Nat Geo presents tool for risk of airborne
High-speed photography shows a sneeze can blast saliva and mucus well beyond current social distancing guidelines, and tiny droplets can remain in the air longer than thought. Source: National Geographic.
Maya Wei-Haas & Kennedy Elliott, Measure the risk of airborne COVID-19 in your office, classroom, or bus ride, National Geographic, 11 August 2020
Can kids go back to crowded schools? Is it safe to eat dinner with friends? Use this mathematical model to help provide some clues.
AMID THE PANDEMIC, once normal activities are now peppered with questions and concerns. Can kids go back to crowded schools? Is it safe to eat dinner with friends? Should we worry about going for a run?
A recent modeling effort may help provide some clues. Led by Jose-Luis Jimenez at the University of Colorado Boulder, the charts below estimate the riskiness of different activities based on one potential route of coronavirus spread: itty-bitty particles known as aerosols. (Read more about what “airborne coronavirus” means and how to protect yourself).
The risk of infection from SARS-CoV-2 aerosols – click the image below to view interactive modelling.
Coughing, singing, talking, or even breathing sends spittle flying in a range of sizes. The closer you are to the spewer, the greater the chance of exposure to large, virus-laden droplets that can be inhaled or land in your eyes.
But many scientists have also grown concerned about the potential risks of aerosols—the smallest of these particles—which may float across rooms and cause infections. It’s a worry that’s greatest where ventilation is poor and airborne particulates could build. While the World Health Organization recently acknowledged that aerosol transmission cannot be ruled out for some situations, they emphasized more research is needed to conclusively demonstrate its role in the spread of the virus.
“We do not have a ton of information, but we cannot afford to wait for a ton of information,” Jimenez says.
The new model incorporates what is known about the coronavirus’s spread from case reports of potential airborne transmission, such as the Washington choir practice where one person was linked to dozens of other infections during a 2.5-hour rehearsal. It’s further calibrated based on studies that attempt to untangle how much virus people emit while performing activities that involve exhalation. An important note: the model does not account for how the risk increases with closer proximity, where droplet and aerosol concentrations will be higher, or for people touching their eyes or noses with contaminated hands.
To calculate the possible aerosol risks in various environments, users can tweak a host of parameters, such as the size of a group, the room size, or the effectiveness of masks.
The risk of infection from SARS-CoV-2 aerosols if you experience a given scenario 20 times
– click the image below to view interactive modelling.
Note: This scenario assumes a well-fitted N95 mask blocks 95 percent of airborne particles. A hot spot is defined as having an infection rate of 3 percent in the local population, and a low infection area has a 0.03 percent infection rate. Unless otherwise specified, the scenarios assume 50 percent of particles pass through masks, 12 square feet of space per person at each event, and an infection rate of 2 percent. The model does not fully account for how your risk increases the closer you get to an infected person, where the concentration of both aerosols and respiratory droplets will be higher. Potential risk from contaminated surfaces is also not included. All scenarios assume constant values for room temperature, pressure, humidity, and how quickly particles settle out of the air onto surfaces due to gravity. The model also assumes that no one in the local population is immune. Source: Jose-Luis Jimenez, University of Colorado Boulder.
The model provides a rough estimation of risk, Jimenez cautions. (Of course, no model can explain exactly what will happen in reality.) Still, it can provide valuable clues to the relative risks of different activities. The risk also depends on the prevalence of the disease in your area, which users can input into the model to change the potential number of infected people in a given group.
As with any model, the calculations must make some assumptions, such as requiring the air to be mixed, so the virus is dispersed throughout the room. (This is why the model does not account for close proximity with other people.) That’s not always the case in the real world, but it is appropriate for many situations, says Shelly Miller, an expert in indoor air pollution at the University of Colorado Boulder, who led the modeling effort to characterize the potential aerosol spread during the Washington choir practice.
The model underscores the importance of widespread use of masks and the risks of COVID-19 transmission in crowded rooms and poorly ventilated conditions—and in any of these settings, time is key, says Linsey Marr, a civil and environmental engineer at Virginia Tech who specializes in airborne transmission of viruses and provided feedback on the model. The longer anyone spends in a poorly ventilated or crowded space, the greater the predicted risk of falling ill.