从观察到的运动模拟COVID19的传递：一个基于Agent的教室分散模型
Simulating COVID19 Transmission From Observed Movement: An Agent-Based Model of Classroom Dispersion
摘要：
目前的COVID-19传播模型通过报告或假设的相互作用预测感染。在这里，我们利用相互作用的高分辨率观察来模拟感染过程。超宽无线射频识别（RFID）系统被用来跟踪实时的物理运动和方向定向的儿童和他们的老师在4个学前班，共34观察。基于代理的传播模型结合观察到的相互作用模式（个人的距离和方向）与CDC发布的风险指南，以估计感染的患者零上课对整体感染的比例，平均传播率和出现症状的个人的时间滞后的传播影响。这些指标突出了减少教室密度和教师接种疫苗的预防作用。将教室密度降低到一半与总体感染比例下降18.2%相关，而教师接种疫苗与下降25.3%相关。教室传播动态的模拟结果可能会为面对COVID-19和类似传染病威胁的公共政策提供信息。
英文摘要：
Current models of COVID-19 transmission predict infection from reported or assumed interactions. Here we leverage high-resolution observations of interaction to simulate infectious processes. Ultra-Wide Radio Frequency Identification (RFID) systems were employed to track the real-time physical movements and directional orientation of children and their teachers in 4 preschool classes over a total of 34 observations. An agent-based transmission model combined observed interaction patterns (individual distance and orientation) with CDC-published risk guidelines to estimate the transmission impact of an infected patient zero attending class on the proportion of overall infections, the average transmission rate, and the time lag to the appearance of symptomatic individuals. These metrics highlighted the prophylactic role of decreased classroom density and teacher vaccinations. Reduction of classroom density to half capacity was associated with an 18.2% drop in overall infection proportion while teacher vaccination receipt was associated with a 25.3%drop. Simulation results of classroom transmission dynamics may inform public policy in the face of COVID-19 and similar infectious threats.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
