Preparing for pandemics

04 November 2014

Interview with

Colin Russell, Cambridge University

Researchers are exploring new ways to assess the risks posed to humansMap of pandemics

by non-human influenza viruses. Colin Russell from the University of Cambridge spoke to Chris Smith about how to predict pandemics...

Colin - In the last 100 years, we've had five influenza pandemics in humans. Four of those pandemics started with viruses that came directly from animals and one of them happened probably as a product of an unintentional laboratory release. There's a tremendous diversity of influenza viruses that are circulating in animals right now. In chickens, in pigs, horses, basically every animal in which we've ever looked hard enough to find an influenza virus we find influenza viruses. We're almost certainly going to have another influenza pandemic within the next 10, 20, 30 years. But the question is which virus is going to cause that? It's important that we figure out which virus is going to cause it because our only good preparations right now to combat the next pandemic are the development of vaccines and the development of anti-viral drugs. And it's particularly the development of vaccines that requires very specific knowledge about the virus that's going to cause the pandemic.

Chris - So it's a bit catch 22 because until we know what's coming, it's very hard to defend against it but we won't know what's coming until it gets here.

Colin - Well that's really the difficulty and so right now, we operate under a very simple model whereby viruses that we observe to cause infections in humans are more likely to cause a pandemic than those viruses that we have not observed to infect humans. However in 2009, we got a pandemic of an H1N1 virus from pigs in Mexico.

Chris - No one saw it coming.

Colin - We didn't see it coming and we want to avoid the repeat of the same situation where we think we know what we should be paying attention to but in fact, we get blind-sided by something else entirely.

Chris - So using the power of the connected world we now live in and our better understanding of influenza and how it spreads and circulates, is there a better way to predict what might be around the corner? What are you proposing in this paper?

Colin - Well what we propose is actually sort of a road map of things that we need to pursue in order to do a better job of assessing risk. We need further experimental work in the laboratory. What are the attributes that a virus needs to acquire in order to be able to transmit efficiently from humans to humans? Once we have a better experimental handle on figuring out what these attributes are, it would be really good if we didn't have to rely on wet laboratory experiments. They're very time consuming and they're very expensive. And so, if we had a new virus that emerged today and then we to go into the lab and do a bunch of experiments on it, that would take a lot time and a lot of money when we might actually be better spending that time actually responding to containing that virus because we're better able to assess that as a threat.

Chris - What are you proposing instead then? That we do this in a computer?

Colin - Basically. So ideally we'll eventually get to a place where we can just get the genetic sequence of that virus and then from that genetic sequence be able to infer all of the risk characteristics of that virus.

Chris - How?

Colin - That's where the tricky part comes in because right now we're a long way from being able to do that. We need a combination of more experimental work and we need a combination of development of new computational methods that we can use to infer those characteristics from genetic sequences.

Chris - Is that because we're just looking at very large numbers of viruses and marrying up what those viruses did, what the outcomes were, what sorts of pathogenicity, how will they make people in other words were associated with them and then say, well if we look at the new viruses just emerged does it have or share any of those particular traits we've seen before and marry traits together to make predictions.

Colin - Exactly. It's those individual traits that you just started to refer to there where things like the pathogenicity of the virus. If we can link that pathogenicity back to specific genetic mutations, then we can make inferences about newly emerging viruses. But one of the real difficulties that we face right now is that we don't have a good handle on if mutations in one virus cause the same effect if we saw those same mutations in a different virus.

Chris -   I can see how that will work very well for viruses that we know exist and that we have some experience of dealing with but in just the last few years we've discovered that bats may be carrying a new strain of flu no one had ever heard of. So what about viruses that are unknown?

Colin - And they're of course the trickiest ones. And so in addition to this experimental work and the computational tool development to make better inferences from genetic data, we also need better surveillance in animals and we need better surveillance in humans, too. We actually need a more systematic analysis of where we should actually be looking for these viruses to emerge. Most animal influenza surveillance is done in a very ad hoc way. We perceive there to be a problem and so we go and do surveillance  rather than figuring out where these viruses are most likely to be transmitting and where they have the greatest potential to transmit to humans. And so to that end we could imagine doing an analysis whereby we look at the distribution of livestock populations figuring out where the greatest density of those populations are and where humans are most likely to be exposed to those populations. We also need better surveillance in humans because right now we have good surveillance here in the UK but for all of the places where we do have good surveillance there's a whole lot of places where we have effectively no surveillance at all.

Chris - No, don't tell me. I bet those are the hot spots.

Colin - Well that's the difficulty right? Because it's in those places where humans have most contact with animals that these viruses are most likely to emerge and its places where humans have most contact with animals that tend to be the poorest and have the least public health infrastructure and thus the least ability to actually detect when these events are actually happening.

Chris - Self-fulfilling prophecy.

Colin - In some ways it's difficult to imagine how it would be any other way in terms of the ability to put emphasis on the detection of emerging viruses when you're at the same time having to deal with a bunch of diseases that don't affect more developed countries.

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