Predictive and retrospective modelling of airborne infection risk using monitored carbon dioxide
Predictive and retrospective modelling of airborne infection risk using monitored carbon dioxide
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DOI：
10.1177/1420326x211043564
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发表时间：
2021-09-28
影响因子：
3.6
通讯作者：
Linden, P. F.
中科院分区：
文献类型：
--
作者：
Burridge, Henry C.;Fan, Shiwei;Linden, P. F.
需要更好地了解远距离感染（此处称为“空气传播”）的风险，在COVID-19大流行期间尤为紧迫。我们提出了一种方法来确定空气传播的相对风险，可以很容易地部署与模拟或监测的CO2数据和室内空间内的占用水平。对于经常或持续被同一群人占据的空间，例如开放式办公室或学校教室，我们制定了协议来评估这种定期参加工作或学校的空气传播感染的绝对风险。我们提出了一种方法来轻松地计算所产生的二次感染的预期数量，从一个经常参加成为传染性和保持在这些空间内的前/无症状。我们证明了我们的模型，通过计算一个模拟的开放式办公室的风险，并通过使用一个小的自然通风的办公室内记录的监测数据。此外，通过从监测的CO2推断通风率，我们表明空气传播感染的估计可以准确地重建，从而提供更明智的回顾性建模范围，如果爆发发生在CO2监测的空间。通风良好的空间似乎不太可能对空气传播的感染有重大影响。然而，即使是办公室内条件的适度变化，或疾病的新变种，通常也会导致更令人不安的预测。
The risk of long range, herein 'airborne', infection needs to be better understood and is especially urgent during the COVID-19 pandemic. We present a method to determine the relative risk of airborne transmission that can be readily deployed with either modelled or monitored CO2 data and occupancy levels within an indoor space. For spaces regularly, or consistently, occupied by the same group of people, e.g. an open-plan office or a school classroom, we establish protocols to assess the absolute risk of airborne infection of this regular attendance at work or school. We present a methodology to easily calculate the expected number of secondary infections arising from a regular attendee becoming infectious and remaining pre/asymptomatic within these spaces. We demonstrate our model by calculating risks for both a modelled open-plan office and by using monitored data recorded within a small naturally ventilated office. In addition, by inferring ventilation rates from monitored CO2, we show that estimates of airborne infection can be accurately reconstructed, thereby offering scope for more informed retrospective modelling should outbreaks occur in spaces where CO2 is monitored. Well-ventilated spaces appear unlikely to contribute significantly to airborne infection. However, even moderate changes to the conditions within the office, or new variants of the disease, typically result in more troubling predictions.