic. We employed computer vision techniques to locate pedestrians in images, and a geometry-based algorithm to estimate physical distance between them. Our results indicate that social distancing behaviors correlated with key factors such as vaccine availability, seasonality, and local socioeconomic data. We also identified behavioral differences at various points of interest within the city (e.g., parks, schools, faith-based organizations, museums). This work represents a first of its kind longitudinal study of outdoor social distancing behaviors using computer vision. Our findings provide key insights for policymakers to understand and mitigate infectious disease transmission risks in outdoor environments.
社交距离被定义为保持最小人际距离（通常为6英尺或1.83米），是一种减少传染病传播的非药物干预措施。虽然许多定量研究利用手机数据研究了人们的社交距离行为，但缺乏对建议的最小人际距离遵守情况的大规模定量分析。我们分析了在新冠疫情期间，美国华盛顿州西雅图市三年街景图像中行人的社交距离行为。我们采用计算机视觉技术在图像中定位行人，并使用基于几何的算法来估计他们之间的实际距离。我们的结果表明，社交距离行为与疫苗可及性、季节性和当地社会经济数据等关键因素相关。我们还识别出了城市内不同兴趣点（如公园、学校、宗教组织、博物馆）的行为差异。这项工作是首次使用计算机视觉对户外社交距离行为进行的纵向研究。我们的研究结果为政策制定者了解和减轻户外环境中的传染病传播风险提供了关键见解。
