Abstract：
Conventional buses, as an indispensable part of the urban public transport system, impose cross-infection risks on passengers. To assess differential risks due to dynamic staying durations and locations, this study considered four spatial distributions (i = 1-4) and six temporal scenarios (j = 1-6) of buses. Based on field measurements and a risk assessment approach combining both short-range and room-scale effects, risks are evaluated properly. The results showed that temporal asynchrony between infected and susceptible individuals significantly affects disease transmission rates. The Control Case assumes that infected and susceptible individuals enter and leave synchronously. However, ignoring temporal asynchrony scenarios, i.e., the Control Case, resulted in overestimation (+30.7 % to +99.6 %) or underestimation (-15.2 % to -69.9 %) of the actual risk. Moreover, the relative difference ratios of room-scale risks between the Control Case and five temporal scenarios are impacted by ventilation. Short-range risk exists only if infected and susceptible individuals have temporal overlap on the bus. Considering temporal and spatial asynchrony, a more realistic total reproduction number (R) can be obtained. Subsequently, the total R was assessed under five temporal scenarios. On average, for the Control Case, the total R was estimated to be +27.3 % higher than j = 1, -9.3 % lower than j = 2, +12.8 % higher than j = 3, +33.0 % lower than j = 4, and + 77.6 % higher than j = 5. This implies the need for a combination of active prevention and real-time risk monitoring to enable rigid travel demand and control the spread of the epidemic.
摘要：
传统巴士,作为城市公共交通系统不可或缺的一部分，给乘客带来交叉感染风险。为了评估动态停留时间和位置造成的差异风险,这项研究考虑了公共汽车的四种空间分布（i=1-4）和六种时间情景（j=1-6）。基于现场测量和结合短程效应和房间尺度效应的风险评估方法，风险评估得当。结果表明，感染和易感个体之间的时间异步显着影响疾病传播率。控制案例假设受感染和易感个体同步进入和离开。然而,忽略时间异步场景，即，控制案例,导致高估（+30.7%至+99.6%）或低估（-15.2%至-69.9%）实际风险。此外，控制案例和五种时间情景之间的房间尺度风险的相对差异比受到通风的影响。只有当感染和易感个体在公共汽车上有时间重叠时，才存在短程风险。考虑到时间和空间的异步性，可以获得更真实的总再现数(R)。随后，在5种时间情景下评估总R.平均而言,对于控制案例，总R估计比j=1高+27.3%,比j=2低-9.3%,比j=3高+12.8%,比j=4低+33.0%,比j=5高+77.6%。这意味着需要积极预防和实时风险监测相结合，实现刚性出行需求，控制疫情蔓延。
