Nav: Home

How at risk are you of getting a virus on an airplane?

March 30, 2020

Fair or not, airplanes have a reputation for germs. However, there are ways to minimize the risks.

Historic research based on group movements of humans and animals suggest three simple rules:
  • move away from those that are too close.

  • move toward those that are far away.

  • match the direction of the movement of their neighbors.
This research is especially used for air travel where there is an increased risk for contagious infection or disease, such as the recent worldwide outbreak of the coronavirus, which causes COVID-19 disease.

"Airlines use several zones in boarding," said Ashok Srinivasan, a professor in the Department of Computer Science University of West Florida. "When boarding a plane, people are blocked and forced to stand near the person putting luggage in the bin -- people are very close to each other. This problem is exacerbated when many zones are used. Deplaning is much smoother and quicker --there isn't as much time to get infected."

Srinivasan is the principal investigator of new research on pedestrian dynamics models that has recently been used in the analysis of procedures to reduce the risk of disease spread in airplanes. The research was published in the journal PLOS ONE in March 2020.

For many years scientists have relied on the SPED (Self Propelled Entity Dynamics) model, a social force model that treats each individual as a point particle, analogous to an atom in molecular dynamics simulations. In such simulations, the attractive and repulsive forces between atoms govern the movement of atoms. The SPED model modifies the code and replaces atoms with humans.

"[The SPED model] changes the values of the parameters that govern interactions between atoms so that they reflect interactions between humans, while keeping the functional form the same," Srinivasan said.

Srinivasan and his colleagues used the SPED model to analyze the risk of an Ebola outbreak in 2015, which was widely covered in news outlets around the world. However, one limitation of the SPED model is that it is slow -- which makes it difficult to make timely decisions. Answers are needed fast in situations such as an outbreak like COVID-19.

The researchers decided there was a need for a model that could simulate the same applications as SPED, while being much faster. They proposed the CALM model (for constrained linear movement of individuals in a crowd). CALM produces similar results to SPED, but is not based on MD code. In other words, CALM was designed to run fast.

Like SPED, CALM was designed to simulate movement in narrow, linear passageways. The results of their research shows that CALM performs almost 60 times faster than the SPED model. Apart from the performance gain, the researchers also modeled additional pedestrian behaviors.

"The CALM model overcame the limitations of SPED where real time decisions are required," Srinivasan said.

Computational Work Using Frontera

The scientists designed the CALM model from scratch so it could run efficiently on computers, especially on GPUs (graphic processing units.

For their research, Srinivasan and colleagues used Frontera, the #5 most powerful supercomputer in the world and fastest academic supercomputer, according to the November 2019 rankings of the Top500 organization. Frontera is located at the Texas Advanced Computing Center and supported by National Science Foundation.

"Once Blue Waters started being phased out, Frontera was the natural choice, given that it was the new NSF-funded flagship machine," Srinivasan said. "One question you have is whether you have generated a sufficient number of scenarios to cover the range of possibilities. We check this by generating histograms of quantities of interest and seeing if the histogram converges. Using Frontera, we were able to perform sufficiently large simulations that we now know what a precise answer looks like."

In practice, it isn't feasible to make precise predictions due to inherent uncertainties, especially at the early stages of an epidemic -- this is what makes the computational aspect of this research challenging.

"We needed to generate a large number of possible scenarios to cover the range of possibilities. This makes it computationally intensive," Srinivasan said.

The team validated their results by examining disembarkation times on three different types of airplanes. Since a single simulation doesn't capture the variety of human movement patterns, they performed simulations with 1,000 different combinations of values and compared it to the empirical data.

Using Frontera's GPU subsystem, the researchers were able to get the computation time down to 1.5 minutes. "Using the GPUs turned out to be a fortunate choice because we were able to deploy these simulations in the COVID-19 emergency. The GPUs on Frontera are a means of generating answers fast."

But Wait -- Models Don't Capture Extreme Events? In terms of general preparation, Srinivasan wants people to understand that scientific models often don't capture extreme events accurately.

Though there have been thorough empirical studies on several flights to understand human behavior and cleanliness of the surfaces and air, a major infection outbreak is an extreme event -- data from typical situations may not capture it.

There are about 100,000 flights on an average day. A very low probability event could lead to frequent infection outbreaks just because the number of flights is so large. Although models have predicted infection transmission in planes as unlikely, there have been several known outbreaks.

Srinivasan offers an example.

"It's generally believed that infection spread in planes happens two rows in front and back of the index patient," he said. "During the SARS outbreak in 2002, on the few flights with infection spread, this was mostly true. However, a single outbreak accounted for more than half the cases, and half of the infected were seated farther than two rows away on that flight. One might be tempted to look at this outbreak as an outlier. But the 'outlier' had the most impact, and so people farther than two rows away accounted for a significant number of people infected with SARS on flights."

Currently, with regard to COVID-19, the typical infected person is believed to sicken 2.5 others. However, there have been communities were a single 'super-spreader' infected a large number of people and played the driving role in an outbreak. The impact of such extreme events, and the difficulty in modeling them accurately, makes prediction difficult, according to Srinivasan.

"In our approach, we don't aim to accurately predict the actual number of cases," Srinivasan said. "Rather, we try to identify vulnerabilities in different policy or procedural options, such as different boarding procedures on a plane. We generate a large number of possible scenarios that could occur and examine whether one option is consistently better than the other. If it is, then it can be considered more robust. In a decision-making setting, one may wish to choose the more robust option, rather than rely on expected values from predictions."

Some Practical Advice

Srinivasan has some practical advice for readers as well.

"You may be still be at risk [for a virus] even if you are farther away than six feet," he said. "In discussion with modelers who advocate it, it appears that those models don't take air flow into account. Just as a ball goes farther if you throw it with the wind, the droplets carrying the viruses will go farther in the direction of the air flow."

These are not just theoretical considerations. In Singapore, they observed that an exhaust air vent of a toilet used by a patient tested positive for the new Coronavirus and attributed it to air flow.

"Models don't account for all factors impacting reality. When the stakes are high, one may wish to err on the side of caution," Srinivasan concludes.

University of Texas at Austin, Texas Advanced Computing Center

Related Outbreak Articles:

Pregnant women's psychological health during the COVID-19 outbreak
A recent study that examined the psychological health of pregnant women during the COVID-19 outbreak uncovered fear and depression in many participants.
Operation Outbreak simulation teaches students how pandemics spread
In 2015, a team of specialists in modeling disease outbreaks got together with educators to create Operation Outbreak, an educational platform and simulation intended to teach high school and college students the fundamentals of responses to pandemics.
Is the coronavirus outbreak of unnatural origins?
Did coronavirus mutate from a virus already prevalent in humans or animals or did it originate in a laboratory?
'Stealth transmission' fuels fast spread of coronavirus outbreak
Undetected cases, many of which were likely not severely symptomatic, were largely responsible for the rapid spread of the COVID-19 outbreak in China, according to new research by scientists at Columbia University Mailman School of Public Health.
'Quit vaping searches increased during lung-disease outbreak
Researchers found that searches on such terms as ''quit vaping'' increased as much as 3.7-fold during the vaping-related illness outbreak.
Researchers trace Coronavirus outbreak in China to snakes
Emerging viral infections -- from bird flu to Ebola to Zika infections -- pose major threats to global public health, and understanding their origins can help investigators design defensive strategies against future outbreaks.
Outbreak science: Infectious disease research leads to outbreak predictions
Infectious diseases have a substantially growing impact on the health of communities around the world and pressure to both predict and prevent such diseases is ever-growing.
Researchers carry out simulation of a hospital outbreak
Researchers carried out a simulation of a hospital outbreak investigation using advanced genomic analysis technologies.
Yale researchers detect unreported Zika outbreak
Researchers at the Yale School of Public Health (YSPH) have detected a large unreported Zika outbreak that occurred in Cuba during 2017, a year after Zika outbreaks peaked throughout the Americas.
2017 pneumonic plague outbreak in Madagascar characterized by scientists
Plague is an endemic disease in Madagascar. Each year there is a seasonal upsurge between September and April, especially in the Central Highlands, which stand at an elevation of more than 800m.
More Outbreak News and Outbreak Current Events

Trending Science News

Current Coronavirus (COVID-19) News

Top Science Podcasts

We have hand picked the top science podcasts of 2020.
Now Playing: TED Radio Hour

Debbie Millman: Designing Our Lives
From prehistoric cave art to today's social media feeds, to design is to be human. This hour, designer Debbie Millman guides us through a world made and remade–and helps us design our own paths.
Now Playing: Science for the People

#574 State of the Heart
This week we focus on heart disease, heart failure, what blood pressure is and why it's bad when it's high. Host Rachelle Saunders talks with physician, clinical researcher, and writer Haider Warraich about his book "State of the Heart: Exploring the History, Science, and Future of Cardiac Disease" and the ails of our hearts.
Now Playing: Radiolab

Insomnia Line
Coronasomnia is a not-so-surprising side-effect of the global pandemic. More and more of us are having trouble falling asleep. We wanted to find a way to get inside that nighttime world, to see why people are awake and what they are thinking about. So what'd Radiolab decide to do?  Open up the phone lines and talk to you. We created an insomnia hotline and on this week's experimental episode, we stayed up all night, taking hundreds of calls, spilling secrets, and at long last, watching the sunrise peek through.   This episode was produced by Lulu Miller with Rachael Cusick, Tracie Hunte, Tobin Low, Sarah Qari, Molly Webster, Pat Walters, Shima Oliaee, and Jonny Moens. Want more Radiolab in your life? Sign up for our newsletter! We share our latest favorites: articles, tv shows, funny Youtube videos, chocolate chip cookie recipes, and more. Support Radiolab by becoming a member today at