On-site quantification and infection risk assessment of airborne SARS-CoV-2 virus via a nanoplasmonic bioaerosol sensing system in healthcare settings

Source avec lien : Advanced Science, (Prépublication). 10.1002/advs.202204774

La quantification sur site et l’évaluation du risque d’infection à un stade précoce du coronavirus 2 du syndrome respiratoire aigu sévère (SRAS-CoV-2) en suspension dans l’air avec une haute résolution spatio-temporelle constituent une approche prometteuse pour atténuer la propagation de la pandémie de coronavirus 2019 (COVID-19) et éclairer les décisions visant à sauver des vies. Nous présentons ici un système de collecte de bioaérosols assisté par condensation (croissance hygroscopique) et de détection photothermique plasmonique (CAPS) pour l’analyse quantitative des risques sur site des aérosols chargés de virus SRAS-CoV-2.

Abstract On-site quantification and early-stage infection risk assessment of airborne severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with high spatiotemporal resolution is a promising approach for mitigating the spread of coronavirus disease 2019 (COVID-19) pandemic and informing life-saving decisions. Here, a condensation (hygroscopic growth)-assisted bioaerosol collection and plasmonic photothermal sensing (CAPS) system for on-site quantitative risk analysis of SARS-CoV-2 virus-laden aerosols is presented. The CAPS system provided rapid thermoplasmonic biosensing results after an aerosol-to-hydrosol sampling process in COVID-19-related environments including a hospital and a nursing home. The detection limit reached 0.25 copies/µL in the complex aerosol background without further purification. More importantly, the CAPS system enabled direct measurement of the SARS-CoV-2 virus exposures with high spatiotemporal resolution. Measurement and feedback of the results to healthcare workers and patients via a QR-code are completed within two hours. Based on a dose-responseµ model, it is used the plasmonic biosensing signal to calculate probabilities of SARS-CoV-2 infection risk and estimate maximum exposure durations to an acceptable risk threshold in different environmental settings.

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