Charles Basenga Kiyanda

How surprising is it actually that nurses were infected with Ebola in Texas?

I’ve been using twitter more and more (mostly given that I’m involved in a local Montreal openstreetmap group and I’m one of the two curating that twitter account) and recently got involved in a back and forth with @2closetocall about his following tweet:

@2closetocall: Ebola, this disease that is supposedly so hard to transmit… And yet we now have two nurses infected by one patient. Are the proba. right?

The exchange then went:

@cbkiyanda: @2closetocall yes, probs are right. The 3 Dallas cases are people who handled/medically cared for infected. Not random people on the street.

@2closetocall: @cbkiyanda but ehy also (at leats in theory) took way more protections than a random person

@cbkiyanda: @2closetocall which is why science is preferred (e.g. ) over asking questions on twitter based on 2 data points.

@2closetocall: @cbkiyanda and ironically, by asking on Twitter somebody provides me with that…

@2closetocall: @cbkiyanda also, these rates still show that two nurses being infected while taking crazy precautions was unlikely it seems

@cbkiyanda: @2closetocall: need contact w/ vomit, blood, feces.  RT @NateSilver538: No, you didn’t catch Ebola on the subway.

@cbkiyanda: @2closetocall : hence, while they take more precautions, med. staff are also much more likely to come in contact with blood, vomit, feces.

@2closetocall: @cbkiyanda I know all this obviously. I still think you’re missing my point. But thanks anyway

@cbkiyanda: @2closetocall I feel you’re missing mine. Lower likelihood of infection given precaution, comes with increase in likelihood due to task.

I’m not sure I’m so enamored with twitter as a discussion platform, so I figured I’d go back over what I view as the underlying problem in his argument in more than 140 characters.
I think that through this exchange I ended up with the right point. I’m not a statistician, so this stuff is always hard for me, but I’ll try to make this important discussion justice.

The initial assertion, which tickled me wrong a bit, essentially states: “Ebola is hard to transmit. Two Texas nurses contracted ebola after treating a single patient. Doesn’t that mean ebola is easier to transmit than we are lead to believe?” (It’s kind of interesting that the gist of a tweet is longer than the original tweet.)

The question, as posed, is (intentionally or not) leading the reader to answer yes. Let me try to summarize the whole argument. Some of what I say here is interpreted from the tweets. (Hence my general uneasiness about having twitter discussions.) It seems to me the argument revolves around surprise. With the high tech means we have in modern, western countries, shouldn’t it be harder to catch ebola while treating patients? These nurses were taking crazy precautions!

Obviously, I believe the answer is no.

The argument appears to assume a few things:
*Two people catching ebola from a patient is unlikely, at least in the US;
*The likelihood of medical staff to catch ebola is the same as that of othe general population;
*Extraordinary protective measures were taken.

First, let’s make something clear: estimating the reproductive rate of diseases is difficult. There’s a statistical measure of the infectivity of viruses (the R0 value, which is what’s estimated in that paper I linked to). R0 tells you, roughly and on average, how many people an infected person will infect in an otherwise uninfected population. If you look at the paper I linked to above, the numbers that come out are around 1.5-2.0 for the current African epidemics. So, one patient infecting two people is actually around the average and not some crazy number like 15. Let me make another point very clear here: the way I just used the R0 value is probably borderline dangerous. Statistics is hard. Statistics from epidemics is doubly hard. Be careful. One may also be tempted to claim this is the R0 value for Africa. Surely, the value must be lower in the US right? We don’t know what R0 would come out to be for an ebola epidemic in the US. There’s never been an ebola epidemic in the US.

The question we’re being asked, though, is whether infecting two people with ebola is really unlikely. This leads to the second point. Statistics like R0 can be misleading because they are statistics over the whole population and assume uniformity. Here are some groups within a population that I would expect to be more at risk of contracting the disease (warning: what follows is my own conjecture and not the expert advice of an epidemiologist). Given that ebola is transmitted through the blood, vomit, and feces of a symptomatic person, I would expect to be more susceptible:
*young children, as they tend to have worse hygiene habits than adults;
*people who care for young children as a job, since they’re surrounded by little pooping machines all day long;
*those who care for infected individuals, i.e. medical staff and close family, since they’re asked to handle the bodily fluids.

Note that it would be expected of nurses to be more at risk than doctors (at least in the west). Doctors don’t change vomit laden sheets, nurses do. Nurses are also the ones drawing blood for tests and carrying it around for testing. It’s kind of like being surprised that more firefighters die in building fires than the general population. It’s not that surprising: firefighters are asked to walk into fiery buildings. What’s surprising is there are not more firefighters dying in burning buildings. That, of course, is because they are trained for this and use protective equipment, which brings us to point 3.

News titles about an ebola patient in the US conjure images of Hollywood movies with CDC personnel magically appearing in hospitals at the first sign of a case and negative pressure plastic rooms popping out of nowhere. I’m not an M.D., so you probably want to go get a bag of salt about now. In the TX case at least, we know that at least two nurses were allowed to travel after the case was confirmed. We have reports that blood samples were mishandled. The patient wasn’t isolated rapidly. Here’s what appears to be a good rundown of what happened in Texas contrasted with the response in New York. I particularly like the bits pointing out that all the CDC protocols were devised for field hospitals in the middle of Africa, which appears to have at least not helped in a large US hospital. The quote from the CDC that “more gear may have in fact increased the risk” is quite interesting. The best defense against Ebola appears to be procedures, not gear. Procedures comes with experience, not money. In that respect, we may not have that much of an upper hand when compared to DWB staffed teams in Africa. The DRC has been dealing with Ebola since 1976. “The west” has only had domestic cases for 3 weeks.

So there you have it: this is, in way more than 140 characters, my scientifically inspired opinion behind my lack of surprise at the Texas cases. Of course, far from me the idea that we should not be a little nervous about Ebola spreading. We’ll know better from the New York situation whether the CDC has learned a lot from Texas. No doubt, they’ll share their expertise with other health agencies around the world as fast as possible. As for us lowly mortals, it’s easy to feel powerless and cynical. Interestingly, there are actions we can take.
*You can give to doctor’s without borders;
*you can call your local representative (whatever name that takes in your country) and ask why we are not doing more to help with the current epidemic in west Africa (Mali has just had a 2 year old die of Ebola).

You can even go all geek and participate in mapping efforts. The openstreetmap community has a humanitarian effort to map conflict and crisis regions from satellite pictures. By now, humanitarian organizations are making requests to have maps made of specific regions. There was just a recent request to map 5 potential sites for treatment centers in Liberia.

So until we have reports that Ebola was transmitted through sneezing (there are no such reports), don’t freak out and help if you can.

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