Multi-scenario surveillance of respiratory viruses in aerosols with sub-single-copy spatial resolution

Bao Li, Baobao Lin, Yan Wang, Ye Shi, Wu Zeng, Yulan Zhao, Yin Gu, Chang Liu, Hui Gao, Hao Cheng, Xiaoqun Zheng, Guangxin Xiang (), Guiqiang Wang () and Peng Liu ()
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Bao Li: Tsinghua University
Baobao Lin: Tsinghua University
Yan Wang: Peking University First Hospital
Ye Shi: Wenzhou Medical University
Wu Zeng: Tsinghua University
Yulan Zhao: Changping Laboratory
Yin Gu: China Astronaut Research and Training Center
Chang Liu: Tsinghua University
Hui Gao: Peking University First Hospital
Hao Cheng: Peking University First Hospital
Xiaoqun Zheng: Wenzhou Medical University
Guangxin Xiang: Wenzhou Medical University
Guiqiang Wang: Peking University First Hospital
Peng Liu: Tsinghua University

Nature Communications, 2024, vol. 15, issue 1, 1-12

Abstract: Abstract Highly sensitive airborne virus monitoring is critical for preventing and containing epidemics. However, the detection of airborne viruses at ultra-low concentrations remains challenging due to the lack of ultra-sensitive methods and easy-to-deployment equipment. Here, we present an integrated microfluidic cartridge that can accurately detect SARS-COV-2, Influenza A, B, and respiratory syncytial virus with a sensitivity of 10 copies/mL. When integrated with a high-flow aerosol sampler, our microdevice can achieve a sub-single-copy spatial resolution of 0.83 copies/m3 for airborne virus surveillance with an air flow rate of 400 L/min and a sampling time of 30 minutes. We then designed a series of virus-in-aerosols monitoring systems (RIAMs), including versions of a multi-site sampling RIAMs (M-RIAMs), a stationary real-time RIAMs (S-RIAMs), and a roaming real-time RIAMs (R-RIAMs) for different application scenarios. Using M-RIAMs, we performed a comprehensive evaluation of 210 environmental samples from COVID-19 patient wards, including 30 aerosol samples. The highest positive detection rate of aerosol samples (60%) proved the aerosol-based SARS-CoV-2 monitoring represents an effective method for spatial risk assessment. The detection of 78 aerosol samples in real-world settings via S-RIAMs confirmed its reliability for ultra-sensitive and continuous airborne virus monitoring. Therefore, RIAMs shows the potential as an effective solution for mitigating the risk of airborne virus transmission.

Date: 2024
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DOI: 10.1038/s41467-024-53059-x

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