How To Measure COVID19 Risks in Public Places- Classroom, Commute & Office

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NANNING, April 8, 2020 . Passengers get off the train G431 at Nanning East Railway Station in Nanning City, south China’s Guangxi Zhuang Autonomous Region, April 8, 2020. Train G431 from Wuhan to Nanning, the first train leaving Hubei Province from Wuhan since the outbound travel restrictions were lifted, reopened its service on Wednesday.
Wuhan on Wednesday lifted outbound travel restrictions, after almost 11 weeks of lockdown to stem the spread of COVID-19. (Photo by Cao Yiming/Xinhua via Getty) (Xinhua/Cao Yiming via Getty Images)
  • The pandemic has taken a toll on normal life and people are craving to go back to their regular activities.
  • However, going back to classrooms and offices might not be that easy.
  • The potential risk of infection and catching the virus remains.
  • This leads to the development of a new model using which you can determine the risk of your activity by looking at the scenarios.
  • Your classrooms, offices, trains, and buses that you are taking, the events that you are going to can be evaluated by this method.

The pandemic has made it absolutely necessary to measure the risk of our daily activities and go for a holistic solution, says an expert analyzed data article by the National Geographic.

Charting the riskiness of our activities

A recent modeling effort led by Jose-Luis Jimenez at the University of Colorado Boulder,  may help provide some clues.  By this method, one can estimate the riskiness of different activities based on one potential route of coronavirus spread: itty-bitty particles known as aerosols.

The risk of infection from SARS-CoV-2 aerosols

Note: 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 Risk areas

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.

How does the new model work?

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

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

How good is this model?

The model provides a rough estimation of risk, Jimenez cautions. 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.

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Source: National Geographic

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