Researchers Predict Location of Next Pandemic Disease
Tuesday, February 19, 2008
In a telephone news conference on Feb. 19, 2008, scientists from four well-known institutions discussed new research that predicts where the next pandemic, like HIV/AIDS or SARS, could occur. This is the transcript.
- Katherine Anderson of Nature
- Rita Teutonico, coordinator, National Science Foundation's Human and Social Dynamics priority area
- Kate Jones, lead author and senior research fellow at the Zoological Society of London
- Peter Daszak, executive director of the Consortium for Conservation Medicine at Wildlife Trust
- Marc Levy, deputy director of the Center for International Earth Science Information Network
- John Gittleman, dean, University of Georgia's Odum School of Ecology
>> Coordinator: Good afternoon, ladies and gentlemen, and welcome to the Nature Press Briefing, hosted by Katherine Anderson of Nature. My name is Phil, and I will be your coordinator for today's conference call. For the duration of the call, you will be in listen-only mode, but at the end of the call, you will have the opportunity to ask any questions. If at any time you need assistance on the call, please press *0 on your telephone keypad and you will be connected to one of our operators who will assist you further. I now hand you over to Katherine Anderson. Thank you.
>> Katherine Anderson: Hello everyone, and welcome to the Nature Press Briefing concerning a paper being published in Nature this week about global trends in emerging infectious diseases. Before we begin, I'd like to remind everyone that the paper in this briefing are subject to the Sound of Nature Embargo of 1800 London Time, 1300 U.S. Eastern Time, this Wednesday, the 20th of February.
So, I'm just going to introduce the speakers. First of all, we're going to hear from Rita Teutonico who's just going to give some opening remarks, and she's at the National Science Foundation, and then we'll hand over to the four authors of the paper, four of the authors on the paper. Um, first of all, Dr. Kate Jones at the Senior Research Fellow--a Senior Research Fellow at the Zoological Society of London. She's going to introduce and just give brief outlines of study. Um, she's going to be followed by Dr. Peter Daszak, who's the Executive Director at the Consortium for Conservation Medicine at the Wildlife Trust. Next, we're going to hear from Marc Levy, who is Deputy Director at the Center for International Earth Science Information Network at the Earth Institute at Columbia University, and finally, we're going to hear from Professor John Gittleman who is Dean of the Odum School of Ecology at the University of Georgia, and after everyone has spoken, there'll be time for questions. We'll hand back over to the phones for Q-and-A. OK, and now I'd now like to pass you over to Rita Teutonico.
>> Rita Teutonico: Thank you, Katherine. I just wanted to commend the work of this truly interdisciplinary team and all the researchers who have collaborated with them on this fascinating project. Results like these, the ability to map, for the first time ever, where our next pandemic might occur, really demonstrate why federal funding of basic research is so important. The potential impact of a tool like this for policymakers and research managers is enormous. Understanding the hows and whys of disease emergence and their impact on human populations, not to mention the potential public health benefits, is crucial for global administrators. The NSF-wide Human and Social Dynamics priority area, which funded this research, was proud to be a part of it. The National Science Foundation looks forward to playing a leading role in interdisciplinary approaches to such important questions in the future. Thank you.
>> Katherine Anderson: OK. Thank you. So, Dr. Kate Jones.
>> Dr. Kate Jones: Thank you, Katherine. So, here's a general introduction here and then I'm just going to go through the main points and then the other authors are going to elaborate a bit further. So, we face a global extinction crisis, and I'm working to understand the processes of few past and present pattern diversity and then really trying to use this knowledge to build predictive models to forecast and prevent future loss and loss of--by adjusting loss of ecosystem services like pollination or provision of clean water. Now, we started to think about how we could bring this predictive approach to understand how these diseases emerge. So initially we were actually interested in understanding how wildlife diseases emerge, like chytrid fungus in amphibians or rabies in wild dog and lion populations. The data really weren't globally available so we actually focused in on one animal first so we were trying to focus on building predictive models of what causes the emergence of human infectious diseases. Can we really make an impact on understanding why, where, and when, what's coming next? So, emerging infectious diseases are diseases that have increased in incidence, impact, or range, or that are newly evolved like multi-drug resistant TB or malaria, or entered the human population for the first time were really nasty like HIV/AIDS(?), Ebola, SARS, Marburg, Nipah, Hendra.
So, to sum it up, by building a database from all the literature we could gather over the last 64 years, we got information for stringent self-defined(?) emerging infectious disease events. This is the first temporal and social current emergence of this disease into the human population. So, briefly, if we outline what we found, controlling for reporting effort, we found a significant increase in emerging disease events that have occurred over the last 64 years. A lot of these diseases are microbial such as the drug-resistant strains of pathogens like drug-resistant TB and malaria. They're also -- three-quarters of them are actually from animals. They're from domestic or wildlife species that are jumping over into humans.
So, we looked at the pattern of spatially where they emerge and found a number of hot spots. So, such as northeastern Iraq, Western Europe, Japan, and southeastern Australia, but to get back to my point about building predictive model, we really need to understand what the drivers were of these occurrences so we looked at proxies of human impact, environment, and ecology. So, firstly, when we looked at what was collated with these events, human population density that are human impact with having significant influence on where these emerging infectious diseases actually occurred so it's driven mainly by human population density or impact on the environment. Now, this is different for the different types of EIDs that we looked at so drug-resistant EIDs were also impacted, uh, influenced by human population growth so that's an additional factor to finding those drug-resistant strains. Now, really importantly, the one showed(?) zoonotic EIDs are the ones from animals are actually a combination of human impact, and actually where a lot of animals are. So, these wild places where there was an increase in growth in human density is where there's an increased likelihood of getting these really nasty zoonotic diseases. So, therefore, when you protect areas which are rich in wildlife development, this may have a significant effect preventing future disease emergence in humans, and it really does provide a powerful argument for wildlife(?) conservation.
>> Katherine Anderson: Thank you, and Dr. Peter Daszak.
>> Dr. Peter Daszak: Yeah. Hi there. I've been working on emerging diseases for about 15 years now. When I first started looking at wildlife diseases that seemed to be emerging and I was part of the team that discovered this amphibian chytrid fungus that Kate was talking about just then, and just after we discovered that, I moved to New York and started working at CDC on a virus called Nipah virus, and back in the 90s when--it certainly is very interesting that diseases could emerge in wildlife and in humans, and then you're working at CDC, which is a multi-billion dollar institution, focused on this process of disease emergence, and we've got billions of dollars from NIH, CDC, World Health, Welcome, other places, putting to dealing with these diseases. And with some of those diseases like HIV where 65 million people have already been infected, 40 million people dead, some of the cost in one single outbreak between $50 and $100 billion globally, it's a huge economic cost, a huge mortality, and all the effort was put onto vaccines and drug development, and yet, there was so little understood about the process of emergence, and that's what really got me interested in trying to understand what drives emergence. We--we published a paper in 2000 in Science on emerging disease of wildlife, and we wanted to try and quantify where these diseases were, and it was just an unfathomable task, so I started to work with Kate and John Gittleman and Marc to see if we can try and get a handle on this, and I think what's--what really is important, the major step that we've managed to do is to link the list of all known emerging diseases in people to what caused their emergence, and that alone took us over a couple of years, and then correct for the bias. What Kate talked about there is to look at where people are looking for emerging diseases because that's where you're going to see more diseases emerge, and once you correct those biases, you start to see these hot spots, which are the true areas where diseases are going to emerge in the future, and I think that's a critical thing for dealing with this problem. So, what's exciting today, we've been able now to--or we will be able to move on from waiting for these diseases to emerge and being surprised at them every time they emerge, and seeing hundreds of thousands of people dying and billions of dollars to the global economy to actually dealing within the herd of the game, and that's my interest now is to say, "Can we get people to take this ecological approach to predicting disease emergence and then move out to the areas, these hot spots, and start to look for new pathogens. So, one of the things we're doing at Wildlife Trust is we're going to choose a site around the world where we look at wildlife, we look at wildlife for conservation reasons, we look at wildlife for emerging disease reasons. We're working on SARS, Nipah virus, West Nile virus. Can we now take samples from those animals in the hot zones, inside these emerging disease hot spots, and look for new pathogens and say, "Are they going to be the next HIV or the next SARS?" And I think this predictive model, although it's very early and it's not absolutely perfect yet, at least it gives us a way forward to start to allocate our resources, and if you look at a group like World Health, for example, World Health Organization, who specifically target areas for surveillance, how have they done that in the past purely on intuition. Well, now we've got a tool that we can actually use to target their resources better, and in a world with a limited economy, that's a very valuable thing to do. So, I think that that's one of the major messages out of the paper, as well as the point that, you know, it's not just the zoonoses in the tropics. It's also us, and I think it brings it right back home when you look at the hot spot maps for the different types of pathogens. You know, Europe and North America still are hot spots for some diseases, and we're talking here about food-borne infections and drug-resistant microbes so we get a lot of emerging diseases related to food and drug resistance. Why is that? Well, it's because we are the country that can afford intensification of agriculture the most and development of antibiotic drugs the most. So, I think we also have to look at diseases as a sort of cost of doing business globally. If we're going to develop areas and regions, one of the potential outcomes of that could be an emerging disease, and I think we can also use this approach to sort of predict where we're going to get into problems when we start to develop regions. Thanks.
>> Katherine Anderson: OK. Thank you. Marc Levy.
>> Marc Levy: Hi. Thank you. Our group at CIESIN specializes in understanding the affects of global environment change. We do global environmental modeling, and our focus is mainly looking at human activity as a driver of global change and also at looking at the consequences of global change on human well-being, and our chief tool for understanding these things has been using geographically precise databases of human activity and human impact. So, our most prime example of that is the gridded population of the world dataset, which was used to geo-reference human location for use in the modeling results that are reported here. So, we've been able to bring the 15 years or so of work that we've done in all these spatial human datasets to bring to bear on this particular problem. So, this kind of work is especially important now because of all the different types of global change that are going on, that are reaching unprecedented magnitudes, and competing for attention. Many of these changes, you know, potentially are going to generate catastrophic changes and people are desperate to better understand, you know, what the actual implications are. You know, we have human population growth going up by about an additional three billion people, we're converting the landscape at unprecedented rates, we're disturbing the global water cycle, and all these things are affecting people but we're -- we don't have lots of precise answers on what it all adds up to, and many of the most worrisome possibilities are fairly complex and those have been, you know, the most difficult to understand even though they're potentially the most important. So, the results in this article are especially promising for me because it's an example of taking data on global change, you know, population location, population growth, the distribution of biodiversity and so on, and then relating that to a fairly complex (inaudible) emergence of infectious diseases and improving our ability to understand. So, we're taking, for example, you can overlay the map of where the zoonotic wildlife diseases have emerged, and you can add to that map where the people are, where the animals are, where the population growth has been bigger, and you can understand the pattern. You can relate these different changes together. So, that's the first step towards understanding and predicting, and it's often quite difficult in this field, and so for me, this is really promising that we've been able to actually put some robust order on this complex pattern. A couple of things that are related to other dimensions of global change that our results are also relevant for is the big spike of diseases in the 1980s we suspect is related to the emergence of HIV/AIDS which became pandemic during that decade, and reduced an increased vulnerability to a range of new diseases that emerged during that decade such as Kaposi's sarcoma, toxoplasmosis and so on. And then, finally, the other big change that obviously on everybody's mind these days is climate change. Our results, per se, don't shed a lot of light on climate change because we're unable to pull together the right information to do that in this particular work. We're trying to do that in the next work, however, it is suggestive that the increase in vector-borne diseases in the 1990s was a decade when there was an unusually high number of El Nino events indicating a great deal of climatic variability compared to normal, and this is the kind of relationship one would expect, that when climatic variability goes up, you get habitat changes and vectors relocating and that can increase vulnerability of emergence for new diseases. So, in sum for me, this is a very promising result that shows the benefits of approaching complex phenomena through a systematic global change modeling approach. Thank you.
>> Katherine Anderson: Thank you, and to finally, Professor John Gittleman.
>>John Gittleman: Well, the primary results in this paper, I think, have been emphasized and talked about eloquently already. I--my view is to step back a bit and to look at how, you know, people might view this work, and I think of the car bumper sticker "Think Globally and Act Locally," and everyone can sort of relate to that, but the issue is, as Kate and Peter and Marc have just said, it's very, very difficult to think globally, and one of the reasons for that is that until very recently we simply have not had the comprehensive databases and really the statistical methods to tease apart and to look at informed way at these patterns. Right now we do have databases. The paper here emphasizes infectious diseases and what's emerging in humans and we can look at this and sort of dig ecological time and spatial scales. As Marc mentioned, this is extremely important right now because we do know that there are many, many interconnected patterns that when we look at infectious disease, human population density, the extinction risk, and biodiversity species, and global climate change, we do see interconnected patterns, but it's only been fairly recently that we can really get full databases to see the degree to which there are significant interconnections, and as Kate mentioned, that we can identify the processes that are influencing these patterns. So, where we are right now is that for the first time in studying the ecology of this planet, that we can pull together the perspectives and the methods from different areas. In this paper, we're looking at patterns of infectious disease, ecology, and indeed, conservation, and this helps us in understanding a lot of the processes that are driving fundamental core global changes on this planet, so this is very, very exciting, I mean, not only for understanding but indeed for predicting some of the problems and the solutions in the future. There are a couple of things that I would like to emphasize. One is that we are seeing a very, very close relationship between changes in biodiversity and the possibility in the areas of emerging infectious disease. So, what that says is that institutions, both federal and non, that have been looking at disease need to think much more carefully about wildlife populations and what's going on there. I'm really tickled and pleased that the CDC is looking more and more at ecological context of disease, and the other is that we need to think about what particular areas are really critical to invest our time and attention into. Again, in stepping back, I think that what we're getting is a much more careful precise model for predicting change that's occurring on this planet. So, change with regard to species, infectious disease, and indeed the welfare of the humans, and this is a really nice example of how we've taken, over a long period of time, ways of collecting more and more comprehensive databases and seeing that once you do pull this information together that it can be used in a very, very effective manner. Thank you.
>> Katherine Anderson: OK. Thanks very much to all speakers. Now we'll go to questions from the phones.
>> Coordinator Phil: Thank you, Katherine. Good afternoon, ladies and gentlemen. It's Phil, your operator, speaking again. We will now proceed to a question and answer session. If you wish to ask a question, please press 7 on your telephone keypad. If you change your mind and want to withdraw your question, please press 7 again. All questions will be answered in the order received and you will be requested by name when to ask your question. Again, please press 7 on your telephone keypad if you wish to ask a question. And our first question comes from the line of Mark N. Ritter from the Associated Press. Please go ahead, Mr. Ritter.
>> Mark Ritter: Hi. Thank you very much. One question about the past, and one question about the future, if I may. What is--can you just summarize why the number of EIDs has gone up every decade, and as for the future, can you just summarize again how you came up with the hot spots. I mean, you didn't just go from history. You used some other factors, some other intervening factors. Those are my two questions.
>> Dr. Peter Daszak: OK. I'll take the first one. Peter Daszak speaking. We don't know for sure why the number of emerging diseases has gone up every decade, but to me, it's pretty obvious. When you look at the correlations in our paper, one of the clear findings is that emerging diseases are driven by human factors. It's changes to demography, it's changes to the environment, it's the things that we do to the planet that drive disease emergence. You know, we intensify agriculture, we'll get an infectious disease in food animals like mad cow disease or E coli in spinach. When we move into a tropical rain forest, we get a new disease from bushmeat like HIV/AIDS. So, all of those factors, all the anthropogenic factors have increased over the last few decades so to me, it goes back to our message. This is simply a product of us doing business globally as a species, and the sooner we realize that, the sooner we're going to be able to deal with this ahead of time and stop the situation from getting worse.
>> Dr. Kate Jones: So, I can take the second question, if that's OK. Kate Jones from ZSL. So, how we did the hot spot maps was we first looked at the spatial patterns so we were mapping how many actual events were in one group spread across the planet so the maps that maybe you can see that you have in the paper, if you can have it in front of you, have a bunch of red dots on them to show you how many and which areas are emerging. Now, that's just the pattern. What we've done and is important is we've gone a step beyond that to think about the processes. So, in our statistical model, we looked at the association of the incidence of these emerging diseases -- emerging disease events and collate it with a set of global spatial variables, human impact to measure the population density, human growth, the environment. We measured latitude and the rainfall ecology which we measured as a density of other wildlife. So, then we established the relationship with those factors and then we were able to spatially map out the relationship between that so that basically means it gives you a likelihood of where we would expect an emerging infectious disease to occur based on their relationship with those other drivers. Does that answer your question?
>> Mark N. Ritter: Yes. Thank you very much.
>> Coordinator Phil: This is the operator speaking. Our next question comes from the line of Richard Ingham from the AFP French News Agency. Please go ahead, Mr. Ingham.
>> Richard Ingham: Thank you very much. The question which I have is looking to the future, what is the--which region and hopefully which country do you think represents the biggest risk of zoonotic conservation? In other words, where do you see this risk of transmission from wildlife to humans because of human population growth and proximity to wild animals?
>> Katherine Anderson: Marc, please take that.
>> Marc Levy: Yeah, sure. The figure in the article that addresses that question is Figure 3A and Figure 3B, but I think Figure 3A is the one that is most relevant potentially which shows the risk of an EID, of an emerging infectious disease, from wildlife and it tracks relatively heavily the areas of high population density and population growth, but magnified by the current levels of potential hosts of biodiversity, and so the areas that are potentially somewhat surprising there would be the whole east Asia region, the Indian subcontinent, the Niger delta, the Great Lakes region in Africa, as well as the historic hot spots of western Europe and the big population centers in North America. It's western Europe, North America, Japan that have historically generated the most reports of diseases, but when we look at the drivers, we are saying that the risks are extremely high for new ones in these other areas, in east Asia, Indian subcontinent, these parts of Africa as well as smaller areas. That Figure 3A is the most direct answer to your question.
>> Dr. Kate Jones: But there are different patterns--Kate Jones, sorry. There are different patterns depending on the different types of EID events as well so the drug-resistant EID events have a different spatial pattern. Marc, do you want to talk about that as well?
>> Marc Levy: Well, I thought the question was mainly about the wild--the zoonotic.
>> Dr. Kate Jones: Oh, OK.
>> Marc Levy: But, yeah, that Figure 3 breaks things about by types of EIDs.
>> Richard Ingham: Great. Thank you very much.
>> Coordinator Phil: Thank you, Mr. Ingham. Our next question comes from the line of Roger Highfield of the Daily Telegraph. Please go ahead, Mr. Highfield.
>> Roger Highfield: Thank you very much. Yes, I just really wanted to ask you about the map of the wildlife zoonotices and the drug-resistant hot spots. I noticed that I seem to be sitting in one in London and I wondered if you could just talk me through a little bit about the taking a rather parochial line, you know, the British sort of perspective on being a hot spot in both types of disease. No one wants to offend, Dwighty? That's right. I'm actually in fear for my life, guys. Come on.
>> Dr. Peter Daszak: There are a couple of -- if you look at the database, there's some diseases that have been emerged due to drug resistance in London and in hospitals across the UK, and you know, we only have to look at some zoonoces, you know, to think of mad cow disease as an example of a new pathogen emerging from animals, from non-human animals. We've got a whole stack of food-borne infections like the famous salmonella in eggs in the 80s that are in the database. So that's why England is showing up as a hot spot.
>> Roger Highfield: I suppose we really -- I mean, I'm obviously aware of that, but I wondered if you just talked to the factors, and I presume it's a combination of sort of factory farming methods and a high population density.
>> Dr. Peter Daszak: It's absolutely right, and it's three things. It's high population density, factory farming, and antibiotic drug use, and the factory farming is more than just factory farming. It's also centralization of agriculture so if you think back to, say, foot and mouth disease or some of the E colis, it's farmers bringing the cattle for slaughter in more centralized areas so you can get cattle from a wide range, wide geographic range, and across the UK, being slaughtered and processed in one place and it's a good chance for a pathogen to spread amongst the meat and get shipped across to various other places. So, you know, the message isn't doom and gloom here. The message is good in a way. You know, we were able to target that problem now because we know that there really is a hot spot, so what should we do? We should now be looking more carefully at every time we intensify agriculture, we should start planning out for some potential emerging diseases and increase our surveillance in them. Let's stop waiting for them to happen and being surprised. I mean, there's no surprise now. It's right there in front of you with a bright red spot on the UK.
>> Roger Highfield: Great. Thanks.
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