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Prediction and control of aerosol transmission of SARS-CoV-2 in ventilated context: from source to receptor
Global spread of COVID-19 has seriously threatened human life and health. The aerosol transmission route of SARS-CoV-2 is observed often associated with infection clusters under poorly ventilated environment. In the context of COVID-19 pandemic, significant transformation and optimization of traditi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8484231/ https://www.ncbi.nlm.nih.gov/pubmed/34611508 http://dx.doi.org/10.1016/j.scs.2021.103416 |
Sumario: | Global spread of COVID-19 has seriously threatened human life and health. The aerosol transmission route of SARS-CoV-2 is observed often associated with infection clusters under poorly ventilated environment. In the context of COVID-19 pandemic, significant transformation and optimization of traditional ventilation systems are needed. This paper is aimed to offer better understanding and insights into effective ventilation design to maximize its ability in airborne risk control, for particularly the COVID-19. Comprehensive reviews of each phase of aerosol transmission of SARS-CoV-2 from source to receptor are conducted, so as to provide a theoretical basis for risk prediction and control. Infection risk models and their key parameters for risk assessment of SARS-CoV-2 are analyzed. Special focus is given on the efficacy of different ventilation strategies in mitigating airborne transmission. Ventilation interventions are found mainly impacting on the dispersion and inhalation phases of aerosol transmission. The airflow patterns become a key factor in controlling the aerosol diffusion and distribution. Novel and personalized ventilation design, effective integration with other environmental control techniques and resilient HVAC system design to adapt both common and epidemic conditions are still remaining challenging, which need to be solved with the aid of multidisciplinary research and intelligent technologies. |
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