Rainey Jeanette J, Cheriyadat Anil, Radke Richard J, Suzuki Crumly Julie, Koch Daniel B
Division of Global Migration and Quarantine, Centers for Disease Control and Prevention, Atlanta, GA, USA.
BMC Public Health. 2014 Oct 24;14:1101. doi: 10.1186/1471-2458-14-1101.
Current approaches for estimating social mixing patterns and infectious disease transmission at mass gatherings have been limited by various constraints, including low participation rates for volunteer-based research projects and challenges in quantifying spatially and temporally accurate person-to-person interactions. We developed a proof-of-concept project to assess the use of automated video analysis for estimating contact rates of attendees of the GameFest 2013 event at Rensselaer Polytechnic Institute (RPI) in Troy, New York.
Video tracking and analysis algorithms were used to estimate the number and duration of contacts for 5 attendees during a 3-minute clip from the RPI video. Attendees were considered to have a contact event if the distance between them and another person was ≤1 meter. Contact duration was estimated in seconds. We also simulated 50 attendees assuming random mixing using a geo-spatially accurate representation of the same GameFest location.
The 5 attendees had an overall median of 2 contact events during the 3-minute video clip (range: 0-6). Contact events varied from less than 5 seconds to the full duration of the 3-minute clip. The random mixing simulation was visualized and presented as a contrasting example.
We were able to estimate the number and duration of contacts for 5 GameFest attendees from a 3-minute video clip that can be compared to a random mixing simulation model at the same location. The next phase will involve scaling the system for simultaneous analysis of mixing patterns from hours-long videos and comparing our results with other approaches for collecting contact data from mass gathering attendees.
目前用于估计大型活动中社交混合模式和传染病传播的方法受到各种限制,包括基于志愿者的研究项目参与率低,以及在量化时空上准确的人际互动方面存在挑战。我们开展了一个概念验证项目,以评估使用自动视频分析来估计纽约州特洛伊市伦斯勒理工学院(RPI)2013年游戏节活动参与者的接触率。
使用视频跟踪和分析算法,从RPI的视频中选取一段3分钟的片段,估计5名参与者的接触次数和接触时长。如果参与者与另一个人的距离≤1米,则认为发生了接触事件。接触时长以秒为单位进行估计。我们还使用该游戏节地点的地理空间精确表示,模拟了50名随机混合的参与者。
在3分钟的视频片段中,这5名参与者的接触事件总数中位数为2次(范围:0 - 6次)。接触事件的时长从不到5秒到3分钟片段的整个时长不等。随机混合模拟以可视化形式呈现,并作为对比示例展示。
我们能够从一段3分钟的视频片段中估计5名游戏节参与者的接触次数和接触时长,并且可以与同一地点的随机混合模拟模型进行比较。下一阶段将涉及扩大该系统规模,以便对长达数小时的视频中的混合模式进行同步分析,并将我们的结果与其他从大型活动参与者收集接触数据的方法进行比较。