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建立模型以分析影响地铁车厢内 SARS-CoV-2 暴露的因素。

Modeling the factors that influence exposure to SARS-CoV-2 on a subway train carriage.

机构信息

Defence Science and Technology Laboratory, Salisbury, UK.

School of Civil Engineering, University of Leeds, Leeds, UK.

出版信息

Indoor Air. 2022 Feb;32(2):e12976. doi: 10.1111/ina.12976. Epub 2022 Feb 8.

Abstract

We propose the Transmission of Virus in Carriages (TVC) model, a computational model which simulates the potential exposure to SARS-CoV-2 for passengers traveling in a subway rail system train. This model considers exposure through three different routes: fomites via contact with contaminated surfaces; close-range exposure, which accounts for aerosol and droplet transmission within 2 m of the infectious source; and airborne exposure via small aerosols which does not rely on being within 2 m distance from the infectious source. Simulations are based on typical subway parameters and the aim of the study is to consider the relative effect of environmental and behavioral factors including prevalence of the virus in the population, number of people traveling, ventilation rate, and mask wearing as well as the effect of model assumptions such as emission rates. Results simulate generally low exposures in most of the scenarios considered, especially under low virus prevalence. Social distancing through reduced loading and high mask-wearing adherence is predicted to have a noticeable effect on reducing exposure through all routes. The highest predicted doses happen through close-range exposure, while the fomite route cannot be neglected; exposure through both routes relies on infrequent events involving relatively few individuals. Simulated exposure through the airborne route is more homogeneous across passengers, but is generally lower due to the typically short duration of the trips, mask wearing, and the high ventilation rate within the carriage. The infection risk resulting from exposure is challenging to estimate as it will be influenced by factors such as virus variant and vaccination rates.

摘要

我们提出了病毒在车厢内传播(TVC)模型,这是一个计算模型,模拟了在地铁轨道系统列车中旅行的乘客潜在暴露于 SARS-CoV-2 的情况。该模型考虑了三种不同的暴露途径:通过接触受污染表面的污染物;近距离接触,考虑了 2 米内感染源的气溶胶和飞沫传播;以及不需要与感染源距离 2 米以内的空气传播,通过小气溶胶传播。模拟基于典型的地铁参数,研究目的是考虑环境和行为因素的相对影响,包括病毒在人群中的流行率、出行人数、通风率以及戴口罩情况,以及排放率等模型假设的影响。结果模拟了在大多数情况下暴露水平普遍较低,特别是在病毒流行率较低的情况下。通过减少负载和高口罩佩戴率的社交距离可以显著减少所有途径的暴露。最高预测剂量通过近距离接触发生,而污染物途径不能忽视;两种途径的暴露都依赖于涉及相对较少个体的不频繁事件。通过空气传播途径模拟的暴露在乘客中更均匀,但由于行程通常较短、佩戴口罩和车厢内通风率高,因此通常较低。暴露引起的感染风险难以估计,因为它将受到病毒变体和疫苗接种率等因素的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5a83/9111599/9828ca0dd5ab/INA-32-0-g004.jpg

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