Fig. 5: Performance evaluation and real-world deployment of S-RIAMs for ultra-sensitive and continuous airborne virus surveillance. | Nature Communications

Fig. 5: Performance evaluation and real-world deployment of S-RIAMs for ultra-sensitive and continuous airborne virus surveillance.

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

Fig. 5: Performance evaluation and real-world deployment of S-RIAMs for ultra-sensitive and continuous airborne virus surveillance.

a Photograph of the experimental setup of the generation and simultaneous detection of SARS-CoV-2 aerosols in a biosafety cabinet. b A histogram of Ct values of mock aerosol samples with varying viral concentrations in the aerosolized liquid stock. Error bars represent mean ± SD (n = 3 independently aerosolized and collected samples). c The fitted relationship between the logarithm of virus input concentration and Ct values. Error bars represent mean ± SD (n = 3 independently aerosolized and collected samples). d Results of 6-day continuous aerosol COVID-19 monitoring using S-RIAMs in an office workplace affected by the COVID-19 epidemic, showing the positive detection rates and the absolute amount of airborne virus in the space. Solid lines represent mean values. (n = 8 independently collected and tested aerosol samples). e Comparison of the positive detection rates and the virus concentrations on day 1 and day 4 of airborne viruses monitoring results around infected individuals within the student dormitory affected by the COVID-19 pandemic, indicating a gradual increase in the number of infected people. Solid lines represent mean values. (n = 10 independently collected and tested aerosol samples). f A scatter plot of the virus concentrations of aerosol RSV samples collected from neonatal RSV-positive areas, including 10 all-positive aerosol samples from 5 neonatal RSV-positive wards.

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