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预测大规模大学校园内的COVID-19病例,使用建筑环境监测
Aaron Hinz1,2, Jason A Moggridge3, Hanna Ke3
1Department of Biology, University of Ottawa, Ottawa, Ontario, Canada.
概括
在大学楼上的SARS-CoV-2环境采样补充了废水监测. 这种建筑环境方法可以预测校园和特定建筑物的COVID-19病例.
科学领域:
- 环境科学环境科学
- 流行病学 流行病学
- 公共卫生 公共卫生
背景情况:
- 废水监测是人口层面SARS-CoV-2监测的关键.
- 建筑环境采样在大学等集体环境中提供了空间精细的病毒检测.
研究的目的:
- 评估在大学建筑楼层对SARS-CoV-2环境监测的实用性.
- 确定建筑环境采样是否可以预测校园和建筑层面的COVID-19病例.
主要方法:
- 在太华大学进行前性研究 (2021年9月至2022年4月).
- 每周两次从六个建筑物收集554个地板表面的擦拭物.
- 使用定量PCR分析了SARS-CoV-2RNA的抽样.
- 使用Poisson回归来建模基于地板抽样阳性,二氧化碳水平,Wi-Fi使用和城市废水数据的全校和建筑层次的COVID-19病例.
主要成果:
- 13%的地板拭子检测出SARS-CoV-2RNA的阳性.
- 地板抽样阳性与校园内COVID-19病例有很强的相关性 (斯皮尔曼r = 0.74).
- 城市废水SARS-CoV-2信号也与校园内病例相关 (斯皮尔曼r = 0.50).
- 建筑环境检测预测了个别建筑层次的COVID-19病例.
结论:
- 在地板上的SARS-CoV-2RNA检测与大学校园的COVID-19发病率密切相关.
- 机构建筑环境采样,结合废水监测,可以预测整个校园和建筑层面的COVID-19病例.
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