Higher Viral Loads And A Lower Minimal Infective Dose Increases Risk of Aerosol Transmission By SARS-Cov-2

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A new Swiss led study involving researchers from the Swiss Centre for Occupational and Environmental Health-Switzerland, Universidad del Rosario-Colombia, Tokyo University of Science-Japan, Repubblica e Cantone Ticino-Switzerland, Centre for Primary Care and Public Health (Unisanté)-Switzerland and the State Secretariat for Economic Affairs (SECO)-Switzerland has found that higher viral loads and a lower minimal infective dose compared to the SARS-CoV-2 wild type strain increases the risk of aerosol transmission by the SARS-CoV-2 Delta and Omicron variants.

The study findings also importantly show that surgical masks are no longer sufficient in most public settings, while correctly fitted FFP2 respirators still provide sufficient protection, except in high aerosol producing situations such as singing or shouting.
 
Airborne transmission of SARS-CoV-2 is an important route of infection. For the wildtype (WT) only a small proportion of those infected emitted large quantities of the virus.
 
However, the currently prevalent variants of concern, Delta (B1.617.2) and Omicron (B.1.1.529), are characterized by higher viral loads and a lower minimal infective dose compared to the WT.
 
The Omicron Aerosol Transmission study team aimed to describe the resulting distribution of airborne viral emissions and to reassess the risk estimates for public settings given the higher viral load and infectivity.

The study findings were published in the peer reviewed journal: Swiss Medical Weekly. https://smw.ch/article/doi/smw.2022.w30133
 

Figure 1 shows the distributions of viral emissions by the infected populations when speaking quietly for the different variants. The distributions for breathing only and speaking loudly (not shown) look identical but are shifted to lower and higher values respectively.

For Delta, and even more so for Omicron, the distribution is shifted towards very high viral emissions. In the new version of the tool, we maintain the emitter strengths used earlier [2] to define high, very high and super-emitters to ensure consistency between different versions of the tool.

It is important, however, to recognize that these emitter types now represent a much larger proportion of the infected population. Most notable is the strong increase in the frequency of super-emitting individuals, represented in Figure 1 by the area under the curve to the right of the line marking the super-emitters.

Figure 1

Table 1 lists the emission strengths for speaking quietly and compares the key emission characteristics for the WT, Delta and the two Omicron estimates. Super-emitters used to represent about one in 1,000 infected with the WT. They have become much more frequent: amongst those infected with Delta it is one in 30; and for Omicron it is one in 20 or one in 10, depending on the viral load estimate used. Super-emitters’ emissions can rapidly lead to concentrations in indoor environments that were previously associated with super-spreading events [2, 15–18].

This increase is therefore of great concern. But the increases in the proportion of high and very high emitting individuals should not be overlooked. Such emitters can, in a short time, cause critical concentrations in medium-sized and small rooms respectively. This implies that for Omicron, one half to two thirds of the infected population emit sufficient virus into the air to pose a realistic infection risk to others by airborne transmission.

In conclusion, the increased viral load seems likely to be a key contributor to the observed rapid spread of the new variants of concern [3, 19].

Table 1

Descriptive statistics of viral emissions in the PM10-sized fraction with quiet speaking for published viral load data for Delta and for two viral load estimates for Omicron (Ox10 and Ox100). For the predefined emitter types, the percentile (pct.) in the WT distribution and the new percentiles are shown.

Statistics for speaking quietlyDelta [copies cm–3]Ox10 [copies cm–3]Ox100 [copies cm–3]
Mean0.6671.1971.900
Standard deviation2.974.015.22
1st percentile2.55E-082.38E-071.89E-06
Median0.003660.02250.0998
99th percentile13.7519.2024.81
New percentiles of emitter types   
High emitter (WT = 90th pct.)63rd pct.48th pct.35th pct.
Very high emitter (WT = 99th pct.)88th pct.80th pct.70th pct.
Super-emitter (WT = 99.9th pct.)97th pct.94th pct.90th pct.

A further challenge is the much higher infectivity [4], which means that a much lower dose is sufficient to transmit the virus. Table 2 lists frequent public situations that we simulated when the WT was prevalent [2]. Most situations in offices, restaurants, discos and on public transport could be sufficiently addressed by correctly wearing a surgical face mask.

However, for Delta many of these situations have become critical (defined as being above the critical dose). For Omicron, almost all are now critical or even very critical (more than double the critical dose).

In most situations, FFP2 respirators will still provide sufficient protection because they remove at least 95% of inhaled aerosols if properly fitted to the face [20, 21]. However, when spending prolonged time in situations with extreme aerosol formation, not even FFP2 respirators may be sufficient, as shown by the scenario of a super-emitter in a disco where very loud voices are required for communication.

Table 2

Consequences of lower critical doses for frequent public situations in the presence of a super-emitter. Everybody is wearing surgical masks unless otherwise indicated (partly reproduced from [2] under CC BY 4.0). ACH: air changes per hour. Vocal intensity: “talk” = low intensity vocal activity. Interpretation: “critical” = above critical dose, “very critical” = more than twice critical dose.

ScenarioDose in far fieldInterpretation for virus variant
 [copies received]WTDeltaOmicron
4 hours in small office (50 m3, 1 ACH), 5% talk479OKCriticalVery critical
4 hours in open space office (1,000 m3, 1 ACH), 5% talk24OKOKOK
4 hours in open space call centre (1,000 m3, 1 ACH), 60% talk100OKOKBorderline
2 hours in meeting room (100 m3, 3 ACH), 50% talk, 5% loud390OKCriticalVery critical
30 minutes in small shop / boutique (100 m3, 3 ACH), 20% talk451OKCriticalVery critical
2 hours in restaurant (500 m3, 1 ACH), 20% talk, emitter no mask153OKOKCritical
2 hours in disco (300 m3, 3 ACH), 20% loud, 50% heavy dancing, receiver only FFP2379OKCriticalVery critical
1 hour travel by train (57 m3, 7.1 ACH), 20% talk40OKOKOK
1 hour travel by train (57 m3, 7.1 ACH), 20% talk, emitter no mask180OKOKCritical
30-minute trolleybus ride (100 m3, 2 ACH), 20% talk, emitter no mask220OKOKCritical

In conclusion, our modelling and risk assessment suggest that both higher viral load and increased infectivity are likely to be important contributors to the rapid spread of Delta and Omicron. However, there are more ways by which virus variants may, in principle, affect transmission by aerosols. For example, it is not known to what extent aerosol formation is modified in infected individuals, although altered mucus viscosity can lead to such changes [22, 23]. Also, an increase in viral production near the vocal cords, the place where the most aerosols are produced [24, 25], would likely increase the viral emissions. More research is needed to address such questions.

Use case: When using the tool, it is important to understand that the CO2 and viral concentrations in a room follow different mathematical processes. CO2 increases with every additional person. In contrast, the viral concentration follows a stochastic process: it increases only if one of the people in the room is infectious. How much virus can accumulate in a room depends strongly on the emission strength and the activity of the infected person. This can be illustrated by a use example with the tool: a school room for a class of twenty teenagers with a volume of 250 m3 and mechanical ventilation that provides three outside air exchanges per hour. Let’s assume the teacher installs a recirculating air cleaner with a CADR of 500 m3 h-1. The tool predicts CO2 concentrations of 640, 760, 810 and 840 ppm after 15, 30, 45 and 60 minutes respectively for 5% light activity. To confirm that the ventilation works, the teacher can use a simple CO2 monitor to check if the measured time course is in a similar range. CO2-wise, the room is fine. But what about the viral dose? If everyone wears ill-fitting masks, the room should be fine for Delta but no longer for Omicron, especially when considering that they have several classes per day. If everyone wears well-fitted surgical masks, the situation still seems safe. However, an entire singing class would not be advisable because it would require very well-fitted FFP2 respirators to stay below the critical dose, if this is set to 100 virus copies (which would be reached after four minutes if no masks are worn). Therefore, the activities in the classroom should be carefully assessed before they are performed. For those activities that still seem safe, the CO2 time course then indicates whether the ventilation is performing as needed for that activity.

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