Dataset Information

Biological fluid dynamics of airborne COVID-19 infection.

ABSTRACT: Abstract:We review the state of knowledge on the bio-fluid dynamic mechanisms involved in the transmission of the infection from SARS-CoV-2. The relevance of the subject stems from the key role of airborne virus transmission by viral particles released by an infected person via coughing, sneezing, speaking or simply breathing. Speech droplets generated by asymptomatic disease carriers are also considered for their viral load and potential for infection. Proper understanding of the mechanics of the complex processes whereby the two-phase flow emitted by an infected individual disperses into the environment would allow us to infer from first principles the practical rules to be imposed on social distancing and on the use of facial and eye protection, which to date have been adopted on a rather empirical basis. These measures need compelling scientific validation. A deeper understanding of the relevant biological fluid dynamics would also allow us to evaluate the contrasting effects of natural or forced ventilation of environments on the transmission of contagion: the risk decreases as the viral load is diluted by mixing effects but contagion is potentially allowed to reach larger distances from the infected source. To that end, our survey supports the view that a formal assessment of a number of open problems is needed. They are outlined in the discussion. Graphic abstract:

SUBMITTER: Seminara G

PROVIDER: S-EPMC7429142 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Biological fluid dynamics of airborne COVID-19 infection.

Seminara Giovanni G Carli Bruno B Forni Guido G Fuzzi Sandro S Mazzino Andrea A Rinaldo Andrea A

Rendiconti Lincei. Scienze fisiche e naturali 20200816 3

<h4>Abstract</h4>We review the state of knowledge on the bio-fluid dynamic mechanisms involved in the transmission of the infection from SARS-CoV-2. The relevance of the subject stems from the key role of airborne virus transmission by viral particles released by an infected person via coughing, sneezing, speaking or simply breathing. Speech droplets generated by asymptomatic disease carriers are also considered for their viral load and potential for infection. Proper understanding of the mechan ...[more]

PMID: 32837713

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Project description:The classic Wells-Riley model is widely used for estimation of the transmission risk of airborne pathogens in indoor spaces. However, the predictive capability of this zero-dimensional model is limited as it does not resolve the highly heterogeneous spatiotemporal distribution of airborne pathogens, and the infection risk is poorly quantified for many pathogens. In this study we address these shortcomings by developing a novel spatiotemporally resolved Wells-Riley model for prediction of the transmission risk of different COVID-19 variants in indoor environments. This modelling framework properly accounts for airborne infection risk by incorporating the latest clinical data regarding viral shedding by COVID-19 patients and SARS-CoV-2 infecting human cells. The spatiotemporal distribution of airborne pathogens is determined via computational fluid dynamics (CFD) simulations of airflow and aerosol transport, leading to an integrated model of infection risk associated with the exposure to SARS-CoV-2, which can produce quantitative 3D infection risk map for a specific SARS-CoV-2 variant in a given indoor space. Application of this model to airborne COVID-19 transmission within a hospital ward demonstrates the impact of different virus variants and respiratory PPE upon transmission risk. With the emergence of highly contagious SARS-CoV-2 variants such as the Delta and Omicron strains, respiratory PPE alone may not provide effective protection. These findings suggest a combination of optimal ventilation and respiratory PPE must be developed to effectively control the transmission of COVID-19 in healthcare settings and indoor spaces in general. This generalised risk estimation framework has the flexibility to incorporate further clinical data as such becomes available, and can be readily applied to consider a wide range of factors that impact transmission risk, including location and movement of infectious persons, virus variant and stage of infection, level of PPE and vaccination of infectious and susceptible individuals, impacts of coughing, sneezing, talking and breathing, and natural and mechanised ventilation and filtration.

Dataset Information

Biological fluid dynamics of airborne COVID-19 infection.

Publications

Biological fluid dynamics of airborne COVID-19 infection.

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