2014-08-10 ~ Medical News Blog

Ebola virus may be spread by droplets, but not by an airborne route: what that means

aerosol, airborne, droplet, droplet spray; droplet nuclei, Ebola virus, EBOV, Zaire ebolavirus

An article collaboratively written by (alphabetically)..

Dr. Katherine Arden
A postdoctoral researcher with interests in the detection, culture, characterization and epidemiology of respiratory viruses.
Dr Graham Johnson
A post-doctoral scientist with extensive experience investigating respiratory bioaerosol production and transport during breathing, speech and coughing and determining the physical characteristics of these aerosols.
Dr. Luke Knibbs
A Lecturer in Environmental Health at the University of Queensland. He is interested in airborne pathogen transmission and holds an NHMRC Early Career Fellowship in this area.
A. Prof Ian Mackay
A virologist with interest in everything viral but especially respiratory, gastrointestinal and central nervous system viruses of humans.

________________________

PLEASE NOTE. There is an important follow-up to this post, "Ebola, pigs, primates and people", that continues this story. I recommend you read it next. There are other posts on VDU as well that deal with Ebola virus disease and different fluids (semen and blood/sweat) that may contain and spread the virus. Please do search them out.

The flight of the aerosol
Understanding what we mean when we discuss airborne virus infection risk

A variant Ebola virus belonging to Zaire ebolavirus (EBOV) is active in four West African countries right now. Much is being said and written about it, and much of that revolves around our movie-influenced idea of an easily spread, airborne horror virus. Many people worry about their risks of catching EBOV, particularly since it hopped on a plane to Nigeria. However, all evidence suggests that this variant is not airborne. The most frequent routes to acquire an EBOV infection involve direct contact with the blood, vomit, sweat or stool of a person with advanced Ebola virus disease (EVD). But what is direct contact? What is an �airborne� route? For that matter what is an aerosol and what role do aerosols play in spreading EVD? How is an aerosol different from a droplet spray? Can droplets carry EBOV through the air?

Direct contact includes physical touch but also contact with infectious droplets; the contact is directly from one human to the next, rather than indirectly via an intermediate object or a lingering cloud of infectious particles. You cannot catch EVD by an airborne route, but you may from droplet sprays. Wait, what?? This is where a simple definition becomes really important.

Airborne, aerosols, droplets, nuclei and confusion

Whether propelled by sneezing, coughing, talking, splashing, flushing or some other process, aerosols (an over-arching term) include a range of particle sizes. Those droplets larger than 5-10 millionths of a meter (a micron [�m]; about 1/10 the width of a human hair), fall to the ground within seconds or impact on another surface, without evaporating (see Figure). The smaller droplets that remain suspended in the air evaporate very quickly (< 1/10 sec in dry air), leaving behind particles consisting of proteins, salts and other things left after the water is removed, including suspended viruses and bacteria. These leftovers, which may be more like a gel, depending on the humidity, are called droplet nuclei. They can remain airborne for hours and, if unimpeded, travel wherever the wind blows them. Coughs, sneezes and toilet flushes generate both droplets and droplet nuclei. Droplets smaller than 5-10�m almost always dry fast enough to form droplet nuclei without falling to the ground, and it is usual for scientists to refer to these as being in the airborne size range. It is only the droplet nuclei that are capable of riding the air currents through a hospital, shopping centre or office building.

The droplet nuclei and the air that surrounds them are correctly referred to as an aerosol, but so are lots of other things and this is where confusion grows. The term aerosol is used to refer to any collection of particles suspended in air, and particle sizes vary enormously. Spray paint from a can is produced in droplets a few hundred microns in diameter so as to quickly coat the intended surface rather than undesirably linger in the air. A can of fly spray on the other hand produces smaller droplets, because that aerosol should stay suspended for long enough to make contact with insects. �Aerosol� is a confusing term, and its varied usage does not help when discussing risk of EBOV infection.

The simplest definition for public understanding of infection risk is to use �airborne� to refer only to the droplet nuclei component.(4)

Figure 1. A representation of how different viruses may be propelled on their journey to cause disease in humans. Recommended droplet precautions for dealing with cases of EVD include the use of gloves, impermeable gowns, protective goggles or face shield and a face mask.(5,6)
Image updated 26-August.

For EBOV at least, airborne droplet nuclei are apparently not infectious to primates under natural or near-natural circumstances (see here for more detail about non-human primates and aerosols used under highly unnatural laboratory conditions).

Why that is so is not known, but perhaps it is because this virus does not survive being dried down, or that primates don�t produce enough virus in what is coughed out to make infectious droplet nuclei. To be clear, there may be some EBOV in these droplet nuclei - but it has never been shown to cause disease, even when that route has been looked for in the same household as a case of EVD.

How the science helps and also hinders understanding.

The scientific literature has a number of very specific examples where droplet nuclei have been used to infect non-human primates with ebolaviruses in order to study the effectiveness of vaccines or antivirals.(1,7,8) These infections are under idealised laboratory conditions, often with what we think are unrealistically high levels of virus. Although airborne infection can be made to occur in a lab, there is no evidence for airborne droplet nuclei spreading EBOV from person-to-person or between non-human primates whether inside or outside the lab.

Protection and clarification.

Included in guidelines issued by the WHO (7) and CDC (5) is the need for droplet precautions (Figure). This is very important for healthcare workers, family and other caregivers who stay close and are frequently exposed for lengthy periods of time with severely ill, highly virulent cases of EVD. These cases may actively propel infectious droplets containing vomit and blood across the short distances separating them from caregivers. But this is a form of direct transmission, and is not airborne transmission.

Messaging the masses.

Leaving aside other issues around acquiring a rare disease like Ebola when outside of the current outbreak region, the case definitions and risk assessments have raised confusion. There are questions around how otherwise apparently well-protected healthcare workers in West Africa are acquiring an EBOV. For a virus described as spreading only through direct contact, recommendations for the use of masks, implying airborne spread to many, fuel such questions. In fact, face protection is recommended to prevent infectious droplets landing on vulnerable membranes (mouth and eyes).

It�s important to pass a message that is correct, but also to ensure distrust does not result from a public reading apparently contradictory literature. Such distrust and real concern have been rampant among a hyperactive #ebola social media. Simple, clear phrases like �ebolaviruses cannot be caught from around a corner� (h/t @Epidemino), may help uncomplicate the communication lines. And it works on Twitter.

[UPDATE #1 9-Sept-2014]

References

Behind the naming of ebolaviruses... [UPDATE 2]

Ebola virus, ebolavirus, genus Ebolavirus, phylogeny, taxonomy

Just don't call me a taxi

Virus taxonomy is the classification of viruses into groups based on similarities.

Today classification is supported by viral gene and genome sequence information.

The International Committee on Taxonomy of Viruses (ICTV) takes care of the official virus taxonomy. It has a pretty friendly website with a good search engine and the latest (2013 at writing) virus taxonomy can be found here. [1]

So what does it, and its tome, Virus Taxonomy, Ninth Report of the International Committee on Taxonomy of Viruses [2], have to say about ebolaviruses? Well, not as much as you might like, if you want to be able to name them, talk conversationally about them and discuss the issues around the disease resulting from infection by most of them. Sure, you can just call it all "Ebola" (which is a river in Africa by the way) and be done with it, but you'd be wrong. And some smart alec will correct you for sure. Here is where the ICTV Filoviridae Study Group fills in a lot of blanks.

One thing to get on top of first up. When talking or writing about these looking little pathogens, we can just call lump them together under the conversational term "ebolaviruses" thus..."Hey Jeanette, did you hear about the latest ebolavirus infection numbers over the weekend?" is a question that could refer to any of the 5 very different viruses.

So, let's try and make that tearoom conversation a little more accurate.

The very dry detailed stuff down to the level of a species.

The italicization and the capitalization below are really important to taxonomy guys - so, ya know, care.

Also, the ICTV reminds us that the name of the species is not the name of a virus - they are 2 different things. The species is a broad term for all the measurably different viruses out in the wild, that it contains. Here, species is to viruses what Mitsubishi Sigma is to identifying my old car. A virus name,

e.g. Ebola virus (see below), is like identifying my car as "a silver 1988 Mitsubishi Sigma".

What if we used taxonomy on cars? A different way to explain how to name ebolaviruses.
Click to enlarge

The viruses we are talking about here belong to the order Mononegavirales, family Filoviridae, genus Ebolavirus.

There are 5 species within the genus. The species names are in italics below. Underneath is the name of the virus (the virus belongs to the species container) and its abbreviation. The viruses in bold have caused outbreaks of human disease.

Ta� Forest ebolavirus

Ta� Forest virus (TAFV)

Reston ebolavirus

Reston virus (RESTV)

Sudan ebolavirus

Sudan virus (SUDV)

Zaire ebolavirus

Ebola virus (EBOV)

Bundibugyo ebolavirus

Bundibugyo virus (BDBV)

But what should I call the latest ebolavirus strain, variant, genotype, subtype, serotype, isolate thingy?

In the case of the current outbreak, that latest virus is an Ebola virus (EBOV), which we can now say belongs to the species Zaire ebolavirus (a Mitsubishi Sigma).

But back to the car analogy. The silver 1989 Mitsubishi Sigma name is still not enough to tell it apart from any other silver Mitsubishi Sigma parked at the same shopping centre. How do you choose yours in a way that won't get you arrested for breaking into someone else's car? They both look like silver Mitsubishi Sigmas. But the silver Mitsubishi Sigma with license plate ABC 321 is yours and your alone, and that code differentiates your car from any other anywhere in the world.

We know from genome sequencing studies that the virus circulating in Guinea is an EBOV (a silver Mitsubishi Sigma) and is not identical to the one in (what was called) Zaire in 1976 (this silver Mitsubishi Sigma car has a different license plate). They couldn't be the same physical virus anyway, because each person hosts millions and millions of virions, each cell has a varied population of viruses in it, and each virion has a relatively short life.

There is no universal definition for classification of viruses below the level of a species. But there are lots of terms that are used - most are listed in the heading to this section. In filovirus-land, the Study Group has sought to impart some order upon the chaos [3].

A virus strain needs to have 1 or more observable, genetically stable and unique differences compared to other viruses in the same species. For instance, one might cause a disease that is different from the one we know. So apart from a different license plate, it might also have an Awesome Mix #1 CD in the tray.

From Kuhn et al.[5]
Viruses 2014, 6(11), 4760-4799Click on image to enlarge.

A variant has some genetic sequence or other differences that may result in a slightly different observable change. The West African EBOV is a variant and not a strain of Zaire ebolavirus and was named after the Makona river (see figure) which makes contact with all three countries that have had widespread and intense transmission.[5] For example, these from Guinea and Sierra Leone:

A virus isolate is a virus sample resulting from growing or culturing it in cells or tissues. Variants can therefore be represented by isolates. These isolates can be identical or slightly different (your neighbour could order the exact same car as you did-but he would still have a different license plate and no bobble-heads and fluffy dice).

The naming schemes do go into further detail, but you can read that in [3].

The disease.

The disease caused by EBOV, SUDV, TAFV and BDBV is called Ebola virus disease (EVD). Frankly, that is a tough one to explain after all of the above. It reads as though we are talking about just 1 virus causing disease (EBOV). But not so. Viruses from 4 species cause EVD - EBOV, SUDV, TAFV and BDBV. Diseases are named by World Health Organization's International Classification of Diseases (ICD) site, (4) and the name of this disease goes back many years and has not been updated yet. The disease has been called Ebola haemorrhagic fever, but is not now. Ebola virus disease is, by itself, a proper noun - that is its name - so it always gets the capital 'E'. And to continue from the taxonomy above, EVD is caused by a virus that can be ascribed to a species. In West Africa right now, EVD is due to infection by an Ebola virus variant classified in the species Zaire ebolavirus.

Navigating a tree in the ebolavirus jungle.

Lastly, I've cobbled together a tree of genomes from each of the 5 ebolavirus species. It may help. Or not.

A phylogenetic tree of some genome sequences of the 5 species of ebolavirus, each indicated with a specific coloured dot.

References...

ICTV Virus Taxonomy: 2013 Release
http://www.ictvonline.org/virusTaxonomy.asp
Ebola virus disease World Helath Organization fact sheet
http://www.who.int/mediacentre/factsheets/fs103/en/
Virus nomenclature below the species level: a standardized nomenclature for natural variants of viruses assigned to the family Filoviridae.Arch Virol (2013) 158:301�311.
http://download.springer.com/static/pdf/619/art%253A10.1007%252Fs00705-012-1454-0.pdf?auth66=1408093824_af9d701ab93574066469a6f6745c11d7&ext=.pdf
International Classification of Diseases (ICD)
http://www.who.int/classifications/icd/en/
Nomenclature- and Database-Compatible Names for the Two Ebola Virus Variants that Emerged in Guinea and the Democratic Republic of the Congo in 2014
http://www.mdpi.com/1999-4915/6/11/4760

Updates...

05AUG2015: Added comment about Ebola virus disease being a proper noun

How to read a VDU graph...

Ebola virus, Graphs, H7N9, How to, MERS-CoV

I'm a pretty simple guy. So the stuff that I put onto Virology Down Under's (VDU) blog is usually something I think can be understood by you - my yard stick is that if I can understand it, then I think you can. Sometimes it can get pretty technical though and with things always done in a rush, I don't stop and explain as much as I could. Which is why I value feedback. And I've had some good stuff from @DeclanButlerNat, @JorgeCastillaE and @Moro_Cedric this week.

Different levels of experience read this blog and my posts on Twitter, so sometimes I direct my graphs towards them. But I do understand that we scientists can be easily carried away by our interests and forget that we're quite used to interpreting our own presentation styles in a certain and speedy way. We've had lots of experience doing it that way. I can change a tyre (as I was reminded a couple of nights ago, at midnight) but I couldn't fix my engine.

At the heart of reading a graph is this fact: you have to look at the axes to understand what the lines or bars or areas mean. Once you know the style, you can understand it at a glance - but first time, examine it with care. If it's one of mine, feel free to ask me what I'm trying to show if it is not immediately obvious. I very well may have failed to make it clear.

So this is a little overview of how to read some of the graphs which I use to communicate what I consider to be otherwise yawn-inducing tables of numbers about viral infection and disease numbers.

A picture is worth a thousand words..

This is a good thing because with my lack of typing skills, if I had to type 1,000 word all the time, that would be at least 200 typos. Graphs plot those tabular numbers in a more colourful and visual way. Once you know how to read a graph, they can become powerful and quick ways to get a quick update on the state of play. On VDU the game seems to be about outbreak data. That's just the way things have evolved for me since I first blogged on 28-March 2013. This includes graphing the number of people with disease (cases), changes in the number of cases, numbers that are suspected versus the number that are actually laboratory confirmed (my currency), dates of onset illness (favoured piece of data and the hardest to come by publicly), the numbers who die, the proportion (%) of all cases/detections who die, dates when disease was reported, sex, age and all of that can be plotted on graphs by day, week, month or year.

Interpreting a basic graph on VDU...

The graph below (Graph 1) comes from following Middle East respiratory syndrome (MERS) public data. It shows the key parts of the structure of the graphs - the axes (the horizontal and vertical lines that are the key to reading the plotted numbers) and the axes.

A basic graph has a bottom horizontal line called the x-axis and it has a vertical line on the side called the y-axis. These are used to tell you what the numbers plotted on the graph mean; they are a key to the placement of each point on a graph, according to at least 2 different values.
Each point on a graph represents a coordinate. Its made up of an x-axis values (abscissa) and a y-axis value (ordinate). For example we plot 50 cases reported on Thursday or 50 on the y-axis and Thursday one the x-axis (x,y)
The points that we plot as pairs of x and y data can be joined up and shown as a line (the area underneath the line can also be coloured in which looks like a mountain that may have peaks and troughs) or they can be plotted as bars. There are other ways too - but I keep it simple. Joining up these dots is not always accurate - we may have no idea what is really happening to the numbers between any 2 points, in that case a bar graph may be more realistic as it shows the numbers at a distinct point in time. Sometimes bar graphs don't work from a formatting perspective (eg bars get so skinny you can't see them). Other times, joining the dots reveals the trends (the general direction that events are heading even if we don't know the values). Trends are useful in infectious disease as they show what has happened and what the latest data mean in the context of what has come before - so not too unrealistic. Some of this is about being accurate while not being too overly obsessive.

The particular example graph I've included below (Graph 1) is a little trickier than some because it has 2 y-axes (vertical lines) - a primary (left-hand side) and a secondary (right-hand side). Some of the numbers are plotted against the primary y-axis (left vertical line) and some against the secondary y-axis (the right hand vertical line). This lets me "double-dip" on shared x-axis numbers, in this case, dates. I'm graphing the course of 2 different things (number of actual cases by day of illness onset) and the number of reported detected by date. These are 2 different things that have dates in common.

This graph lets us compare, using the same x-axis, what the MERS case numbers look like when they are plotted by the day the people were reported to have become ill compared to the date of public reporting of the cases. There are differences that become more clear when you can run the 2 lines on the same graph, that may be a bit harder to see when they are plotted on 2 separate graphs. This graph highlights that when cases become ill and when they are reported are different things. It also shows that there were a bunch of cases (113) reported in 1 day that have never been given dates of illness onset (or hospitalization or the date they were each reported to the Ministry of Health). It also makes use of the 2 y-axes to have different scales. The primary or left-hand y-axis goes up to 35 while the secondary or right-hand y-axis maxes out at 120. If the same axis values were used, the illness onset cases would mostly be hard to see.

Graph 1. The basics of a graph.

What about cumulative graphs? What are they and how do I interpret those?

The next graph is made to show cases piling up over time (Graph 2). This is the graph that sparked this blog. It plots numbers as a line graph but instead of showing the value at that timepoint (day, week, month, year), it adds the new number to sum of all the previous numbers. It is plotting a cumulative tally, so it will always be a hill with an upwards (left-to-right, bottom to top) slope except when there are no new cases to add, when the curve becomes parallel to the x-axis - a flat line. How steep that line is can tells us how rapidly cases are piling up. That can also be fudged if you present the chart with a very short or long x-axis.

In the case of the Zaire ebolavirus outbreak in West Africa, we have the unusual ability to compare numbers from multiple countries at the same time, and use the same x-axis. Here, we show the date when the World Health Organization's Disease Outbreak News update was released. Sadly for us graph addicts, this doesn't include any illness onset dates, but the WHO do have those data and plot it themselves here (1).
A steep slope indicates a rapid rise in cases and this results from a lot of new cases being added in a short period of time.
A near flat or horizontal slope to the line shows that there are not many new cases being added.
In this graph we also show multiple lines plotted using the primary (left) x-axis to present how much and at what rate the total suspect, probable and laboratory confirmed case numbers are piling up (pink) as well as how the deaths from among that number are changing (blue line) and how many of the cases are being laboratory confirmed (green line) as due to the virus suspected of being the cause. This last one is important as it gives a glimpse of how the laboratory network is coping, perhaps how specimen access is going and how much faith to put in the other two totals. Why are we worried about the result totals? Because many other things can look like Ebola virus disease (EVD) early on, and even later in the disease course. A laboratory test is the only way to be certain that the patient had that virus.
Nigeria's numbers look to be rising alarmingly fast. Relative to each other they are, but compared to the dozens of new EVD cases being added between reports in other countries, it is still a small (although still very bad for Nigeria!) increase. This highlights that care is needed when reading charts. Perhaps also an understanding that between different outbreaks, the rate of new cases being added is disease specific. Lots of influenzavirus detections during flu season is what we expect, any ebolavirus cases are not what we expect nor what we want to see. Context. A hard thing to account for and probably a matter of experience.

Graph 2. The cumulative case graph. Adding new numbers to the sum of all the numbers that came before.
Click on image to enlarge.

Graph 3. Changing the scale. Raising the primary y-axis (left) scale to 750, the level of the other country graphs, makes Nigeria's case numbers look tiny. But it underestimates the impact of the localised spread of Zaire ebolavirus in an are that was not part of the outbreak until a case flew in and spread it. Changing the scale is not just whimsical decision making, it can highlight the importance of events that may otherwise go unnoticed.
Click on image to enlarge.

Take care when interpreting a graph - look at the axes and also use your noodle

Finally, I'm going to look at the way in which I present the numbers I plot on a graph. I'm using the cumulative case chart for Liberia as my example (Graph 4 collection). Its the same one used in Graph 3 - the only thing different is that I've dragged the x-axis to the left (shrunk) or to the right (stretched) to see what that does.

The line plots look more or less steep when you shrink or stretch the x-axis, respectively. But the numbers have not changed. Possibly, our interpretation of them has, as a result of seeing the slope change. Remember though, check the axes. If you look at the x-axis, the shrunken version shows that those cases have climbed over a longer period than the slope suggests. Always check the denominator (the y of x/y) when you think about slope. Equally, the flatter curves of the stretched out x-axis, at the bottom of the Graph 4 collection, have to be looked at in context with time. The dates have been dragged out to what may be an unreasonable length, which makes the slopes look less; but they are still steeper in July than they were in April. Look around the graph for comparison.
As I said above, the current multi-country outbreak lets us compare and so we can see that some areas are adding new cases very rapidly between each report (Liberia and Sierra Leone) while others (Guinea) are not adding as many as quickly. Nigeria looks to have jumped quickly but that is also because of the altered scale (discussed above)
On VDU I get around this by also adding charts that plot total numbers per day or week or month or year. This shows a more discrete series of data that grow or shrink as the outbreak peaks or resolves. The 2 peaks of influenza A(H7N9) virus outbreaks illustrate this nicely - especially when combined with a cumulative case chart (Graph 5)!
There is no real right or wrong here (although there are pixel width constraints)- but don't let your perceptions fool you when looking at someone's graphs for the first time. Take some time to really look at the graphs.

Graph 4 collection. Stretching the x-axis can seem like stretching the truth. But carefully read the axes. Some experience is needed here and ultimately you are at the mercy of the person presenting the data.
Click on image to enlarge.

Graph 5. Influenza A(H7N9) virus outbreak in China during 2013 and 2014. Plotting the numbers discretely (by week) clearly shows the two outbreak peaks (darker blue lines joining the data point dots) and gives valuable context to the cumulative graph in the background (pale blue mountain). This is probably my favourite style of disease numbers graph.
Click on image to enlarge.

I hope that has helped make sense of my graphs, and perhaps those of others too. I'm always on Twitter so hit me up with questions about this or requests for more posts like this, or to tell me whether it was helpful.

References

http://www.who.int/csr/disease/ebola/EVD_WestAfrica_WHO_RiskAssessment_20140624.pdf?ua=1

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Medical News Blog Information

Ebola virus may be spread by droplets, but not by an airborne route: what that means

Behind the naming of ebolaviruses... [UPDATE 2]

How to read a VDU graph...

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