On-Site Quantification and Infection Risk Assessment of Airborne SARS-CoV-2 Virus Via a Nanoplasmonic Bioaerosol Sensing System in Healthcare Settings

被引:12
|
作者
Qiu, Guangyu [1 ,2 ,3 ]
Spillmann, Martin [1 ]
Tang, Jiukai [1 ,2 ]
Zhao, Yi-Bo [1 ,2 ]
Tao, Yile [1 ]
Zhang, Xiaole [1 ]
Geschwindner, Heike [4 ]
Saleh, Lanja [5 ]
Zingg, Walter [6 ]
Wang, Jing [1 ,2 ]
机构
[1] Swiss Fed Inst Technol, Inst Environm Engn, CH-8093 Zurich, Switzerland
[2] Swiss Fed Labs Mat Sci & Technol, Lab Adv Analyt Technol, Empa, CH-8600 Dubendorf, Switzerland
[3] Shanghai Jiao Tong Univ, Inst Med Robot, Shanghai, Peoples R China
[4] Senior Hlth Ctr City Zurich, Nursing Res & Sci, Zurich, Switzerland
[5] Univ Zurich, Univ Hosp Zurich, Inst Clin Chem, CH-8091 Zurich, Switzerland
[6] Univ Hosp Zurich, Clin Infect Dis & Hosp Hyg, CH-8091 Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
airborne transmission; bioaerosols; biosensors; coronavirus; COVID-19; plasmonics; risk assessment;
D O I
10.1002/advs.202204774
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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/mu L 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-response mu 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.
引用
收藏
页数:11
相关论文
共 50 条
  • [31] A coupled experimental and statistical approach for an assessment of SARS-CoV-2 infection risk at indoor event locations
    Siebler, Lukas
    Rathje, Torben
    Calandri, Maurizio
    Stergiaropoulos, Konstantinos
    Donker, Tjibbe
    Richter, Bernhard
    Spahn, Claudia
    Nusseck, Manfred
    BMC PUBLIC HEALTH, 2023, 23 (01)
  • [32] Integrated Microfluidic-Based Platforms for On-Site Detection and Quantification of Infectious Pathogens: Towards On-Site Medical Translation of SARS-CoV-2 Diagnostic Platforms
    Escobar, Andres
    Chiu, Phyllis
    Qu, Jianxi
    Zhang, Yushan
    Xu, Chang-qing
    MICROMACHINES, 2021, 12 (09)
  • [33] Burden, risk assessment, surveillance and management of SARS-CoV-2 infection in health workers: a scoping review
    Federica Calò
    Antonio Russo
    Clarissa Camaioni
    Stefania De Pascalis
    Nicola Coppola
    Infectious Diseases of Poverty, 9
  • [34] Burden, risk assessment, surveillance and management of SARS-CoV-2 infection in health workers: a scoping review
    Calo, Federica
    Russo, Antonio
    Camaioni, Clarissa
    De Pascalis, Stefania
    Coppola, Nicola
    INFECTIOUS DISEASES OF POVERTY, 2020, 9 (01)
  • [35] Burden, risk assessment, surveillance and management of SARS-CoV-2 infection in health workers: a scoping review
    Cal Federica
    Russo Antonio
    Camaioni Clarissa
    De Pascalis Stefania
    Coppola Nicola
    贫困所致传染病(英文), 2020, 09 (05) : 1 - 11
  • [36] An estimation of airborne SARS-CoV-2 infection transmission risk in New York City nail salons
    Harrichandra, Amelia
    Ierardi, A. Michael
    Pavilonis, Brian
    TOXICOLOGY AND INDUSTRIAL HEALTH, 2020, 36 (09) : 634 - 643
  • [37] Longitudinal assessment of symptoms and risk of SARS-CoV-2 infection in healthcare workers across 5 hospitals to understand ethnic differences in infection risk.
    Valdes, Ana M.
    Moon, James C.
    Vijay, Amrita
    Chaturvedi, Nish
    Norrish, Alan
    Ikram, Adeel
    Craxford, Simon
    Cusin, Lola M. L.
    Nightingale, Jessica
    Semper, Amanda
    Brooks, Timothy
    McKnight, Aine
    Kurdi, Hibba
    Menni, Cristina
    Tighe, Patrick
    Noursadeghi, Mahdad
    Aithal, Guruprasad
    Treibel, Thomas A.
    Ollivere, Benjamin J.
    Manisty, Charlotte
    ECLINICALMEDICINE, 2021, 34
  • [38] A Risk Prediction Model and Risk Score of SARS-CoV-2 Infection Following Healthcare-Related Exposure
    Sripanidkulchai, Kantarida
    Rattanaumpawan, Pinyo
    Ratanasuwan, Winai
    Angkasekwinai, Nasikarn
    Assanasen, Susan
    Werarak, Peerawong
    Navanukroh, Oranich
    Phatharodom, Phatharajit
    Tocharoenchok, Teerapong
    TROPICAL MEDICINE AND INFECTIOUS DISEASE, 2022, 7 (09)
  • [39] Risk factors and on-site simulation of environmental transmission of SARS-CoV-2 in the largest wholesale market of Beijing, China
    Li, Xia
    Wang, Qin
    Ding, Pei
    Cha, Yu'e
    Mao, Yixin
    Ding, Cheng
    Gu, Wen
    Wang, Youbin
    Ying, Bo
    Zhao, Xiaoning
    Pan, Lijun
    Li, Yunpu
    Chang, Junrui
    Meng, Congshen
    Zhou, Jun
    Tang, Zhigang
    Sun, Ruofeng
    Deng, Fuchang
    Wang, Chong
    Li, Li
    Wang, Jiao
    MacIntyre, C. Raina
    Wu, Zunyou
    Feng, Zijian
    Tang, Song
    Xu, Dongqun
    SCIENCE OF THE TOTAL ENVIRONMENT, 2021, 778
  • [40] SARS-CoV-2: Nutritional determinants of reducing the risk of infection of the central nervous system
    Szponar, Lucjan
    Matczuk, Ewa
    POSTEPY PSYCHIATRII I NEUROLOGII, 2021, 30 (02): : 130 - 140