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I've been doing some pandemic reading and can't find why there is a distinction between transmission by aerosols and by droplets. Some articles give a size cutoff of 5 microns; how is that important?
Aerosols were also mentioned to be either wet (small droplets) or dry (dry remains from an evaporated droplet). Does that mean droplets can evaporate enough to count as an aerosol?
An Aerosol is a suspension of droplets or particles in air. A "suspension" means that the droplets or particles are suspended in the air and do not just fall down with gravity. Very tiny droplets can be suspended in this way by the Brownian motion of the air molecules: The air molecules move around randomly (their speed indicates the air's temperature) and hit these tiny droplets back and forth and prevent them from falling down as they would normally do because of gravity. But larger droplets are too big, the air's Brownian motion is not powerful enough to keep them suspended against gravity, so larger do fall down and do not create an aerosol.
So, if the coughed-up droplets are big, they will quickly fall down - and as a result the disease will be hard to transmit (the healthy person needs to stand close enough to the infected person to inhale the droplets before they fall down). However, if the droplets are smaller than some size, they form - as I described above - an aerosol. Such an aerosol can be suspended in the air for a long time, which can mean that a person who walks into a room where a person previously sneezed will get infected. It can also mean that the aerosol can float around the room, and infect a person standing pretty far away from the source.
Aerosol transmission of infectious disease
Objective: The concept of aerosol transmission is developed to resolve limitations in conventional definitions of airborne and droplet transmission.
Methods: The method was literature review.
Results: An infectious aerosol is a collection of pathogen-laden particles in air. Aerosol particles may deposit onto or be inhaled by a susceptible person. Aerosol transmission is biologically plausible when infectious aerosols are generated by or from an infectious person, the pathogen remains viable in the environment for some period of time, and the target tissues in which the pathogen initiates infection are accessible to the aerosol. Biological plausibility of aerosol transmission is evaluated for Severe Acute Respiratory Syndrome coronavirus and norovirus and discussed for Mycobacterium tuberculosis, influenza, and Ebola virus.
Conclusions: Aerosol transmission reflects a modern understanding of aerosol science and allows physically appropriate explanation and intervention selection for infectious diseases.
The 60-Year-Old Scientific Screwup That Helped Covid Kill
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Early one morning, Linsey Marr tiptoed to her dining room table, slipped on a headset, and fired up Zoom. On her computer screen, dozens of familiar faces began to appear. She also saw a few people she didn’t know, including Maria Van Kerkhove, the World Health Organization’s technical lead for Covid-19, and other expert advisers to the WHO. It was just past 1 pm Geneva time on April 3, 2020, but in Blacksburg, Virginia, where Marr lives with her husband and two children, dawn was just beginning to break.
Marr is an aerosol scientist at Virginia Tech and one of the few in the world who also studies infectious diseases. To her, the new coronavirus looked as if it could hang in the air, infecting anyone who breathed in enough of it. For people indoors, that posed a considerable risk. But the WHO didn’t seem to have caught on. Just days before, the organization had tweeted “FACT: #COVID19 is NOT airborne.” That’s why Marr was skipping her usual morning workout to join 35 other aerosol scientists. They were trying to warn the WHO it was making a big mistake.
Over Zoom, they laid out the case. They ticked through a growing list of superspreading events in restaurants, call centers, cruise ships, and a choir rehearsal, instances where people got sick even when they were across the room from a contagious person. The incidents contradicted the WHO’s main safety guidelines of keeping 3 to 6 feet of distance between people and frequent handwashing. If SARS-CoV-2 traveled only in large droplets that immediately fell to the ground, as the WHO was saying, then wouldn’t the distancing and the handwashing have prevented such outbreaks? Infectious air was the more likely culprit, they argued. But the WHO’s experts appeared to be unmoved. If they were going to call Covid-19 airborne, they wanted more direct evidence—proof, which could take months to gather, that the virus was abundant in the air. Meanwhile, thousands of people were falling ill every day.
On the video call, tensions rose. At one point, Lidia Morawska, a revered atmospheric physicist who had arranged the meeting, tried to explain how far infectious particles of different sizes could potentially travel. One of the WHO experts abruptly cut her off, telling her she was wrong, Marr recalls. His rudeness shocked her. “You just don’t argue with Lidia about physics,” she says.
Morawska had spent more than two decades advising a different branch of the WHO on the impacts of air pollution. When it came to flecks of soot and ash belched out by smokestacks and tailpipes, the organization readily accepted the physics she was describing—that particles of many sizes can hang aloft, travel far, and be inhaled. Now, though, the WHO’s advisers seemed to be saying those same laws didn’t apply to virus-laced respiratory particles. To them, the word airborne only applied to particles smaller than 5 microns. Trapped in their group-specific jargon, the two camps on Zoom literally couldn’t understand one another.
When the call ended, Marr sat back heavily, feeling an old frustration coiling tighter in her body. She itched to go for a run, to pound it out footfall by footfall into the pavement. “It felt like they had already made up their minds and they were just entertaining us,” she recalls. Marr was no stranger to being ignored by members of the medical establishment. Often seen as an epistemic trespasser, she was used to persevering through skepticism and outright rejection. This time, however, so much more than her ego was at stake. The beginning of a global pandemic was a terrible time to get into a fight over words. But she had an inkling that the verbal sparring was a symptom of a bigger problem—that outdated science was underpinning public health policy. She had to get through to them. But first, she had to crack the mystery of why their communication was failing so badly.
Marr spent the first many years of her career studying air pollution, just as Morawska had. But her priorities began to change in the late 2000s, when Marr sent her oldest child off to day care. That winter, she noticed how waves of runny noses, chest colds, and flu swept through the classrooms, despite the staff’s rigorous disinfection routines. “Could these common infections actually be in the air?” she wondered. Marr picked up a few introductory medical textbooks to satisfy her curiosity.
According to the medical canon, nearly all respiratory infections transmit through coughs or sneezes: Whenever a sick person hacks, bacteria and viruses spray out like bullets from a gun, quickly falling and sticking to any surface within a blast radius of 3 to 6 feet. If these droplets alight on a nose or mouth (or on a hand that then touches the face), they can cause an infection. Only a few diseases were thought to break this droplet rule. Measles and tuberculosis transmit a different way they’re described as “airborne.” Those pathogens travel inside aerosols, microscopic particles that can stay suspended for hours and travel longer distances. They can spread when contagious people simply breathe.
The distinction between droplet and airborne transmission has enormous consequences. To combat droplets, a leading precaution is to wash hands frequently with soap and water. To fight infectious aerosols, the air itself is the enemy. In hospitals, that means expensive isolation wards and N95 masks for all medical staff.
The books Marr flipped through drew the line between droplets and aerosols at 5 microns. A micron is a unit of measurement equal to one-millionth of a meter. By this definition, any infectious particle smaller than 5 microns in diameter is an aerosol anything bigger is a droplet. The more she looked, the more she found that number. The WHO and the US Centers for Disease Control and Prevention also listed 5 microns as the fulcrum on which the droplet-aerosol dichotomy toggled.
There was just one literally tiny problem: “The physics of it is all wrong,” Marr says. That much seemed obvious to her from everything she knew about how things move through air. Reality is far messier, with particles much larger than 5 microns staying afloat and behaving like aerosols, depending on heat, humidity, and airspeed. “I’d see the wrong number over and over again, and I just found that disturbing,” she says. The error meant that the medical community had a distorted picture of how people might get sick.
Linsey Marr stands in front of a smog chamber in her laboratory at Virginia Tech. For years, she says, the medical establishment treated her as an outsider.
Epidemiologists have long observed that most respiratory bugs require close contact to spread. Yet in that small space, a lot can happen. A sick person might cough droplets onto your face, emit small aerosols that you inhale, or shake your hand, which you then use to rub your nose. Any one of those mechanisms might transmit the virus. “Technically, it’s very hard to separate them and see which one is causing the infection,” Marr says. For long-distance infections, only the smallest particles could be to blame. Up close, though, particles of all sizes were in play. Yet, for decades, droplets were seen as the main culprit.
Marr decided to collect some data of her own. Installing air samplers in places such as day cares and airplanes, she frequently found the flu virus where the textbooks said it shouldn’t be—hiding in the air, most often in particles small enough to stay aloft for hours. And there was enough of it to make people sick.
In 2011, this should have been major news. Instead, the major medical journals rejected her manuscript. Even as she ran new experiments that added evidence to the idea that influenza was infecting people via aerosols, only one niche publisher, The Journal of the Royal Society Interface, was consistently receptive to her work. In the siloed world of academia, aerosols had always been the domain of engineers and physicists, and pathogens purely a medical concern Marr was one of the rare people who tried to straddle the divide. “I was definitely fringe,” she says.
Thinking it might help her overcome this resistance, she’d try from time to time to figure out where the flawed 5-micron figure had come from. But she always got stuck. The medical textbooks simply stated it as fact, without a citation, as if it were pulled from the air itself. Eventually she got tired of trying, her research and life moved on, and the 5-micron mystery faded into the background. Until, that is, December 2019, when a paper crossed her desk from the lab of Yuguo Li.
An indoor-air researcher at the University of Hong Kong, Li had made a name for himself during the first SARS outbreak, in 2003. His investigation of an outbreak at the Amoy Gardens apartment complex provided the strongest evidence that a coronavirus could be airborne. But in the intervening decades, he’d also struggled to convince the public health community that their risk calculus was off. Eventually, he decided to work out the math. Li’s elegant simulations showed that when a person coughed or sneezed, the heavy droplets were too few and the targets—an open mouth, nostrils, eyes—too small to account for much infection. Li’s team had concluded, therefore, that the public health establishment had it backward and that most colds, flu, and other respiratory illnesses must spread through aerosols instead.
Their findings, they argued, exposed the fallacy of the 5-micron boundary. And they’d gone a step further, tracing the number back to a decades-old document the CDC had published for hospitals. Marr couldn’t help but feel a surge of excitement. A journal had asked her to review Li’s paper, and she didn’t mask her feelings as she sketched out her reply. On January 22, 2020, she wrote, “This work is hugely important in challenging the existing dogma about how infectious disease is transmitted in droplets and aerosols.”
Even as she composed her note, the implications of Li’s work were far from theoretical. Hours later, Chinese government officials cut off any travel in and out of the city of Wuhan, in a desperate attempt to contain an as-yet-unnamed respiratory disease burning through the 11-million-person megalopolis. As the pandemic shut down country after country, the WHO and the CDC told people to wash their hands, scrub surfaces, and maintain social distance. They didn’t say anything about masks or the dangers of being indoors.
A few days after the April Zoom meeting with the WHO, Marr got an email from another aerosol scientist who had been on the call, an atmospheric chemist at the University of Colorado Boulder named Jose-Luis Jimenez. He’d become fixated on the WHO recommendation that people stay 3 to 6 feet apart from one another. As far as he could tell, that social distancing guideline seemed to be based on a few studies from the 1930s and ’40s. But the authors of those experiments actually argued for the possibility of airborne transmission, which by definition would involve distances over 6 feet. None of it seemed to add up.
Scientists use a rotating drum to aerosolize viruses and study how well they survive under different conditions.
Marr told him about her concerns with the 5-micron boundary and suggested that their two issues might be linked. If the 6-foot guideline was built off of an incorrect definition of droplets, the 5-micron error wasn’t just some arcane detail. It seemed to sit at the heart of the WHO’s and the CDC’s flawed guidance. Finding its origin suddenly became a priority. But to hunt it down, Marr, Jimenez, and their collaborators needed help. They needed a historian.
Luckily, Marr knew one, a Virginia Tech scholar named Tom Ewing who specialized in the history of tuberculosis and influenza. They talked. He suggested they bring on board a graduate student he happened to know who was good at this particular form of forensics. The team agreed. “This will be very interesting,” Marr wrote in an email to Jimenez on April 13. “I think we’re going to find a house of cards.”
The graduate student in question was Katie Randall. Covid had just dealt her dissertation a big blow—she could no longer conduct in-person research, so she’d promised her adviser she would devote the spring to sorting out her dissertation and nothing else. But then an email from Ewing arrived in her inbox describing Marr’s quest and the clues her team had so far unearthed, which were “layered like an archaeology site, with shards that might make up a pot,” he wrote. That did it. She was in.
Randall had studied citation tracking, a type of scholastic detective work where the clues aren’t blood sprays and stray fibers but buried references to long-ago studies, reports, and other records. She started digging where Li and the others had left off—with various WHO and CDC papers. But she didn’t find any more clues than they had. Dead end.
She tried another tack. Everyone agreed that tuberculosis was airborne. So she plugged “5 microns” and “tuberculosis” into a search of the CDC’s archives. She scrolled and scrolled until she reached the earliest document on tuberculosis prevention that mentioned aerosol size. It cited an out-of-print book written by a Harvard engineer named William Firth Wells. Published in 1955, it was called Airborne Contagion and Air Hygiene. A lead!
In the Before Times, she would have acquired the book through interlibrary loan. With the pandemic shutting down universities, that was no longer an option. On the wilds of the open internet, Randall tracked down a first edition from a rare book seller for $500—a hefty expense for a side project with essentially no funding. But then one of the university’s librarians came through and located a digital copy in Michigan. Randall began to dig in.
In the words of Wells’ manuscript, she found a man at the end of his career, rushing to contextualize more than 23 years of research. She started reading his early work, including one of the studies Jimenez had mentioned. In 1934, Wells and his wife, Mildred Weeks Wells, a physician, analyzed air samples and plotted a curve showing how the opposing forces of gravity and evaporation acted on respiratory particles. The couple’s calculations made it possible to predict the time it would take a particle of a given size to travel from someone’s mouth to the ground. According to them, particles bigger than 100 microns sank within seconds. Smaller particles stayed in the air. Randall paused at the curve they’d drawn. To her, it seemed to foreshadow the idea of a droplet-aerosol dichotomy, but one that should have pivoted around 100 microns, not 5.
The book was long, more than 400 pages, and Randall was still on the hook for her dissertation. She was also helping her restless 6-year-old daughter navigate remote kindergarten, now that Covid had closed her school. So it was often not until late at night, after everyone had gone to bed, that she could return to it, taking detailed notes about each day’s progress.
One night she read about experiments Wells did in the 1940s in which he installed air-disinfecting ultraviolet lights inside schools. In the classrooms with UV lamps installed, fewer kids came down with the measles. He concluded that the measles virus must have been in the air. Randall was struck by this. She knew that measles didn’t get recognized as an airborne disease until decades later. What had happened?
Part of medical rhetoric is understanding why certain ideas take hold and others don’t. So as spring turned to summer, Randall started to investigate how Wells’ contemporaries perceived him. That’s how she found the writings of Alexander Langmuir, the influential chief epidemiologist of the newly established CDC. Like his peers, Langmuir had been brought up in the Gospel of Personal Cleanliness, an obsession that made handwashing the bedrock of US public health policy. He seemed to view Wells’ ideas about airborne transmission as retrograde, seeing in them a slide back toward an ancient, irrational terror of bad air—the “miasma theory” that had prevailed for centuries. Langmuir dismissed them as little more than “interesting theoretical points.”
But at the same time, Langmuir was growing increasingly preoccupied by the threat of biological warfare. He worried about enemies carpeting US cities in airborne pathogens. In March 1951, just months after the start of the Korean War, Langmuir published a report in which he simultaneously disparaged Wells’ belief in airborne infection and credited his work as being foundational to understanding the physics of airborne infection.
How curious, Randall thought. She kept reading.
In the report, Langmuir cited a few studies from the 1940s looking at the health hazards of working in mines and factories, which showed the mucus of the nose and throat to be exceptionally good at filtering out particles bigger than 5 microns. The smaller ones, however, could slip deep into the lungs and cause irreversible damage. If someone wanted to turn a rare and nasty pathogen into a potent agent of mass infection, Langmuir wrote, the thing to do would be to formulate it into a liquid that could be aerosolized into particles smaller than 5 microns, small enough to bypass the body’s main defenses. Curious indeed. Randall made a note.
When she returned to Wells’ book a few days later, she noticed he too had written about those industrial hygiene studies. They had inspired Wells to investigate what role particle size played in the likelihood of natural respiratory infections. He designed a study using tuberculosis-causing bacteria. The bug was hardy and could be aerosolized, and if it landed in the lungs, it grew into a small lesion. He exposed rabbits to similar doses of the bacteria, pumped into their chambers either as a fine (smaller than 5 microns) or coarse (bigger than 5 microns) mist. The animals that got the fine treatment fell ill, and upon autopsy it was clear their lungs bulged with lesions. The bunnies that received the coarse blast appeared no worse for the wear.
For days, Randall worked like this—going back and forth between Wells and Langmuir, moving forward and backward in time. As she got into Langmuir’s later writings, she observed a shift in his tone. In articles he wrote up until the 1980s, toward the end of his career, he admitted he had been wrong about airborne infection. It was possible.
A big part of what changed Langmuir’s mind was one of Wells’ final studies. Working at a VA hospital in Baltimore, Wells and his collaborators had pumped exhaust air from a tuberculosis ward into the cages of about 150 guinea pigs on the building’s top floor. Month after month, a few guinea pigs came down with tuberculosis. Still, public health authorities were skeptical. They complained that the experiment lacked controls. So Wells’ team added another 150 animals, but this time they included UV lights to kill any germs in the air. Those guinea pigs stayed healthy. That was it, the first incontrovertible evidence that a human disease—tuberculosis—could be airborne, and not even the public health big hats could ignore it.
The groundbreaking results were published in 1962. Wells died in September of the following year. A month later, Langmuir mentioned the late engineer in a speech to public health workers. It was Wells, he said, that they had to thank for illuminating their inadequate response to a growing epidemic of tuberculosis. He emphasized that the problematic particles—the ones they had to worry about—were smaller than 5 microns.
Inside Randall’s head, something snapped into place. She shot forward in time, to that first tuberculosis guidance document where she had started her investigation. She had learned from it that tuberculosis is a curious critter it can only invade a subset of human cells in the deepest reaches of the lungs. Most bugs are more promiscuous. They can embed in particles of any size and infect cells all along the respiratory tract.
What must have happened, she thought, was that after Wells died, scientists inside the CDC conflated his observations. They plucked the size of the particle that transmits tuberculosis out of context, making 5 microns stand in for a general definition of airborne spread. Wells’ 100-micron threshold got left behind. “You can see that the idea of what is respirable, what stays airborne, and what is infectious are all being flattened into this 5-micron phenomenon,” Randall says. Over time, through blind repetition, the error sank deeper into the medical canon. The CDC did not respond to multiple requests for comment.
In June, she Zoomed into a meeting with the rest of the team to share what she had found. Marr almost couldn’t believe someone had cracked it. “It was like, ‘Oh my gosh, this is where the 5 microns came from?!’” After all these years, she finally had an answer. But getting to the bottom of the 5-micron myth was only the first step. Dislodging it from decades of public health doctrine would mean convincing two of the world’s most powerful health authorities not only that they were wrong but that the error was incredibly—and urgently—consequential.
2. Predicting Airborne Infection Risk: From Source to Receptor
For effective ventilation design of a health care facility, one needs to be able to quantify and predict airborne infection risk. The informed selection of one ventilation design strategy over another requires the use of suitable metrics. To provide a useful prediction, many input parameters need to be supplied to an airborne infection risk model or experiment. The accuracy and extent of these parameters, of course, depend on the model or experiment complexity and the desired level of detail for the expected results. The key factors of the airborne infection process, which determine the organization of our discussion, are present in the Wells-Riley risk model for a well-mixed room 
where P I is the probability of infection, C is the number of infection cases, S is the number of susceptible persons, I is the number of infectors, q is the quanta generation rate, p is the pulmonary ventilation rate of a person (inhalation), t is the exposure time interval, and Q is the room ventilation rate with clean air. As implied by this equation, one needs to know I, q, p, t, and Q in order to quantify infection risk.
This model is useful but only for the simple case of a well-mixed room, where airborne pathogens are randomly distributed in space. More parameters and complications arise for scenarios in which the air is not well-mixed. In addition, empirical data need to exist for q that quantifies a minimum dose of pathogens that has been observed to infect a person. In Section 2.5, we will consider and compare more sophisticated risk models, but they all involve the same factors: aerosol generation, pathogen transport, infectivity loss, and inhalation and deposition.
2.1. Generation of Aerosols
2.1.1. Categories of Airborne Aerosols
Aerosols are suspensions of fine solid or liquid particles in a gas. The medical profession reserves the term airborne for aerosols that are transported by air currents over long time periods (minutes) and large distances (ϡ m). Thus, small aerosols contribute to the airborne infection mode, while larger aerosols (which settle out quickly) contribute to the droplet infection mode. These are some variations in how the terms are used in the literature [5, 6].
There is agreement that aerosols smaller than 5 μm in aerodynamic diameter (also called droplet nuclei ) contribute to airborne infection [1, 6]. However, Tellier  considers aerosols larger than 20 μm, while Tang et al.  consider aerosols larger than 60 μm as contributing to droplet infection. Some authors also define an intermediate size range where aerosols contribute to infection via both airborne and droplet modes. This intermediate behavior depends on particular geometrical settings, airflow patterns in ventilation, and also aerosol response to the surrounding environment [1, 10].
Particular care must be given to aerosols that change in size during the time of flight due to evaporation. An aerosol may move from the droplet regime towards the airborne regime due to mass loss. Aerosol composition and environmental factors such as temperature and relative humidity determine such changes and must carefully be considered in any study [1, 6, 7, 10, 11].
There are hundreds of airborne communicable pathogens [6, 10, 12] falling into three major categories: viruses, bacteria, and fungal spores. Viruses are the smallest with diameters of 0.02𠄰.3 μm. Bacteria have diameters in the range of 0.5 μm. Spores are the largest with diameters in the range of 0.5 μm .
Human activities are key sources for dispersal of airborne pathogens. These include respiratory activities (breathing, speaking, coughing, sneezing, etc.), showering, flushing, using tap water (atomization of infectious aerosols, particularly bacteria present in the water or in the local plumbing), sewage aerosolization from toilets and its transport in building down-pipe systems, and wet-cleaning of indoor surfaces . Other human activities such as bed making, walking on carpet, or skin shedding, cause resuspension of aerosols from surfaces .
In addition, various medical procedures also contribute to pathogen transmission. Some procedures that may increase droplet nuclei generation are intubation, cardiopulmonary resuscitation, bronchoscopy, autopsy, and surgery with high-speed devices. Presently, there is no precise list of such procedures, and neither has there been any study on the impact of ventilation design on the spread of pathogens released by high-risk procedures .
Aside from these sources, each building facility has its own microbial ecology that supports the growth of certain kinds of pathogens and suppresses the growth of others. For example, heating ventilation and air conditioning (HVAC) system components such as filters, cooling coils, air intakes, and porous insulation in air ducts can support the growth and dissemination of spores in certain areas. On the other hand, sufficient sunlight and natural ventilation in other areas may disinfect pathogens [11, 12].
2.1.2. Expiratory Aerosols
Expiratory droplets are particularly important in the spread of airborne infection. Human expirations (breathing, coughing, and sneezing) create the smallest aerosols compared to other sources. Particular attention is paid to human expiratory sources of aerosols for the remainder of this paper.
Coughs and sneezes were studied by Jennison  who applied high-speed photography to track the size and motion of droplets as subjects sneezed. Seventy years ago, it was not possible to track aerosols smaller than 100 μm. Nevertheless, Jennison determined the important length and time scales of sneezes.
Duguid  studied the sizes of droplets produced by sneezing, coughing, and speaking using microscopic measurement of stain marks found on slides exposed directly to air exhaled from the mouth. He was able to detect droplets sized in the range of 1 μm. Fairchild and Stamper  measured droplets in exhaled breath using an optical particle counter (OPC) in the range of 0.09𠄳.0 μm. Papineni and Rosenthal  studied the size distribution of droplets exhaled by healthy individuals while mouth breathing, nose breathing, talking, and coughing. They used an OPC and an analytical transmission electron microscope (ATEM). The OPC indicated that the majority of droplets were under 1 μm. ATEM measurements were conducted by collecting droplets on slides and viewing their size under microscope after evaporation. The original droplet size was corrected with a calculation. They confirmed the existence of larger droplets in exhaled breath as opposed to nose breathing. Yang et al.  studied the size distribution of droplets experimentally using the aerodynamic particle spectrometer (APS) and the scanning mobility particle spectrometer (SMPS). Their samples were bagged before analysis hence, significant evaporation and droplet settling may have occurred. An experimental study by Chao et al.  considered characteristics of a real cough just after the mouth opening using interferometric Mie imaging (IMI). They found that droplets are in the range of 2 μm (corresponding to the entire measurement range of IMI).
The large variation in reported droplet size can be attributed to three major causes: (i) the sensitivity of different measurement techniques, (ii) the unrepeatable nature of coughs and sneezes for each subject as well as the variability of coughs and sneezes among different subjects, and (iii) the evaporation of droplets at different time scales according to their initial size. Size distribution data found in the literature are summarized in Table 1 .
Experimental expiratory droplet size data.
|Study||Measurement technique||Expiration type||D min [μm]||D max [μm]||Geometric mean [μm]||Geometric standard deviation [μm]|
|Loudon and Roberts ||Microscopy||Coughing||1||12||8.4|
|Papineni and Rosenthal ||OPC 1||Talking||π.6||2.5||0.8||1.5|
|Papineni and Rosenthal ||OPC||Nose breathing||π.6||2.5||0.8||1.5|
|Papineni and Rosenthal ||OPC||Mouth breathing||π.6||2.5||0.7||1.4|
|Papineni and Rosenthal ||OPC||Coughing||π.6||2.5||0.7||1.5|
|Papineni and Rosenthal ||ATEM 2||Mouth breathing||π.6||2.5||1.2||1.6|
|Chao et al. ||IMI 3||Talking||2||2000||12.6||3.2|
|Chao et al. ||IMI||Coughing||2||2000||13.1||3.6|
1 OPC: optical particle counter, 2 ATEM: analytical transmission electron microscope, 3 IMI: interferometric Mie imaging.
The physiology of coughing is described by McCool  as a three-phase reflex: inspiration, compression, and expiration. The peak flow rate in a cough may reach as high as 12 L/s. Piirilä and Sovijarvi  performed an objective assessment of coughing. They investigated the cough as a primitive reflex typically consisting of an initiating deep inspiration, glottal closure, and an explosive expiration accompanied by a sound. The flow characteristics of a cough were reported to vary from person to person. They reported that the durations of the different phases of the cough reflex can be easily measured on a graph of flow versus time. They suggested that the duration of the glottal closure during the compressive phase of cough varies in the range of 0.09𠄱.01 s. They also defined a useful parameter in characterizing the cough, the cough peak expiratory flow rate (CPEF). Nishino  explains the physiology of coughing and sneezing in detail and points out the similarities and differences between the two. The flow dynamics of a sneeze are similar to the cough in time variation of flow rate. However, the peak velocities are higher, and in addition to mouth exhalation, a small fraction of the exhalation exits the nose. For sneezes, Jennison  reported exit velocities as high as 90 m/s with peak velocity time (PVT) of 57 ms. The total sneeze time was reported in the range of 0.07𠄰.20 s. Zhu et al.  performed particle image velocimetry (PIV) measurements and computational fluid dynamics (CFD) simulations of cough droplet dispersion in a calm background. Experimentally, they found that the initial velocity of coughs varies in the range of 6 m/s and the amount of saliva injected is in the range of 6.1𠄷.7 mg. Chao et al.  reported an average expiration air velocity of 11.7 m/s for coughing and 3.9 m/s for speaking.
Gupta et al.  performed an experimental study to characterize the flow rate versus time profile of a human exhalation. They have combined gamma-probability-distribution functions to fit experimental data. Such functions will be particularly useful for setting cough and sneeze boundary conditions for CFD studies. They characterize the complete distribution by only three parameters: cough peak flow rate (CPFR), peak velocity time (PVT), and cough expired volume (CEV). These boundary conditions were implemented in a CFD simulation by Aliabadi et al. . They demonstrated that volatile cough and sneeze aerosols evaporate at different time scales according to their size. In general, small droplets (㰠 μm) evaporate at much faster time scales (milliseconds) than larger droplets (㹐 μm) for which the evaporation time is in the order of seconds. The most important factors in evaporation rate are temperature and relative humidity in the ambient air.
Höppe  pioneered the measurement of expiration temperatures in different climatic conditions. He studied the nasal and oral exhalation temperatures as a function of environment temperature (5ଌ ଌ) and environment relative humidities (10%%). Noticeable variabilities in exhalation temperatures were observed. Similarly, McFadden et al.  provided thermal mapping of the human airways using measurements by inserting fine thermistor probes into the respiratory tract. They found that at normal-to-high rate breathing, the temperature in the upper airway system is in the range of 33.9ଌ .5ଌ.
2.2. Dispersion, Heat, and Mass Transfer
After aerosol generation, the next step in the infection pathway is the dispersion of airborne pathogens in ventilation space, possibly towards potential suspects. This dispersion is a function of many variables such as aerosol size, mean and fluctuating velocities of air, temperature, and the rate at which the aerosol is transferring mass or heat with the environment (i.e., evaporation or cooling/heating). These processes cannot be modeled analytically except in the most idealized cases. Rather, CFD is required to model both the continuous phase (the air) and the discrete phase (the aerosols).
2.2.1. Modeling Airflow
Solving the continuum phase (air) in ventilation flow requires the integration and solution of mass, momentum, and energy equations, normally using finite volume discretization methods .
The fluid flow regime is determined largely by the Reynolds number (dimensionless ratio of intertial to viscous forces, Re = VL/ν) and Grashof number (dimensionless ratio of the buoyancy to viscous forces, Gr = gβ(T s − T ∞)L 3 /ν 2 ). In these equations, V is velocity, L is length scale, ν is kinematic viscosity, g is gravitational acceleration, β is coefficient of thermal expansion, T s is surface temperature, and T ∞ is far-field temperature. Depending on the room geometry, transition from laminar to turbulent flow occurs at Re
O(10 3 ), and buoyancy-driven flows (e.g., thermal plumes) become important for Gr/Re 2 > O(10). The process of airborne infection in a room involves widely differing scales. For example, the flow in the vicinity of a sneeze is highly turbulent and not strongly influenced by gravity or buoyancy. In contrast, over longer times (minutes) and larger length scales (full room), the turbulence intensity is less and the influence of gravity or buoyancy may be larger. The heat and mass transfer to an expiratory droplet is determined by flow conditions in the immediate distance (1 μm) around the droplet, which is always laminar due to the small relevant length scales and the small aerosol-air relative velocity.
Typically, some form of turbulence modelling is needed for room-scale simulations, yet modeling turbulence accurately is the limiting factor for continuum phase modeling for two reasons: (i) the physics of turbulence is not well understood and (ii) accurate modeling of turbulence is computationally very expensive.
The most accurate way to model turbulence is direct numerical simulation (DNS). In this technique, the eddies (fluid structures) of all length scales (from small to large) are resolved. This technique, however, demands immense computational power with increasing Re or Gr numbers, and, hence, is not applied in ventilation simulations.
As a compromise, the large eddy simulation (LES) technique has been developed that resolves larger eddies but uses simple models of the smaller scales of the flow. The basic motivation behind this idea is that large eddies are the primary mechanisms transporting aerosols over large distances. This reduces the computation cost substantially, but it still poses challenges for modeling ventilation airflow: (i) the required computation cost is still high, (ii) many realizations of the airflow are necessary for statistically significant results, and (iii) original perturbation fields for the flow are not known or are difficult to generate .
A less computationally costly approach in modeling turbulence is Reynolds averaged Navier-Stokes (RANS) modeling. This approach does not resolve any real-time scales of the flow but instead considers time-averaged and fluctuating components of the flow separately. These models report time-averaged parameters of turbulence such as kinetic energy and dissipation rate. Many variations of RANS models are available (k − ϵ, k − ω, v 2 f, Reynolds stress model (RSM), etc.). Many researchers have used the standard or realizable k − ϵ turbulence model in solving ventilation airflow . Other researchers have predicted ventilation airflow using renormalization group (RNG) k − ϵ turbulence model. Compared to the standard and realizable k − ϵ models, the RNG model has a better ability to model both high and low Re or Gr numbers in the same flow [29, 32]. Most RANS models are computationally economic and provide useful results, particularly when qualitative results are sought. However, they do not consider the anisotropy of the turbulence and often have difficulty to reach a converged solution. One remedy is to use the Reynolds stress model (RSM) that allows for anisotropy of turbulence and provides better results than other RANS models if the initial solution is guessed properly.
An alternative approach is to combine RANS and LES to obtain a detached eddy simulation (DES) in which LES is used in areas of strong large-scale unsteadiness such as in the wake of a person, while RANS is used to model the flow elsewhere. In this technique, LES is used where the grid is sufficiently fine so that large eddies can be resolved accurately .
A summary of the advantages and disadvantages of the major turbulence models is provided in Table 2 . Due to its relative computational speed, RANS is the only approach used today in the engineering design of ventilation systems.
Summary of turbulence modeling approaches (with representative number of required computational cells and computational time to simulate one hour of ventilation flow in a hospital inpatient room).
|DNS 1||Resolves eddies of all lengths||Computationally very expensive||10 10||Years|
|LES 2||Resolves large eddies||Computationally expensive||10 8||Months|
|DES 3||Computationally economic||Difficult to implement||10 7||Weeks|
|RANS 4||Computationally economic||Less accurate, difficult to converge||10 6||Days|
1 DNS: direct numerical simulation, 2 LES: large eddy simulation, 3 DES: detached eddy simulation, 4 RANS: Reynolds averaged Navier-Stokes.
2.2.2. Modeling Aerosol Dispersion, Heat, and Mass Transfer
Particle dispersion can be modeled using several approaches. The simplest approach is to assume that aerosols behave like gases (true only for submicrometer aerosols) and to solve for gas concentration transport in the conservation equations. Many studies have used this approach [32, 33, 35, 36], but it cannot be used to predict the transfer of heat and mass with the continuum phase. Also, aerosols larger than 1 μm are affected by other dispersion forces including gravity, which are not accounted for in gas dispersion modeling.
Alternatively, the trajectory of an aerosol can be determined by the force balance that equates the aerosol inertia with the forces acting on it [25, 39]
where u ⃗ p is the aerosol velocity, u ⃗ is the continuum phase velocity, F D is drag acceleration per unit velocity (determined by Stokes law for the smallest aerosols or empirical drag coefficients for larger aerosols), g is gravitational acceleration, ρ p is aerosol density, ρ is continuum phase density, and F ⃗ is the acceleration per unit mass caused by the Brownian force.
Neglecting radiation, the mechanisms of aerosol mass, and temperature change are convection and evaporation. Having the time rate of change of aerosol mass and the convective heat transfer coefficient, the energy balance equation for an aerosol may be written as
where m p is aerosol mass, c p is aerosol specific heat capacity, T p is aerosol temperature, h is convective heat transfer coefficient, A p is aerosol surface area, T ∞ is the far-field continuum phase temperature, and h fg is the latent heat of vaporization.
To produce statistically significant results, a large ensemble of droplets of various sizes are tracked stochastically, and bin-based mean dispersion locations and diameters are reported for a distribution of aerosols . Many literature studies adopt this modeling approach [30, 34, 38].
2.3. Viability and Infectivity
The term viability refers to the survival of pathogens in a given set of environmental conditions. Pathogens are termed infective only if they are able to attack host cells and reproduce themselves . Thus, all infective pathogens are also viable, but the converse is not necessarily true [42, 43]. This paper does not focus on detailed and complex mechanisms of infection however, a cursory review is needed here, because the uncertainty in infectivity data can dominate risk estimates and strongly influence ventilation design.
During aerosolization, fluid shear stresses can inactivate some pathogens. Furthermore, following aerosolization, the viability of a pathogen changes as a function of various environmental conditions, including the relative humidity, temperature, oxygen and ozone concentration, open air factor (OAF), and electromagnetic radiation . On the other hand, the infectious disease process in a host depends on the pathogen concentration (infection dose) and virulence (disease promoting factors) that enable an agent to overcome the physical and immunologic defense mechanisms in the host .
It is important to note that innate and adaptive host immune responses (e.g., past exposures and/or vaccination) will modify the response to any exposure considerably. The following responses may be possible: (i) exposed but not infected, (ii) exposed and infected but not diseased (due to rapid immune clearance primed by past exposures and/or vaccination, (iii) exposed, infected, and diseased. In addition, infectivity of a virus depends on previous infection of a host with another disease. Hall et al.  studied viral shedding patterns of ambulatory children with influenza B. They found that the infection symptoms varied in type and time depending on previous infections/diseases that the children already had. These intrahost mechanisms/factors are not within the scope of this paper.
2.3.1. Viability and Infectivity Measurements
Numerous techniques have been used to measure the viability and infectivity of airborne pathogens. Four major classes of techniques are reviewed below.
Animal tests for airborne infection consider many physical and biological aspects of pathogen viability and infectivity. Some researchers have reported studies using guinea pigs, monkeys, and cattle [1, 42, 45]. Although many pathogenic species are common to humans and these animals, some difficulties exist in extrapolating the viability and infectivity measurements to humans using these tests. The respiratory tracts of humans and animals have different physiologies. As a result, the respiratory tract size-dependent filtration and deposition efficiencies vary greatly from one creature to another . In addition, the true infectivity of airborne pathogens is a function of both the source and the receptor. The defense mechanisms in humans and other creatures are different, resulting in different infectivities for a given pathogen.
A large class of methods are termed culture methods, since they are based on the principle of cell growth. These methods are among the most popular and classical techniques used to measure viability and infectivity of airborne pathogens. Using these methods, a sample of airborne pathogens is collected on a media (e.g., agar plates) and incubated over time in favorable conditions (temperature, relative humidity, and chemical composition) to investigate how the pathogens multiply. The colony-forming unit (CFU) will then be the measure of the pathogen's ability to reproduce [46, 47].
It is important to account for viability and physical losses of pathogenic aerosols separately . To achieve this, some researchers have added aerostable spores or radioactively marked cells of a known proportion to the pathogen of interest whose viability is going to be studied. The viability for these aerostable spores or radioactive marked cells does not change in a wide range of environmental conditions . Some difficulties exist with traditional culture methods. The capturing of very fine pathogen-containing aerosols on solid media (e.g., agar plates) or liquid media (e.g., all-glass impingers) may be difficult . In addition, viable and reproducible cells may be collected in agglomerates whose CFU will underestimate the actual count.
Another large class of methods are termed molecular methods. These methods do not depend on cell growth and can detect both reproducible and nonreproducible pathogens . The reverse transcriptase-polymerase chain reaction (RT-PCR) technique permits detection of a single-pathogen DNA or RNA by making a billion-fold copies of it [1, 7]. Although accurate in detecting the genomes (DNA or RNA), an important limitation of this technique is that RT-PCR cannot establish the infectivity of the viral aerosols detected . Some researchers have used direct microscopy to provide a total count of viable pathogens in a prepared solution. One such technique relies on color staining of pathogens in the solution by adding chemicals (e.g., acids) to which pathogens respond .
Yet another large class of methods are termed plaque assay methods. The main characteristic of these methods is that the activity of the species of interest is observed in an organism or organic sample. For infectivity tests, the ability of a pathogen to attack and damage a cell is measured. To form a plaque assay, aerosols are sampled (e.g., with all-glass impingers) and multifold dilutions of a pathogen stock are prepared. Then, standard volume aliquots are inoculated and incubated in the vicinity of susceptible cell samples on plates. A plaque forms around damaged cells, and it grows until limited by the gel structure of the plate. This visual plaque allows for titer calculation of the pathogen in plaque-forming units (PFUs) per unit space. Sometimes, living cells are dyed such that the color contrast between the plaque and living cells are pronounced . Plaque assay methods reveal information about the ability of the pathogen to attach and infect living cells under favorable conditions. However, it is very difficult to extrapolate true infectivity of a pathogen for the host due to the variability of host factors already listed. Table 3 provides a summary of viability and infectivity measurement techniques for airborne pathogens.
Summary of viability and infectivity measurement techniques for airborne pathogens.
|Animal tests||Common diseases between humans and animals and interaction with the host||Difficult to extrapolate test results to human infection|
|Culture methods||Reproducibility||Pathogen interaction with host|
|Molecular methods||Single-pathogen detection limit||Reproducibility and pathogen interaction with host|
|Plaque assay methods||Infectivity and interaction with live cells||Interaction with host|
The true viability and infectivity of airborne pathogens depend on complex physical and biological mechanisms that affect the survival of pathogens while suspended in air, their deposition onto susceptible sites in the host, and their ability to defeat the defense mechanisms of the host. None of the existing measurement techniques accurately accounts for all of these mechanisms. As a result, it must be understood that any measurement technique, at best, approximates true viability and infectivity focusing on only limited aspects of viability or infectivity. For example, if molecular methods are used, accurate counts of pathogens are possible, but the estimates for their reproducibility and true interaction with the host are compromised. On the other hand, if plaque assay methods are used, some degree of pathogen interaction with the host is accounted for, while an accurate count of pathogens is compromised. Hence, the validity for prediction of airborne infection risk in a given building ventilation setting is limited to the type of viability and infectivity measurement technique used.
2.3.2. Environmental Factors Affecting Infectivity and Viability
Many environmental stressors are responsible for the loss of viability and infectivity in aerosolized pathogens. Table 4 shows the stresses and the target cell components in order of significance .
Summary of most probable target molecules .
|Stress||Most probable target molecules|
|Relative humidity and temperature||Outer membrane lipids and proteins|
|Oxygen||Lipids and proteins|
|Ozone||Lipids and proteins|
|Open air factor (O3 + olefins)||Lipids, proteins and nucleic acids|
|γ-rays, X-rays, and UV radiation||Lipids, proteins and nucleic acids|
Upon aerosolization, bacteria and viruses desiccate when dispersed in liquid suspensions such as saliva and then surrounded by relatively dry air. Loss of water is the greatest environmental stressor to pathogens and results in a loss of viability. On the other hand, the high relative humidity level in the respiratory tract promotes aerosol growth and affects the deposition site and efficiency as well as some repair mechanisms in the viability of microbes upon inhalation.
The relative simplicity of viral structure explains why the results of aerosol inactivation studies are more consistent for viruses than for bacteria. Inactivation of viruses is affected by the following variables: (i) viruses with lipids in their outer membrane are more stable at low relative humidities (20%%) than at high relative humidities, (ii) viruses without lipids are more stable at high relative humidities (70%%) than at low relative humidities, (iii) the nucleic acid for viruses without lipid membrane may be isolated and not detected during desiccation, while it can be recovered by prehumidification at sampling, (iv) minimal survival for both lipid and nonlipid membrane viruses occurs at intermediate relative humidities (40%%) [55, 56]. Example viruses with lipid membranes include Langat, Semliki forest, Vesicular Stomatitis, Vaccinia, and influenza . Some nonlipid membrane viruses include respiratory Adenoviruses and Rhinoviruses .
Due to the greater complexity of their biochemistry, structure, and organization, it is difficult to generalize the effect of relative humidity on bacterial viability. Gram-negative bacteria (bacteria that do not retain crystal violet dye in the Gram-staining protocol) such as Serratia marcescens, Escherichia coli, Salmonella pullorum, Salmonella derby, Pseudomonas aeruginosa, and Proteus vulgaris have lower viability at intermediate (50%%) to high (70%%) relative humidity environments. Also, some Gram-positive bacteria (bacteria that are stained dark blue or violet by the Gram staining protocol) such as Staphylococcus albus, Streptococcus haemolyticus, Bacillus subtilis, and Streptococcus pneumoniae (type 1) are found to have lower viability at intermediate relative humidities. In contrast, Gram-negative Klebsiella pneumoniae demonstrates relative stability (higher viability) at intermediate relative humidities. Some studies have also shown that Gram-negative Pasteurella species survive better at high relative humidities .
Aside from whether the bacteria are Gram-positive or Gram-negative, whether the bacteria are dry-disseminated or wet-disseminated also affects viability. Cox  has defined the former as meaning that the organism is aerosolized from a dry dust or freeze-dried powder, and the latter means that the organism is aerosolized from a liquid suspension, for example, human mucus or saliva. Cox  has found that dry-disseminated bacteria absorb water from the environment, while the wet-disseminated bacteria lose water to the environment by evaporation. Such changes in water content (i.e., rehydration or desiccation) affect the viability behavior. For example, Cox  found that for wet dissemination of Pasteurella, viability reaches a minimum at 50%% relative humidity, while for dry dissemination it reaches a minimum at 75% relative humidity.
Fungi have been less studied under laboratory conditions and most experimental data have been obtained by monitoring fungal levels in indoor and outdoor environments. Fungi are expected to be present at higher levels in naturally ventilated buildings. Generally, higher relative humidities support the survival of fungi .
The vapor pressure, and therefore the relative humidity, is dependent on temperature. As a result, it is difficult to completely separate the effects of humidity from temperature. However, studies that do attempt to find the effect of temperature on aerosolized pathogen stability have generally shown a decrease in viability when temperature increases .
Temperature can affect the state of viral proteins (including enzymes) and the virus genome (RNA or DNA). DNA viruses are generally more stable than RNA. Usually, an increase in the temperature results in a decrease in virus viability. Maintaining temperatures above 60ଌ for 60 min is generally enough to inactivate most viruses. The presence of surrounding organic material (e.g., blood, saliva, mucus, etc.) can protect viruses against temperature stresses .
Viral culture experiments show that temperatures as low as 7ଌ -8ଌ are optimal for airborne influenza survival, with survival decreasing progressively at moderate temperatures of 20.5ଌଌ. This relationship holds true for a range of relative humidities (23%%). Other in vivo experiments with guinea pigs confirm that influenza transmits through air better in cold and dry conditions. Recent experiments have shown that higher temperatures of about 30ଌ actually block the aerosol transmission of influenza .
Studies generally show that at temperature above about 24ଌ, bacteria appear to universally lose viability. This reduced viability has been observed in members of Gram-positive, Gram-negative, and intracellular bacteria: Pseudomonas, Pasteurella, Salmonella, Serratia, Escherichia, Bacillus, Brodetella, Chlamydia, and Mycoplasma species .
Generally, higher temperatures support fungi survival. The indoor and outdoor concentration of Aspergillus and Penicillium species may vary considerably in both winter and summer, as well as in urban or suburban environments, with higher temperature and relative humidity with suburban areas being generally more favorable for higher airborne spore concentrations . Table 5 shows a summary of the effect of temperature and relative humidity on the survival of airborne pathogens.
Summary of the effect of temperature and relative humidity on airborne pathogen viability and infectivity.
|Pathogen type||Temperature||Relative humidity|
|Viruses||Decrease by higher temperature||Variable|
|Bacteria||Decrease by higher temperature||Variable|
|Fungi||Increase by higher temperature||Increase by higher relative humidity|
Comparing the survival of pathogens in the laboratory with those outdoors shows that under the same conditions of photoactivity, relative humidity, and temperature, outdoor air is often more toxic to pathogens than indoor air, especially in urban areas [43, 57]. Cox  attributes this inactivation to an open air factor (OAF). OAF inactivation is probably caused by a multitude of factors including pollutant concentration, relative humidity, pressure fluctuations, and air ions .
Although the exact nature of the (OAF) is not known, various experimental efforts have been undertaken to correlate OAF mechanisms with known mechanisms of pathogen inactivation. In a study, various concentrations of O3, NO, NO2, SO2, C3H8, C3H6, C2H4, and C2H2 have been introduced to inactivate pathogens. In separate experiments, various exposures of OAF have been introduced to inactivate organisms. It was found that OAF is most closely correlated with ozone (O3) and C3H6 .
Aerosol inactivation caused by electromagnetic radiation is observed to be wavelength dependent. Also, relative humidity, oxygen concentration, aerosol age, and the presence of other gases affect the electromagnetic radiation damage to viability. Shorter and more energetic wavelengths (X-rays and gamma rays) can break the DNA of pathogens. UV radiation acts as an energy source for the production of thymidine dimers. Longer and visible wavelengths are shown to affect cytochromes in the mitochondria of yeasts and bacteria. Another study also shows that survival of aerosolized bacteria around sewage treatment plants was higher at night compared to daytime .
2.3.3. Viability and Infectivity Models
Viability and infectivity are often difficult to separate, so it is common to model their product as a single parameter (equivalent to assuming that all viable organisms are infective). Inactivation of microbial aerosols is a function of many parameters: temperature, suspension fluid chemistry, relative humidity, oxygen, and time. However, integration of all of these factors in a model is a complicated task, because the exact inactivation mechanisms for many microbes are not well understood. In addition, many factors have synergistic effects (e.g., temperature and relative humidity), making it difficult to formulate a comprehensive model. Finally, the response to environmental stressors is unique to each organism (e.g., genetic predisposition). Thus, most developed models in the literature are empirical, only considering a few of these factors, usually time and another factor like temperature or relative humidity. The model parameters are fit experimentally for the viability decay of each microbial aerosol of interest.
During and after the aerosolization of a microbial solution, there is a period of stabilization. During this initial time period, many microbes experience shear stresses and disintegrate. Also, aerosols of interest that remain airborne experience rapid evaporation (during the first 10 s) with temperature, relative humidity, and concentration of certain solutes in the droplet varying rapidly to a level that may be toxic to the microbes. The initial stabilization period is fast relative to the airborne lifetime of aerosols. Also, the interplay of various environmental stressors are far too complicated to be understood and modeled with the current methodologies .
Exponential decay is often used to model viability although a gross simplification, it often performs as well as detailed models with 20 or more parameters . For any set of environmental conditions, the exponential decay model is given by
where V 0 is % viability at time zero, V t is viability at time t, and k is decay constant. Many studies have used the standard exponential decay model to fit curves to viability data or predict viability in some other modeling context [12, 54, 59]. Some researchers have extended the standard exponential model by expressing the decay parameter as a variable governed by water activity and critical water activity in the suspension solution. Posada et al.  fit other constants to obtain an exponential expression for the decay variable.
Although the exponential decay model (4) offers many advantages and it is easy to use, it has one major drawback. It predicts the viability to be near zero when the aerosol age is large. This is contrary to experimental data that show an initial fast decay followed by a slow decay causing viability to asymptotically approach a nonzero minimum value . As a result, particularly when using the exponential decay model for airborne infection risk prediction over long periods, extreme care must be taken not to underestimate the risk.
To overcome this difficulty with the exponential decay model, a series of higher-order kinetic models have been developed by Cox . As explained, each model considers only up to two parameters, one of which is time and the other the relative humidity, temperature, or oxygen. As described before, relative humidity has the greatest impact on microbial survival. To use kinetic models, one needs to have experimental data for a given set of relative humidities, temperature, or oxygen for a particular pathogen. One then fits the data with a few constants to obtain the model.
The other alternative to the exponential model (4) is the catastrophe model. In classical treatments, chemical reactions are assumed to proceed continuously, whereas close examination suggests this is only an approximation, because at the molecular level, individual reactions are not continuous events. The continuum approximation becomes more accurate as the number of molecules becomes large. Loss of viability in a small aerosol has a discontinuous nature, since only a small quantity of microbes are concerned. A microbe is either alive or dead, and the sudden change between these two states is termed catastrophe . The mathematical model of catastrophe theory involves describing the potential energy of the system in terms of control parameters. For some range of values for the control parameters, the potential energy curve has a stable equilibrium, which represents the viable state. If the control parameters are changed, there may result a catastrophic drop in potential energy, which leads to the inactivated or nonequilibrium state .
High-order kinetic and catastrophe models for pathogen inactivation are more biologically plausible than the exponential model, but seldom is there sufficient data to support the more sophisticated models. The advantages and disadvantages of the viability models described above are listed in Table 6 .
3. Size distribution, time taken, and distances transmitted by aerosols and droplets produced by infected people
The SARS-CoV-2 is often said to be transmitted through droplets generated when a symptomatic person coughs, sneezes, talks, or exhales ( Morawska and Cao, 2020 ). Some of these droplets are too heavy to remain in the air, and rather fall on nearby floors or surfaces. Fomites collect droplets contaminated with SARS-CoV-2, and touching of such surfaces by a susceptible host would get infected. However, some droplets, when ejected from an infected person, convert to aerosol particles (also known as bioaerosols) with relatively smaller aerodynamic diameters and, consequently, become airborne ( Morawska, 2006 ). Such virus-laden aerosol particles are capable of infecting people who inhale such particles, thereby spreading the disease. Further, there have been several transport phenomena where larger droplets become smaller through evaporation so that such smaller particles are called droplet nuclei. Such aerosol particles with the encapsulation of viruses could be termed as bioaerosols or droplet nuclei hence, the term rosol’, 𠆋ioaerosol’, and 𠆍roplet nuclei’ is used in this paper interchangeably. The scenarios in respect of the generation of droplets and aerosol, particularly in the indoor environment, have not been adequately understood, and thus, insights into the plausible mechanisms are worthy of being explored. Duguid (1945) , for the first time, has explored the characteristics of droplets and aerosol from human expiratory activities with chest infections, and such information is presented in Table 1 . Duguid (1945) has observed that 95% of particles were often smaller than 100 μm, and the majority were between 4 and 8 μm. The findings corroborated that breathing and exhalation originated from the nose have shed up to a few hundreds of droplets of which some were aerosols. In contrast, talking, coughing, and sneezing have produced more aerosols than droplets ( Table 1 ).
Detailed information of droplets and aerosols generated from human expiratory activities (Source: Duguid, 1945 ).
|Activity||Number of droplets and aerosols generated (1 μm)||Presence of aerosols (1𠄲 μm)||Region of origin|
|Normal breathing (for 5 min)||None – few||Some||Nose|
|Single strong nasal expiration||Few – few hundred||Some||Nose|
|Counting loudly - talking||Few dozen – few hundred||Mostly||Front of the mouth|
|A single cough (mouth open)||None – few hundred||Some||Faucial region|
|A single cough (mouth initially closed)||Few hundred – many thousand||Mostly||Front of the mouth|
|Single sneeze||Few hundred thousand – few million||Mostly||Front of the mouth|
|Few – few thousand||Some||Both from the nose and the faucial region|
On the contrary to what Duguid (1945) has presented, a study conducted by Papineni and Rosenthal (1997) with five healthy individuals has manifested that 80% of particles from human expiratory activities were aerosols with the diameter being smaller than 1 μm. The study also corroborated that the highest aerosol densities were generated during coughing and the lowest from nasal breathing, of which exhaled breath would be more responsible in transmitting the viruses (size of the order of 0.1 μm) when compared with transmitting the bacteria (> 1 μm). It has been found that vomiting by a SARS-CoV infected person in the corridor of a hotel in Hong Kong in 2003 has contracted the disease on several people nearby by aerosol transmission ( Morawska, 2006 ).
The physicochemical processes affecting the fate of airborne aerosols constitute evaporation, interaction with other types of particles, transport, and removal from the air by deposition on solid surfaces ( Morawska, 2006 ). Particles in the air are often subjected to Brownian motion, gravity, electrostatic forces, thermal gradients, electromagnetic radiation, turbulent diffusion, and inertial forces ( Baron and Willeke, 2001 ). Of these mechanisms, the diffusion is a key mechanism of transmitting viruses with particles in the lower sub-micrometer range, together with other aerosol particles ( Baron and Willeke, 2001 ). For droplets larger than 1 μm, gravity becomes significant than Brownian motion in deciding the fate of such particles ( Cox, 1995 ). Under the standard atmospheric conditions, droplets smaller than 100 μm often evaporate before reaching the ground, and the evaporated droplet residues linger in the air for prolonged periods ( Morawska, 2006 ). When the droplets contain infectious bioaerosols, such as viruses, bioaerosols will remain in the air, even after the liquid content evaporates ( Morawska, 2006 ). However, the time interval that a virus survives in the air varies from one type of bioaerosol to another type. Droplets in the range of 0.5.0 μm lingering in the air are more likely to be retained in the respiratory tract and produce the infection ( McCluskey et al., 1996 ). However, droplets seem to be not present in the air for longer periods instead, evaporation takes place, transforming droplets to bioaerosol residues, which could linger in the air for extended periods.
Hui and Chan (2010) have investigated that in different indoor environments, SARS-CoV could be transmitted through the airborne route. Another retrospective study has found that the airborne transmission in an aircraft from an infected person to passengers located seven rows of seats ahead, indicating that the SARS-CoV virus could travel for a distance more than 1 m horizontally ( Olsen et al., 2003 ). Another case has been reported on infecting more than 1,000 persons in an apartment complex in Hong Kong because of aerosols generated by the building's sewage system ( McKinney et al., 2006 ). These observations manifest that the aerosol-laden SARS-CoV virus transmission is a phenomenon, which would impart greater havoc than one thinks, and precautionary measures are, therefore, of paramount importance.
The SARS-CoV-2 virus has been found to remain viable in aerosols for 3 h, while it, in the form of droplets, is more stable on plastic and stainless steel, copper, cardboard, and glass with durations detected up to 72, 4, 24, and 84 h, respectively ( van Doremalen et al., 2020 ). In comparison, the SARS-CoV virus was also found to be airborne in the form of aerosols for 3 h, indicating that both SARS viruses behave more or less in the same manner in the air. Nevertheless, the SARS-CoV virus remains stable and viable in the form of droplets on plastic and stainless steel, copper, cardboard, and glass with durations (half-lives) lasting to 72, 8, 8, and 96 h, respectively ( van Doremalen et al., 2020 ). The half-lives of the SARS-CoV-2 and SARS-CoV are almost the same in aerosols, with median estimates of approximately 1.1𠄱.2 h, indicating that both viruses have similar stability characteristics in transmitting through the air ( van Doremalen et al., 2020 ). However, more profound epidemiological sustenance of SARS-CoV-2 virus may, therefore, be because of some other factors, including high viral loads in the upper respiratory tract and the capability of persons infected with COVID-19 to shed and transmit the virus while remaining asymptomatic ( Bai et al., 2020 Zou et al., 2020 ).
Based on a study carried out by Nicas et al. (2005) , it has been estimated that particles emitted from a cough of an infected person of a respiratory illness quickly decrease in diameter (with initial diameters of less than 20 μm) mainly because of the water loss by approximately half of the initial volume, amounting to 6 ×ꀐ 𢄨 mL. Exhaust ventilation, particle settling, die-off, and air disinfection methods are some prominent mechanisms by which the removal of viable airborne pathogens often takes place each removal mechanism follows a first-order reduction rate ( Nicas et al., 2005 ). Based on 3-h viability of SARS-CoV-2 in the air ( van Doremalen et al., 2020 ), prerequisites for the disease such as exposure, inhalation, and infection could occur minutes or a few hours later near and far from an aerosol source even in a stagnant environment ( Bourouiba, 2020 ).
The actual airborne times for droplets may be greater in an environment where there are significant cross-flows ( WHO, 2009 ). Such scenarios could be expected in quarantine and healthcare centers (e.g., with doors opening, bed and equipment movement, and people walking back and forth, constantly). Conversely, airborne durations for smaller droplet nuclei or aerosols may be profoundly shorter when they are subject to a significant downdraft (e.g., if they pass under a ceiling supply vent) ( WHO, 2009 ). When the flow of mucus or saliva ejects from an infected person, its trajectory is determined primarily by the size of droplets and airflow patterns that govern the paths of movement ( Tang et al., 2006 ). The Stokes' law describes the resultant trajectory of the droplets subjected to the forces of gravity downwards and air friction upwards, which governs the droplet movement in the air ( Wells, 1934 ). Coughs and sneezes usually constitute a turbulent cloud of buoyant gas with suspended droplets of various sizes. The larger droplets follow a ballistic trajectory irrespective of flow in the gas phase, whereas the aerosols are buoyant to a varying degree within the turbulent gas cloud ( Bourouiba et al., 2014 ).
In general, there exists an accepted notion of a 2-m safe exclusion zone to prevent possible droplet transmission from an infected person to a susceptible host however, there are no comprehensive studies to support such a phenomenon. Wells (1934) has supported the 2-m exclusion zone concept taking into account the evaporation-falling curve. Wells (1934) has postulated that large droplets (> 100 μm) will fall to the floor within a horizontal distance of 2 m from the source. Simple calculations, assumptions, and inadequate empirical data of Wells's study have been later speculated by Xie et al. (2007) . Xie et al. (2007) have corroborated that for respiratory exhalation flows, the larger droplets (diameter between 60 μm and 100 μm) were, depending on the exhalation air velocity and relative humidity of the air, carried away for more than 6 m of horizontal distance with the exhaled air having a velocity of 50 m/s at the point of expiration ( Fig. 2 a). Such scenarios simulate sneezing events. Conversely, larger droplets were found to carry for more than 2 m afar at a velocity of 10 m/s reordered at the point of exit, simulating coughing bouts ( Fig. 2 b). The same for exhaling events for which the velocity is at 1 m/s was found to carry large droplets only up to about 1 m horizontally ( Fig. 2 c). Other studies also have proven that when an infected person of a respiratory illness coughs or sneezes, a cloud of pathogen-bearing droplets of different sizes appears to come out and travels even up to 7𠄸 m from the point of source ( Bourouiba et al., 2014 Bourouiba, 2016 ).
Trajectories of droplets and aerosols from an infected patient (a) event of sneezing with droplets travelled for 6 mਊt a speed of 50 m/s within 0.12 s (b) event of coughing with droplets travelled for 2 mਊt a speed of 10 m/s within 0.2 s (c) event of exhaling with droplets travelled for 1 mਊt a speed of 1 m/s within 1 s.
Moreover, recent experiments conducted after COVID-19 contagion by Bourouiba (2020) and Loh et al. (2020) have been in agreement with the findings of Xie et al. (2007) . Xie et al. (2007) have reported that pathogen-bearing droplets of all sizes can travel for almost 7𠄸 m during sneezes and for more than 2 m (maximum of 4.5 m) during coughs. Surprisingly, there have been contradicting insights on the distance to be maintained between healthcare workers and COVID-19 infected patients [e.g., 1 m ( WHO, 2020e ) and 2 m ( CDC, 2020b )]. However, most of the studies on the COVID-19 virus mentioned above have been carried out in laboratories with expiration devices set on manikins hence, no convincing information can be deduced.
Difference between aerosol and droplet transmission for airborne diseases - Biology
Knowing the methods in which a disease is transmitted is important for implementing proper infection control measures and large scale prevention campaigns. Each disease has transmission characteristics based on the nature of the microorganism that causes it.
The types of transmission described below are not mutually exclusive. Some diseases, such as anthrax, can be transmitted in more than one way. Anthrax can be spread through direct contact to a cut on the skin, producing cutaneous anthrax. It can also be spread through airborne spores which are inhaled, producing a more serious type of infection. Gastrointestinal anthrax can occur when anthrax spores are ingested.
» What is transmission by direct contact?
Direct contact transmission requires physical contact between an infected person and a susceptible person, and the physical transfer of microorganisms. Direct contact includes touching an infected individual, kissing, sexual contact, contact with oral secretions, or contact with body lesions. This type of transmission requires close contact with an infected individual, and will usually occur between members of the same household or close friends and family.
Diseases spread exclusively by direct contact are unable to survive for significant periods of time away from a host. Sexually transmitted diseases are almost always spread through direct contact, as they are extremely sensitive to drying.
» What is transmission by indirect contact?
Indirect contact transmission refers to situations where a susceptible person is infected from contact with a contaminated surface. Some organisms (such as Norwalk Virus) are capable of surviving on surfaces for an extended period of time. To reduce transmission by indirect contact, frequent touch surfaces should be properly disinfected.
Frequent touch surfaces (fomites) include:
- Door knobs, door handles, handrails
- Tables, beds, chairs
- Washroom surfaces
- Cups, dishes, cutlery, trays
- Medical instruments
- Computer keyboards, mice, electronic devices with buttons
- Pens, pencils, phones, office supplies
- Children's toys
» What is transmission by droplet contact?
Some diseases can be transferred by infected droplets contacting surfaces of the eye, nose, or mouth. This is referred to as droplet contact transmission. Droplets containing microorganisms can be generated when an infected person coughs, sneezes, or talks. Droplets can also be generated during certain medical procedures, such as bronchoscopy. Droplets are too large to be airborne for long periods of time, and quickly settle out of air.
Droplet transmission can be reduced with the use of personal protective barriers, such as face masks and goggles. Measles and SARS are examples of diseases capable of droplet contact transmission.
» What is airborne transmission?
Airborne transmission refers to situations where droplet nuclei (residue from evaporated droplets) or dust particles containing microorganisms can remain suspended in air for long periods of time. These organisms must be capable of surviving for long periods of time outside the body and must be resistant to drying. Airborne transmission allows organisms to enter the upper and lower respiratory tracts. Fortunately, only a limited number of diseases are capable of airborne transmission.
Diseases capable of airborne transmission include:
» What is fecal-oral transmission?
Fecal-oral transmission is usually associated with organisms that infect the digestive system. Microorganisms enter the body through ingestion of contaminated food and water. Inside the digestive system (usually within the intestines) these microorganisms multiply and are shed from the body in feces. If proper hygienic and sanitation practices are not in place, the microorganisms in the feces may contaminate the water supply through inadequate sewage treatment and water filtration. Fish and shellfish that swim in contaminated water may be used as food sources. If the infected individual is a waiter, cook, or food handler, then inadequate handwashing may result in food being contaminated with microorganisms.
Fecal-oral transmission can be reduced by:
- Proper storage of food at proper temperatures
- Thorough cooking of food
- Frequent and thorough handwashing, especially after washroom use
- Adequate sewage treatment and water filtration/chlorination systems
- Disinfection of frequent touch surfaces to prevent indirect contact transmission
- Increased public awareness of proper hygiene and food handling
» What is vector-borne transmission?
Vectors are animals that are capable of transmitting diseases. Examples of vectors are flies, mites, fleas, ticks, rats, and dogs. The most common vector for disease is the mosquito. Mosquitoes transfer disease through the saliva which comes in contact with their hosts when they are withdrawing blood. Mosquitoes are vectors for malaria, West Nile virus, dengue fever, and yellow fever.
Vectors add an extra dimension to disease transmission. Since vectors are mobile, they increase the transmission range of a disease. Changes in vector behaviour will affect the transmission pattern of a disease. It is important to study the behaviour of the vector as well as the disease-causing microorganism in order to establish a proper method of disease prevention. In the case of malaria, insecticides were sprayed and breeding grounds for mosquitoes were eliminated in an attempt to control the spread of malaria.
Biting is not the only way vectors can transmit diseases. Diseases may be spread through the feces of a vector. Microorganisms could also be located on the outside surface of a vector (such as a fly) and spread through physical contact with food, a common touch surface, or a susceptible individual.
'Aerosol' vs. 'airborne' vs. 'droplets' amid COVID-19: What you need to know
Conflicting messages from public health authorities have fueled a great deal of confusion over COVID-19, particularly regarding its transmission.
The terms "aerosol," "airborne" and "droplet" have made the rounds in attempts to explain how the novel coronavirus may spread, but without sufficient explanations.
There's still debate over the exact role airborne transmission plays in spreading COVID-19, said William Schaffner, M.D., a professor of preventive medicine and infectious disease at Vanderbilt University Medical Center.
"The science supporting [airborne transmission] is not as strong as we would like," Schaffner said. However, there's mounting evidence it's possible, particularly in indoor spaces with poor ventilation. "We need more clear guidance . people out there are wanting it."
Here's what you need to know about what these terms mean, and how they relate to COVID-19:
Aerosol is a catch-all term for any solid or liquid particle so tiny and lightweight it can become suspended in air and float. Smoke and dust are examples. Some viruses can become aerosols, making airborne transmission possible.
The World Health Organization defines aerosol transmission, also known as airborne transmission, as "very small droplets . that are able to stay suspended in the air for longer periods of time."
Airborne is when a droplet containing a virus is small enough to float in the air, and airborne transmission occurs when that infectious particle is inhaled by someone else, according to the WHO.
The WHO said there's mounting evidence airborne transmission of COVID-19 may be possible indoors, especially poorly ventilated spaces, because of "reported outbreaks of COVID-19 in some closed settings, such as restaurants, nightclubs, places of worship or places of work, where people may be shouting, talking or singing."
Droplets are large mucus or saliva particles heavier than air that fall toward the ground as soon as they're expelled, and droplet transmission typically occurs when a droplet containing a virus comes in contact with another person's eyes, nose or mouth. An example might be a loud-talking person whose droplets make contact with your face.
According to the WHO, current evidence suggests that close-contact, person-to-person transmission is the primary way COVID-19 spreads, as droplets "are released from the mouth or nose when an infected person coughs, sneezes, speaks or sings, for example." People in close contact with an infected person can become infected "when those infectious droplets get into their mouth, nose or eyes."
How has our understanding of COVID-19 changed over time?
COVID-19 originally was thought to be spread only by droplet transmission -- 6-foot social distancing guidelines were based on research that showed droplet transmission occurred most easily at such short distances. Scientists still believe this is the primary way coronavirus spreads person to person.
But more evidence is mounting that the virus could become an aerosol, leading to airborne spread. Although many scientists now believe airborne transmission is possible, many agree the majority of infections happen when people are crowded close together, exchanging the heavier droplets.
The WHO updated its online COVID-19 guidance in July to include information on airborne transmission. The Centers for Disease Control and Prevention followed suit on Sept. 18 but retracted the information a few days later, stating it was posted in error. The CDC has yet to issue an update on airborne transmission.
For many scientists, the CDC's confusing, disjointed stance on airborne transmission has been discouraging. The scientific community decried the mixed messaging, emphasizing the need for clear, unified public information.
According to Schaffner, with clearer guidance from the CDC, businesses operating indoor spaces can better prepare by taking precautions, such as adding new ventilation systems and limiting crowds, to defend against possible transmission.
The classification of an infectious agent as airborne and therefore ‘aerosol-transmissible’ has significant implications for how healthcare workers (HCWs) need to manage patients infected with such agents and what sort of personal protective equipment (PPE) they will need to wear. Such PPE is usually more costly for airborne agents (i.e. aerosol-transmissible) than for those that are only transmitted by large droplets or direct contact because of two key properties of aerosols: a) their propensity to follow air flows, which requires a tight seal of the PPE around the airways, and b) for bioaerosols, their small size, which calls for an enhanced filtering capacity.
Several recent articles and/or guidance, based on clinical and epidemiological data, have highlighted the potential for aerosol transmission for Middle-East Respiratory Syndrome-associated coronavirus (MERS-CoV) [1, 2] and Ebola virus [3, 4]. Some responses to the latter have attempted to put these theoretical risks in a more practical light , and this nicely illustrates the quandary of how to classify such emerging or re-emerging pathogens into either the large droplet (short-range) versus airborne (short and possibly long-range) transmission categories. However, this delineation is not black and white, as there is also the potential for pathogens under both classifications to be potentially transmitted by aerosols between people at close range (i.e. within 1 m).
Strictly speaking, ‘aerosols’ refer to particles in suspension in a gas, such as small droplets in air. There have been numerous publications classifying droplets using particle sizes over the years [5,6,7,8,9,10]. For example it is generally accepted that: i) small particles of < 5–10 μm aerodynamic diameter that follow airflow streamlines are potentially capable of short and long range transmission particles of < 5 μm readily penetrates the airways all the way down to the alveolar space, and particles of < 10 μm readily penetrates below the glottis (7) ii) large droplets of diameters > 20 μm refer to those that follow a more ballistic trajectory (i.e. falling mostly under the influence of gravity), where the droplets are too large to follow inhalation airflow streamlines. For these particle sizes, for example, surgical masks would be effective, as they will act as a direct physical barrier to droplets of this size that are too large to be inhaled into the respiratory tract around the sides of the mask (which are not close-fitting) iii) ‘intermediate particles’ of diameters 10–20 μm, will share some properties of both small and large droplets, to some extent, but settle more quickly than particles < 10 μm and potentially carry a smaller infectious dose than large (> 20 μm) droplets.
‘Aerosols’ would also include ‘droplet nuclei’ which are small particles with an aerodynamic diameter of 10 μm or less, typically produced through the process of rapid desiccation of exhaled respiratory droplets [5, 6]. However, in some situations, such as where there are strong ambient air cross-flows, for example, larger droplets can behave like aerosols with the potential to transmit infection via this route (see next section below).
Several properties can be inferred from this, for example the penetration of the lower respiratory tract (LRT), as at greater than 10 μm diameter, penetration below the glottis rapidly diminishes, as does any potential for initiating an infection at that site. Similarly, any such potential for depositing and initiating an LRT infection is less likely above a droplet diameter of 20 μm, as such large particles will probably impact onto respiratory epithelial mucosal surfaces or be trapped by cilia before reaching the LRT .
The Infectious Diseases Society of America (IDSA) has proposed a scheme that is essentially equivalent , defining “respirable particles” as having a diameter of 10 μm or less and “inspirable particles” as having a diameter between 10 μm and 100 μm, nearly all of which are deposited in the upper airways. Some authors have proposed the term “fine aerosols”, consisting of particles of 5 μm or less, but this has been in part dictated by constraints from measurement instruments . Several authors lump together transmission by either large droplets or aerosol-sized particles as “airborne transmission” , or use “aerosol transmission” to describe pathogens that can cause disease via inspirable particles of any size .
However, we think that it is important to maintain a distinction between particles of < 10 μm and larger particles, because of their significant qualitative differences including suspension time, penetration of different regions of the airways and requirements for different PPE. In this commentary, we use the common convention of “airborne transmission” to mean transmission by aerosol-size particles of < 10 μm.
If the infected patients produce infectious droplets of varying sizes by breathing, coughing or sneezing, transmission between individuals by both short-range large droplets and airborne small droplet nuclei are both possible, depending on the distance from the patient source. Figure 1 illustrates these potential routes of short and long-range airborne transmission, as well as the downstream settling of such droplets onto surfaces (fomites). From such fomites, they may be touched and transported by hands to be self-inoculated into mucosal membranes e.g. in the eyes, nose and mouth) to cause infection, depending on the survival characteristics of individual pathogens on such surfaces, and the susceptibility (related to available, compatible cell receptors) of the different exposed tissues to infection by these pathogens.
An illustration of various possible transmission routes of respiratory infection between an infected and a susceptible individual. Both close range (i.e. conversational) airborne transmission and longer range (over several meters) transmission routes are illustrated here. The orange head colour represents a source and the white head colour a potential recipient (with the bottom right panel indicating that both heads are potential recipients via self-inoculation from contaminated surface fomite sources). Here ‘Expiration’ also includes normal breathing exhalation, as well as coughing and/or sneezing airflows. Airborne droplets can then settle on surfaces (fomites) from where they can be touched and carried on hands leading to further self-inoculation routes of transmission
For example, when the infectious dose (the number of infectious agents required to cause disease) of an organism is low, and where large numbers of pathogen-laden droplets are produced in crowded conditions with poor ventilation (in hospital waiting rooms, in lecture theatres, on public transport, etc.), explosive outbreaks can still occur, even with pathogens whose airborne transmission capacity is controversial, e.g. the spread of influenza in a grounded plane where multiple secondary cases were observed in the absence of any ventilation .
The more mechanistic approaches (i.e. arguing from the more fundamental physical and dynamic behavior of small versus larger particle and droplet sizes in the absence of any biological interactions) to classifying which pathogens are likely to transmit via the airborne route have been published in various ways over the years [12,13,14,15,16,17], but may have to be considered in combination with epidemiological and environmental data to make a convincing argument about the potential for the airborne transmissibility of any particular agent – and the number of possible potential exposure scenarios is virtually unlimited).
The importance of ambient airflows and the of aerosols
One should note that “aerosol” is essentially a relative and not an absolute term. A larger droplet can remain airborne for longer if ambient airflows can sustain this suspension for longer, e.g. in some strong cross-flow or natural ventilation environments, where ventilation-induced airflows can propagate suspended pathogens effectively enough to cause infection at a considerable distance away from the source.
One of the standard rules (Stoke’s Law) applied in engineering calculations to estimate the suspension times of droplets falling under gravity with air resistance, was derived assuming several conditions including that the ambient air is still [13,14,15,16,17]. So actual suspension times will be far higher where there are significant cross-flows, which is often the case in healthcare environments, e.g. with doors opening, bed and equipment movement, and people walking back and forth, constantly. Conversely, suspension times, even for smaller droplet nuclei, can be greatly reduced if they encounter a significant downdraft (e.g. if they pass under a ceiling supply vent). In addition, the degree of airway penetration, for different particle sizes, also depends on the flow rate.
In the field of dentistry and orthopedics, where high-powered electric tools are used, even bloodborne viruses (such as human immunodeficiency virus – HIV, hepatitis B and hepatitis B viruses) can become airborne when they are contained in high velocity blood splatter generated by these instruments [18, 19]. Yet, whether they can cause efficient transmission via this route is more debatable. This illustrates another point, that although some pathogens can be airborne in certain situations, they may not necessarily transmit infection and cause disease via this route.
Over time, for a pathogen with a truly predominant airborne transmission route, eventually sufficient numbers of published studies will demonstrate its true nature . If there are ongoing contradictory findings in multiple studies (as with influenza virus), it may be more likely that the various transmission routes (direct/indirect contact, short-range droplet, long-, and even short-range airborne droplet nuclei) may predominate in different settings [16, 20], making the airborne route for that particular pathogen more of an opportunistic pathway, rather than the norm . Several examples may make this clearer.
The selected pathogens and supporting literature summarized below are for illustrative purposes only, to demonstrate how specific studies have impacted the way we consider such infectious agents as potentially airborne and ‘aerosol-transmissible’. It is not intended to be a systematic review, but rather to show how our thinking may change with additional studies on each pathogen, and how the acceptance of “aerosol transmission” for different pathogens did not always followed a consistent approach.
We first investigate the dynamics of influenza spread in three different transmission models, namely a droplet-based, an aerosol-based, and a combined droplet-aerosol-based model (for a schematic explanation of these transmission models, please see Fig. 1). These three models were chosen to compare the two extreme situations (droplet-only, and aerosol-only) as well as an intermediate situation where the two transmission modes are equally relevant 13,14 . Simulations of influenza outbreaks were based on an SEIR model run on a high-resolution contact network collected at a US high school 17 using wireless sensor network technology. In addition, we used the location information of each individual obtained using the same technology. In order to simulate partial or full aerosol transmission, we combined this data with building data from the school in order to compute the relevant infection probabilities due to aerosol transmission as per eq. 3. The entire model, and the data sources, are described in full detail in the Methods. Figure 2 shows an example of quanta concentrations in multiple classrooms during a day.
Simplified scheme of transmission routes. Different sets of individuals in the school can occupy the same rooms, at different times t1 and t2 (A). In these rooms, individuals may be in close proximity to one another. For visual simplicity, we assume in this figure that all individuals in the same room at the same time are in close proximity (but note that in the model, proximity is given by the sensor measurements). In the aerosol model, infected individuals can shed infectious material while in the room, which in turn may infect those individuals in the room concurrently or later on. The network of possible transmission pathways will therefore look different depending on the transmission routes. Based on the spatio-temporal pattern shown in panel (A), panel (B) shows the network of pure droplet transmission panel (C) shows the network of pure aerosol transmission and panel (D) shows the network of droplet and aerosol transmission combined. The edges for droplet transmission are always bidirectional, hence no arrows are shown. The edges for aerosol transmission may be unidirectional due to the temporal delay of virus shedding and virus uptake, hence arrows are shown.
Illustration of relationship between presence of infected individual and exposure to others in the aerosol model. Presence of one (selected) infected individual in different rooms (gray area) and other people’s exposure to infectious material shed by the individual in the respective rooms (black bars) across 8 hours the scale of the x-axis is hours, the scale of the y-axis is exposure in [0–0.02] quanta. Exposure levels depend on the number of exposed individuals in the room following deposition of infectious material, as well as air change rates (here 0.5).
As illustrated in Fig. 1, both droplet and aerosol transmission can be represented as weighted networks. It has been shown previously that strength (i.e., the weighted degree) is a key network metric for understanding disease spread in networks: hosts with a high strength generate on average more secondary cases, hosts with a low strength less 18,19,20 . Figure 3 shows distribution of and correlation between measures of strength for both modes of transmission, aerosol (quanta) and droplet (contact duration). As can be seen, distributions are similar and both strength measures are correlated across modes of transmission.
Weighted network representations of droplet transmission (cumulated contact duration) and aerosol transmission (cumulated quanta exposure). Quanta exposure caused in others represents outdegree, quanta exposure to the individual of interest represents indegree. Contact duration in droplet transmission is symmetric, therefore there is no difference between in- and outdegrees. Top figure and right figure illustrate weighted degree distributions the scatter plot relates network metrics for droplet and aerosol transmission to each other.
For all three transmission models, we measure three epidemiological quantities: the final size of an outbreak (number of recovered r(t) individuals after a simulation run), the total duration of an outbreak (time until there are no more exposed e(t) or infected i(t) individuals, respectively), and the time to reach the peak of the outbreak, i.e. to reach the maximal prevalence. In addition, in order to be able to put these quantities in context, we also measure R0 for the three transmission models. In an individual-based model like the one used here, measuring R0 is straightforward using the droplet-based transmission model, because one can directly track which individual infected which. However, in the case of partial or full aerosol-mediated transmission where infection is mediated by the air in a room, this tracking is harder because one would need to computationally keep track of the individual sources of infectious aerosol particles. We thus measure an alternative but similar quantity, namely the number of all cases infected during the initial time period until the index case recovers. We call this quantity R′0. Theoretically, there is a chance that this overestimates the true R0 by including third generation cases that were not infected by the index case, but given the values for the incubation period and the recovery rate, this is rather rare.
In Fig. 4, we can observe that increasing the relative importance of aerosol-based transmission (i.e., shifting from pure close-contact transmission via combined to pure aerosol-based transmission) has no major effect overall on disease dynamics. We note that outbreak sizes in the pure droplet model are slightly increased, and the time to outbreak peak is slightly increased. However, the small increase in outbreak size is also reflected in a small increase of R′0 (see Fig. 4D). In summary, our results indicate that one should not necessarily expect influenza disease dynamics to be very different when taking aerosol-based transmission into account.
Frequency distributions of mean final size (A), mean duration of outbreak (B) mean time to reach the maximum prevalence (C), and mean R′0 (D), for the three different transmission models. Color-codes in panels A, B and C follow the labels on the x-axis in panel D (red for aerosol-based, green for combined, and blue for droplet-based transmission). For each transmission model, the values are based on 78,900 simulations where each individual served as index case in 100 independent simulation runs.
For a better understanding of the behavior of the transmission models, we performed a sensitivity analysis on the core infectivity parameters (Fig. 5). In particular, we altered the droplet infectivity in the close-contact component (baseline set to 0.003 – see eq. 1) and the shedding rate (q – see eq. 2) in the aerosol component within the model that captures both modes of transmission at 50%. We changed both parameters, relative to the baselines, by −20%, −10%, 0%, 10% and 20%. As can be seen in Fig. 5, changes on median outbreak size appear to be well-behaved and proportionate, regardless whether parameters for close-contact or aerosol transmission are changed.
Sensitivity plots showing the effect of changes in relevant transmission parameters on outbreak size. In particular, both shedding rate and droplet infectivity were shifted from −20% up to +20% with respect to baseline values, as reported in the literature. (A) Scatter plot summarizing the effect of both parameters changes on median outbreak size (proportional to circles size, as shown in legend). (B) Boxplots plot presenting the details on the outbreak size distributions, depending on changes in droplet infectivity (x axis) and shedding rate (horizontal facets).
In pure droplet-based transmission models, vaccination is a powerful strategy to mitigate the spread of an infectious disease. When transmission can also be aerosol-based, increasing ventilation is an additional way to curb the spread of disease. We therefore compared the effect of ventilation to traditional vaccination strategies. According to the American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 21 , a good ventilation in classrooms corresponds to 3 air changes per hour. Most classrooms, however, have poor ventilation at rates around 0.5 air changes per hour (see Methods for more details). In the pure aerosol-based model, bringing all rooms to the recommended ventilation rate would almost completely eliminate the chance of an outbreak. This corresponds to the same effect of complete vaccination coverage in the case of poor ventilation rates, as shown in Fig. 6B. In the combined droplet-aerosol scenario, improvements of ventilation still results in a significant decrease of outbreak sizes. In particular, Fig. 6A shows that in the combined droplet-aerosol model, a good ventilation would have a similar effect to a 50–60% vaccination coverage in the poor ventilation scenario. This finding proved to be robust to changes in transmission parameters in the sensitivity analysis (data not shown).
Comparison of the effect of ventilation (boxplots) and vaccination coverage (horizontal lines) on outbreak size. Colors refer to different vaccination coverages. Results are reported for aerosol-based (A) and combined transmission models (B,C). For (A,B), air change rate varies from 0.5 to 3.0 changes/h, while (C) assumes an air change rate of 0.5 changes/h. (C) Comparison of partially improved ventilation strategies (boxplots) in the school. Classrooms for improved ventilation were selected by ranking them according to the amount of inhaled infectious particles (optimal), their occupancy according to the school roster (schedule-based), or occupancy corrected by room size (size-corrected). Effect of vaccination coverage is also reported (median outbreak sizes under corresponding vaccination coverages, reported as horizontal lines).
In practice, upgrading the ventilation system of an entire school campus to the rates proposed by ASHRAE will often be challenging due to limited resources. We therefore asked how strong the mitigating effect would be of upgrading the ventilation of only a fraction of all rooms. We also asked how one would identify the optimal set of rooms for mitigation purposes. The room selection strategies we explore are optimal, schedule-based, and size-corrected, which are all described in the methods. As expected, applying good ventilation to less rooms instead of the entire school leads to less pronounced improvements. However, Fig. 6C shows that selecting only a fraction of rooms for improved ventilation, according to the criteria explained above, still results in median outbreak sizes comparable with those obtained in a setting with 30–40% vaccination coverage. In particular, the size-corrected strategy, which requires only information readily available to each school (i.e. school rosters and room size) can result in median outbreak sizes that are comparable to those obtained with vaccination rates above 40%, even when only applied to 25% of all rooms.
Comparisons between the effects of improved ventilation and vaccination also depend on vaccine efficacy. The baseline efficacy was assumed to be 60%. If the ASHRAE recommended air change rate were implemented school-wide, this would result in a protective effect in the combined model that would correspond to a vaccination coverage of 60–70% for an efficacy of 40%, 50–60% for 60% efficacy, and 40–50% for 80% efficacy. In the aerosol model, consistently improved ventilation beats vaccination even with full coverage if efficacies are low.
Transmission-Based Precautions are the second tier of basic infection control and are to be used in addition to Standard Precautions for patients who may be infected or colonized with certain infectious agents for which additional precautions are needed to prevent infection transmission.
Source: Guideline for Isolation Precautions
Use Contact Precautions for patients with known or suspected infections that represent an increased risk for contact transmission.
- Ensure appropriate patient placement in a single patient space or room if available in acute care hospitals. In long-term and other residential settings, make room placement decisions balancing risks to other patients. In ambulatory settings, place patients requiring contact precautions in an exam room or cubicle as soon as possible.
- Use personal protective equipment (PPE) appropriately, including gloves and gown. Wear a gown and gloves for all interactions that may involve contact with the patient or the patient&rsquos environment. Donning PPE upon room entry and properly discarding before exiting the patient room is done to contain pathogens.
- Limit transport and movement of patients outside of the room to medically-necessary purposes. When transport or movement is necessary, cover or contain the infected or colonized areas of the patient&rsquos body. Remove and dispose of contaminated PPE and perform hand hygiene prior to transporting patients on Contact Precautions. Don clean PPE to handle the patient at the transport location.
- Use disposable or dedicated patient-care equipment (e.g., blood pressure cuffs). If common use of equipment for multiple patients is unavoidable, clean and disinfect such equipment before use on another patient.
- Prioritize cleaning and disinfection of the rooms of patients on contact precautions ensuring rooms are frequently cleaned and disinfected (e.g., at least daily or prior to use by another patient if outpatient setting) focusing on frequently-touched surfaces and equipment in the immediate vicinity of the patient.
Use Droplet Precautions for patients known or suspected to be infected with pathogens transmitted by respiratory droplets that are generated by a patient who is coughing, sneezing, or talking.
- Source control: put a mask on the patient.
- Ensure appropriate patient placement in a single room if possible. In acute care hospitals, if single rooms are not available, utilize the recommendations for alternative patient placement considerations in the Guideline for Isolation Precautions. In long-term care and other residential settings, make decisions regarding patient placement on a case-by-case basis considering infection risks to other patients in the room and available alternatives. In ambulatory settings, place patients who require Droplet Precautions in an exam room or cubicle as soon as possible and instruct patients to follow Respiratory Hygiene/Cough Etiquette recommendations.
- Use personal protective equipment (PPE) appropriately. Don mask upon entry into the patient room or patient space.
- Limit transport and movement of patients outside of the room to medically-necessary purposes. If transport or movement outside of the room is necessary, instruct patient to wear a mask and follow Respiratory Hygiene/Cough Etiquette.
Use Airborne Precautions for patients known or suspected to be infected with pathogens transmitted by the airborne route (e.g., tuberculosis, measles, chickenpox, disseminated herpes zoster).
- Source control: put a mask on the patient.
- Ensure appropriate patient placement in an airborne infection isolation room (AIIR) constructed according to the Guideline for Isolation Precautions. In settings where Airborne Precautions cannot be implemented due to limited engineering resources, masking the patient and placing the patient in a private room with the door closed will reduce the likelihood of airborne transmission until the patient is either transferred to a facility with an AIIR or returned home.
- Restrict susceptible healthcare personnel from entering the room of patients known or suspected to have measles, chickenpox, disseminated zoster, or smallpox if other immune healthcare personnel are available.
- Use personal protective equipment (PPE) appropriately, including a fit-tested NIOSH-approved N95 or higher level respirator for healthcare personnel.
- Limit transport and movement of patients outside of the room to medically-necessary purposes. If transport or movement outside an AIIR is necessary, instruct patients to wear a surgical mask, if possible, and observe Respiratory Hygiene/Cough Etiquette. Healthcare personnel transporting patients who are on Airborne Precautions do not need to wear a mask or respirator during transport if the patient is wearing a mask and infectious skin lesions are covered.
- Immunize susceptible persons as soon as possible following unprotected contact with vaccine-preventable infections (e.g., measles, varicella or smallpox).
The following are examples of signs for Contact, Droplet, and Airborne Precautions that can be posted outside patient rooms.