The airborne transmission of disease-causing pathogens like the SARS-CoV-2 virus responsible for the COVID-19 pandemic is known to occur not only through violent expiratory events like coughs or sneezes , but also during activities like singing and even speech. We study, using direct numerical simulation (DNS), the transport of virus-laden aerosols generated during human speech. We show that the use of the " top-hat " formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3. We propose an alternative method of estimating viral ingestion that includes exposure through the eyes and mouth , to provide more realistic estimates of the risk of infection . This method is then used to determine infection probabilities when two speakers facing each other are engaged in a short conversation. We show that the interaction between the two oppositely-directed speech jetscan increase or decrease infection probabilities, which peak for a height difference between the speakers of about 10cm (30cm) when the axial separationbetween them is 2ft (6ft). These results can help improve the existing public health guidelines for COVID mitigation by introducing a lateral shift between people during short conversations. Moreover, simulations like these can provide useful inputs to the existing epidemiological models for improving their reliability and accuracy .
Pathogens like the SARS-CoV-2 are transmitted not only through violent expiratory events like coughing , but also through routine activities like breathing/speaking/singing. We perform direct numerical simulations of the turbulent transport of potentially infectious aerosols in short conversations. It is shown that a two-way conversation significantly reduces the aerosol exposure compared to a relative monologue by one person and relative silence of the other. This is because the interaction of the jets ejected from the mouth of each speaker produce a " canceling " effect. Unequal conversation is shown to significantly increase the risk of infection to the person who talks less. Interestingly, a small height difference is worse for infection spread, due to reduced interference between the two speech jets, than two faces at the same level! For small axial separation, speech jets show large oscillations and reach the other person intermittently. We suggest a range of lateral separations between two people to minimize transmission risk. A realistic estimate of the infection probability is provided by including exposure through eyes and mouth, in addition to the more common method of using inhaled virions alone. We expect that our results will provide useful inputs to epidemiological models and to disease management .
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The airborne transmission of disease-causing pathogens
Pathogens
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virus responsible for the COVID-19 pandemic is known to occur
are transmitted
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coughs or sneezes
coughing
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during activities like singing and even speech. We study, using direct numerical simulation (DNS), the transport of virus-laden aerosols generated during human speech. We show that
through routine activities like breathing/speaking/singing. We perform direct numerical simulations of the turbulent transport of potentially infectious aerosols in short conversations. It is shown that a two-way conversation significantly reduces the aerosol exposure compared to a relative monologue by one person and relative silence of the other. This is because the interaction of
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use of the
jets ejected from the mouth of each speaker produce a
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top-hat
canceling
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formulation for steady speech flows can underestimate infection probabilities by a factor of 2-3. We propose an alternative method of estimating viral ingestion that includes exposure through the eyes and mouth , to provide more realistic estimates of
effect. Unequal conversation is shown to significantly increase
R
. This method is then used to determine infection probabilities when two speakers facing each other are engaged in a short conversation. We show that the interaction
to the person who talks less. Interestingly, a small height difference is worse for infection spread, due to reduced interference
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oppositely-directed speech jetscan increase or decrease infection probabilities, which peak for a height difference between the speakers of about 10cm (30cm) when the axial separationbetween them is 2ft (6ft). These results can help improve the existing public health guidelines for COVID mitigation by introducing a lateral shift between people during short conversations. Moreover, simulations like these can
speech jets, than two faces at the same level! For small axial separation, speech jets show large oscillations and reach the other person intermittently. We suggest a range of lateral separations between two people to minimize transmission risk. A realistic estimate of the infection probability is provided by including exposure through eyes and mouth, in addition to the more common method of using inhaled virions alone. We expect that our results will
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the existing epidemiological models for improving their reliability and accuracy
epidemiological models and to disease management