# Ecology and Evolution of Infectious Disease, 2013

I am recently back from the Ecology and Evolution of Infectious Disease (EEID) Principal Investigators' Meeting hosted by the Odum School of Ecology at the University of Georgia in lovely Athens. This is a remarable event, and a remarkable field, and I can't remember ever being so energized after returning from a professional conference (which often leave me dismayed or even depressed about my field). EEID  is an innovative, highly interdisciplinary funding program jointly managed by the National Science Foundation and the National Institutes of Health. I have been lucky enough to be involved with this program for the last six years. I've served on the scientific review panel a couple times and am now a Co-PI on two projects.

We had a big turn-out for our Uganda team in Athens and team members presented no fewer than four posters. The Stanford social networks/human dimensions team (including Laura Bloomfield, Shannon Randolph and Lucie Clech) presented a poster ("Multiplex Social Relations and Retroviral Transmission Risk in Rural Western Uganda") on our preliminary analysis of the social network data. Simon Frost's student at Cambridge, James Lester, presented a poster ("Networks, Disease, and the Kibale Forest") analyzing our syndromic surveillance data. Sarah Paige from Wisconsin presented a poster on the socio-economic predictors of high-risk animal contact ("Beyond Bushmeat: Animal contact, injury, and zoonotic disease risk in western Uganda") and Maria Ruiz-López, who works with Nelson Ting at Oregon, presented a poster on their work on developing the resources to do some serious population genetics on the Kibale red colobus monkeys ("Use of RNA-seq and nextRAD for the development of red colobus monkey genomic resource").

Parviez Hosseini, from the EcoHealth Alliance, also presented a poster for our joint work on comparative spillover dynamics of avian influenza ("Comparative Spillover Dynamics of Avian Influenza in Endemic Countries"). I'm excited to get more work done on this project which is possible now that new post-doc Ashley Hazel has arrived from Michigan. Ashley will oversee the collection of relational data in Bangladesh and help us get this project into high gear.

The EEID conference has a unique take on poster presentations which make it much more enjoyable than the typical professional meeting. In general, I hate poster sessions. Now, don't get me wrong: I see lots of scientific value in them and they can be a great way for people to have extended conversations about their work. They can be an especially great forum for students to showcase their work and start the long process of forming professional networking. However, there is an awkwardness to poster sessions that can be painful for the hapless conference attender who might want, say, to walk through the room in which a poster session is being held. These rooms tend to be heavy with the smell of desperation and one has to negotiate a gauntlet of suit-clad, doe-eyed graduate students desperate to talk to anyone who will listen about their work. "Please talk to me; I'm so lonely" is what I imagine them all saying as I briskly walk through, trying to look busy and purposeful (while keeping half an eye out for something really interesting!).

The scene at EEID is much different. All posters go up at the same time and the site-fidelity of poster presenters is the lowest I have ever seen. It has to be since, if everyone stuck by their poster, there wouldn't be anyone to see any of them! What this did was allow far more mixing than I normally see at such sessions and avoid much of the inherent social awkwardness of a poster session. Posters also stayed up long past the official poster session. I continued to read posters for at least a day after the official session ended. Of course, it helps that there was all manner of great work being presented.

There were lots of great podium talks too. I was particularly impressed with the talks by Charlie King of Case Western on polyparasitism in Kenya, Maria Diuk-Wasser of Yale on the emergence of babesiosis in the Northeast, Jean Tsao (Michigan State) and Graham Hickling's (Tennessee) joint talk on Lyme disease in the Southeast, and Bethany Krebs's talk on the role of robin social behavior in West Nile Virus outbreaks. Laura Pomeroy, from Ohio State, represented one of the other few teams with a substantial anthropological component extremely well, talking about the transmission dynamics of foot-and-mouth disease in Cameroon. Probably my favorite talk of the weekend was the last talk by Penn State's Matt Thomas. They done awesome work elucidating the role of temperature variability on the transmission dynamics of malaria.

It turns out that this was the last EEID PI conference. Next year, the EEID PI conference will be combined with the other EEID conference which was originally organized at Penn State (and is there again this May). This combining of forces is, I'm sure, a good thing as it will reduce confusion and probably make it more likely that all the people I want to see have a better chance of showing up. I just hope that this new, larger conference retains the charms of the EEID PI conference.

EEID is a new, interdisciplinary field that has grown thanks to some disproportionately large contributions of a few, highly energetic people. One of the principals in this realm is definitely Sam Scheiner, the EEID program officer at NSF.  The EEID PI meeting has basically been Sam's baby for the past 10 years. Sam has done an amazing job creating a community of interdisciplinary scholars and I'm sure I speak for every researcher who has been heavily involved with EEID when I express my gratitude for all his efforts.

# On The Dilution Effect

A new paper written by Dan Salkeld (formerly of Stanford), Kerry Padgett (CA Department of Public Health), and myself just came out in the journal Ecology Letters this week.

One of the most important ideas in disease ecology is a hypothesis known as the "dilution effect". The basic idea behind the dilution effect hypothesis is that biodiversity -- typically measured by species richness, or the number of different species present in a particular spatially defined locality -- is protective against infection with zoonotic pathogens (i.e., pathogens transmitted to humans through animal reservoirs). The hypothesis emerged from analysis of Lyme disease ecology in the American Northeast by Richard Ostfeld and his colleagues and students from the Cary Institute for Ecosystem Studies in Millbrook, New York. Lyme disease ecology is incredibly complicated, and there are a couple different ways that the dilution effect can come into play even in this one disease system, but I will try to render it down to something easily digestible.

Lyme disease is caused by a spirochete bacterium Borrelia burgdorferi. It is a vector-borne disease transmitted by hard-bodied ticks of the genus >Ixodes. These ticks are what is known as hemimetabolous, meaning that they experience incomplete metamorphosis involving larval and nymphal stages. Rather than a pupa, these larvae and nymphs resemble little bitty adults. An Ixodes tick takes three blood meals in its lifetime: one as a larva, once as a nymph, once as an adult. At different life-cycle stages, the ticks have different preferences for hosts. Larval ticks generally favor the white-footed mouse (Peromyscus leucopus) for their blood meal and this is where the catch is. It turns out that white-footed mice are extremely efficient reservoirs for Lyme disease. In fact, an infected mouse has as much as a 90% chance of transmitting infection to a larva feeding on it. The larvae then molt into nymphs and overwinter on the forest floor. Then, in spring or early summer a year after they first hatch from eggs, nymphs seek vertebrate hosts. If an individual tick acquired infection as a larva, it can now transmit to its next host. Nymphs are less particular about their choice of host and are happy to feed on humans (or just about any other available vertebrate host).

This is where the dilution effect comes in. The basic idea is that if there are more potential hosts such as chipmunks, shrews, squirrels, or skunks, there are more chances that an infected nymph will take a blood meal on a person. Furthermore, most of these hosts are much less efficient at transmitting the Lyme spirochete than are white-footed mice. This lowers the prevalence of infection and makes it more likely that it will go extinct locally. It's not difficult to imagine the dilution effect working at the larval stage blood-meal too: if there are more species present (and the larvae are not picky about their blood meal), the risk of initial infection is also diluted.

In the highly-fragmented landscape of northeastern temperate woodlands, when there is only one species in a forest fragment, it is quite likely that it will be a white-footed mouse. These mice are very adaptable generalists that occur in a wide range of habitats from pristine woodland to degraded forest. Therefore, species-poor habitats tend to have mice but no other species. The idea behind the dilution effect is that by adding different species to the baseline of a highly depauperate assemblage of simply white-footed mice, the prevalence of nymphal infection will decline and the risk for zoonotic infection of people will be reduced.

It is not an exaggeration to say that the dilution-effect hypothesis is one of the two or three most important ideas in disease ecology and much of the explosion of interest in disease ecology can be attributed in part to such ideas. The dilution effect is also a nice idea. Wouldn't it be great if every dollar we invested in the conservation of biodiversity potentially paid a dividend in reduced disease risk? However, its importance to the field or the beauty of the idea do not guarantee that it is actually scientifically correct.

One major issue with the dilution effect hypothesis is its problem with scale, arguably the central question in ecology. Numerous studies have shown that pathogen diversity is positively related to overall biodiversity at larger spatial scales. For example, in an analysis of global risk of emerging infectious diseases, Kate Jones and her colleagues form the London Zoological Society showed that globally, mammalian biodiversity is positively associated with the odds of an emerging disease. Work by Pete Hudson and colleagues at the Center for Infectious Disease Dynamics at Penn State showed that healthy ecosystems may actually be richer in parasite diversity than degraded ones. Given these quite robust findings, how is it that diversity at a smaller scale is protective?

We use a family of statistical tools known as "meta-analysis" to aggregate the results of a number of previous studies into a single synthetic test of the dilution-effect hypothesis. It is well known that inferences drawn from small samples generally have lower precision (i.e., the estimates carry more uncertainty) than inferences drawn from larger samples. A nice demonstration of this comes from the classical asymptotic statistics. The expected value of a sample mean is the "true mean" of a normal distribution and the standard deviation of this distribution is given by the standard error, which is defined as the standard deviation of the distribution divided by the square root of the sample size. Say that for two studies we estimate the standard deviation of our estimate of the mean to be 10. In the first study, this estimate is based on a single observation, whereas in the second, it is based on a sample of 100 observations. The estimated of the mean in the second study is 10 times more precise than the estimate based on the first because $10/\sqrt{1} = 10$ while $10/\sqrt{100} = 1$.

Meta-analysis allows us to pool estimates from a number of different studies to increase our sample size and, therefore, our precision. One of the primary goals of meta-analysis is to estimate the overall effect size and its corresponding uncertainty. The simplest way to think of effect size in our case is the difference in disease risk (e.g., as measured in the prevalence of infected hosts) between a species rich area and a species poor area. Unfortunately, a surprising number of studies don't publish this seemingly basic result. For such studies, we have to calculate a surrogate of effect size based on the reported test statistics of the hypothesis that the authors report. This is not completely ideal -- we would much rather calculate effect sizes directly, but to paraphrase a dubious source, you do a meta-analysis with the statistics that have been published, not with the statistics you wish had been published. On this note, one of our key recommendations is that disease ecologists do a better job reporting effect sizes to facilitate future meta-anlayses.

In addition to allowing us to estimate the mean effect size across studies and its associated uncertainty, another goal of meta-analysis is to test for the existence of publication bias. Stanford's own John Ioannidis has written on the ubiquity of publication bias in medical research. The term "bias" has a general meaning that is not quite the same as the technical meaning. By "publication bias", there is generally no implication of nefarious motives on the part of the authors. Rather, it typically arises through a process of selection at both the individual authors' level and the institutional level of the journals to which authors submit their papers. An author, who is under pressure to be productive by her home institution and funding agencies, is not going to waste her time submitting a paper that she thinks has a low chance of being accepted. This means that there is a filter at the level of the author against publishing negative results. This is known as the "file-drawer effect", referring to the hypothetical 19 studies with negative results that never make it out of the authors' desk for every one paper publishing positive results. Of course, journals, editors, and reviewers prefer papers with results to those without as well. These very sensible responses to incentives in scientific publication unfortunately aggregate into systematic biases at the level of the broader literature in a field.

We use a couple methods for detecting publication bias. The first is a graphical device known as a funnel plot. We expect studies done on large samples to have estimates of the effect size that are close to the overall mean effect because estimates based on large samples have higher precision. On the other hand, smaller studies will have effect-size estimates that are more distributed because random error can have a bigger influence in small samples. If we plot the precision (e.g., measured by the standard error) against the effect size, we would expect to see an inverted triangle shape -- or a funnel -- to the scatter plot. Note -- and this is important -- that we expect the scatter around the mean effect size to be symmetrical. Random variation that causes effect-size estimates to deviate from the mean are just as likely to push the estimates above and below the mean. However, if there is a tendency to not publish studies that fail to support the hypothesis, we should see an asymmetry to our funnel. In particular, there should be a deficit of studies that have low power and effect-size estimates that are opposite of the hypothesis. This is exactly what we found. Only studies supporting the dilution-effect hypothesis are published when they have very small samples. Here is what our funnel plot looked like.

Note that there are no points in the lower right quadrant of the plot (where species richness and disease risk would be positively related).

While the graphical approach is great and provides an intuitive feel for what is happening, it is nice to have a more formal way of evaluating the effect of publication bias on our estimates of effect size. Note that if there is publication bias, we will over-estimate our precision because the studies that are missing are far away from the mean (and on the wrong side of it). The method we use to measure the impact of publication bias on our estimate of uncertainty formalizes this idea. Known as "trim-and-fill", it uses an algorithm to find the most divergent asymmetric observations. These are removed and the precision of the mean effect size is calculated. This sub-sample is known as the "truncated" sample. Then a sample of missing values is imputed (i.e., simulated from the implied distribution) and added to the base sample. This is known as the "augmented" sample. The precision is then re-calculated. If there is no publication bias, these estimates should not be too different. In our sample, we find that estimates of precision differ quite a bit between the truncated and augmented samples. We estimate that between 4-7 studies are missing from the sample.

Most importantly, we find that the 95% confidence interval for our estimated mean effect size crosses zero. That is, while the mean effect size is slightly negative (suggesting that biodiversity is protective against disease risk), we can't confidently say that it is actually different than zero. Essentially, our large sample suggests that there is no simple relationship between disease risk and biodiversity.

On Ecological Mechanisms One of the main conclusions of our paper is that we need to move beyond simple correlations between species richness and disease risk and focus instead on ecological mechanisms. I have no doubt that there are specific cases where the negative correlation between species richness and disease risk is real (note our title says that we think this link is idiosyncratic). However, I suspect where we see a significant negative correlation, what is really happening is that some specific ecological mechanism is being aliased by species richness. For example, a forest fragment with a more intact fauna is probably more likely to contain predators and these predators may be keeping the population of efficient reservoir species in check.

I don't think that this is an especially controversial idea. In fact, some of the biggest advocates for the dilution effect hypothesis have done some seminal work advancing our understanding of the ecological mechanisms underlying biodiversity-disease risk relationships. Ostfeld and Holt (2004) note the importance of predators of rodents for regulating disease. They also make the very important point that not all predators are created equally when it comes to the suppression of disease. A hallmark of simple models of predation is the cycling of abundances of predators and prey. A specialist predator which induces boom-bust cycles in a disease reservoir probably is not optimal for infection control. Indeed, it may exacerbate disease risk if, for example, rodents become more aggressive and are more frequently infected in agonistic encounters with conspecifics during steep growth phases of their population cycle. This phenomenon has been cited in the risk of zoonotic transmission of Sin Nombre Virus in the American Southwest.

I have a lot more to write on this, so, in the interest of time, I will end this post now but with the expectation that I will write more in the near future!

# New Publication, Emerging infectious diseases: the role of social sciences

This past week, The Lancet published a brief commentary I wrote with a group of anthropologist-collaborators. The piece, written with Craig Janes, Kitty Corbett, and Jim Trostle, arose from a workshop I attended in lovely Buenos Aires back in June of 2011. This was a pretty remarkable meeting that was orchestrated by Josh Rosenthal, acting director of the Division of International Training and Research at the Fogarty International Center at NIH, and hosted in grand fashion by Ricardo Gürtler of the University of Buenos Aires.

Our commentary is on a series of papers on zoonoses, a seemingly unlikely topic for about which a collection of anthropologists might have opinions. However, as we note in our paper, social science is essential for understanding emerging zoonoses. First, human social behavior is an essential ingredient in $R_0$, the basic reproduction number of an infection (The paper uses the term "basic reproductive rate," which was changed somewhere in production from the several times I changed "rate" to "number"). Second, we suggest that social scientists who participate in primary field data collection (e.g., anthropologists, geographers, sociologists) are in a strong position to understand the complex causal circumstances surrounding novel zoonotic disease spill-overs.

We note that there are some challenges to integrating the social sciences effectively into research on emerging infectious disease. Part of this is simply translational. Social scientists, natural scientists, and medical practitioners need to be able to speak to each other and this kind of transdisciplinary communication takes practice. I'm not at all certain what it takes to make researchers from different traditions mutually comprehensible, but I know that it's more likely to happen if these people talk more. My hypothesis is that this is best done away from anyone's office, in the presence of food and drink. Tentative support for this hypothesis is provided by the wide-ranging and fun conversations over lomo y malbec. These conversations have so far yielded at least one paper and laid the foundations for a larger review I am currently writing. I know that various permutations of the people in Buenos Aires for this meeting are still talking and working together, so who knows what may eventually come of it?

# This is Just What Greece Needs

Greece was officially deemed malaria-free in 1974. Recent reports, however, suggest that there is ongoing autochthonous transmission of of Plasmodium vivax malaria. According to a brief report from the Mediterranean Bureau of the Italian News Agency (ANSAmed), 40 cases of P. vivax malaria have been reported in the first seven months of 2012. Of these 40, six had no history of travel to areas known to be endemic for malaria transmission. The natural inference is thus that they acquired it locally (i.e., "autochthonously") and that malaria may be back in Greece.

More detail on the malaria cases in Greece can be found on this European Centre for Disease Prevention and Control website. The actual ECDC report on autochthonous malaria transmission in Greece can be found here. A point in that report that is not mentioned in the ANSAmed newswire is that 2012 marks the third consecutive year in which autochthonous transmission has been inferred in Greece. So much for Greece being malaria-free.

# Get Off the Sexual Network

When I was in Uganda last month, I was talking with collaborators, field assistants, villagers, taxi drivers, bartenders – pretty much anyone who would listen – about social networks, I was struck by what a sophisticated understanding of social networks my average interlocutor had.  As part of our project examining the risk of zoonotic disease spillover in rural Uganda, we are gathering data on individual people's personal networks. We are interested in contact networks, for sure, but we are also examining people's social capital – the resources to which an individual has access for instrumental action that are embedded in his or her social network. There are generally two classes of definitions of social capital used in the literature. The first, made famous by Robert Putnam's book, Bowling Alone, is really a measure of community solidarity. How cohesive are communities and how does this contribute to individuals' and communities' welfare?  The definition I typically employ is attributable to Bourdieau and a host of other scholars, especially Nan Lin. This definition emphasizes both the networked nature of social capital and the instrumentality of it.

The reasoning behind doing a social capital inventory in conjunction with our study of zoonotic disease spillover risk is to have a thorough description of the "state" of individuals. Social surveys typically measure income, household wealth, land holdings, etc. One measures such things in a social survey because one is interested in the economic state of the individual or household in which she is embedded. Social capital is a measure of economic – and social – well-being for people where many of the resources that they need to succeed, or even just get by, are not specifically located in the household or with the individual. We suspect that people in rural Uganda will vary in the amount of social capital they have and that this may be a major axess of vulnerability.

So, there I am, talking to anyone who would listen about the best way to gather information on personal social networks and it turns out that everyone I spoke with was amazingly familiar with the whole concept of social networks. The catch is, the networks with which they are familiar are a special type of networks – sexual networks. When I asked how everyone seemed to know so much about sexual networks, they pointed me to a public-service advertising campaign for which the tag line is "get off the sexual network." Despite the Central African origin of HIV-1, Uganda was an early center for the epidemic. However, as noted by Stoneburner and Lowbeer, in their important 2004 paper, Uganda experienced substantial – and early – decline in HIV-1 incidence because of health communication through social networks. They write:

The response in Uganda appears to be distinctively associated with communication about acquired immunodeficiency syndrome (AIDS) through social networks. Despite substantial condom use and promotion of biomedical approaches, other African countries have shown neither similar behavioral responses nor HIV prevalence declines of the same scale. The Ugandan success is equivalent to a vaccine of 80% effectiveness. (Stoneburner & Lowbeer 2004)

I definitely need to check out the current state of the art to see if other countries in Sub-Saharan Africa have now experienced similar public health gains as a result of network-oriented interventions.

Based on my rather unsystematic sample, I'd say that this campaign has really worked raise people's understanding of relational interconnectedness.  I was not able to get a picture of the huge billboards on the Kampala-Entebbe Highway (because it was always dark when I drove by them) but the TV ad is available on youtube. On the one hand, this is really great (both for the obvious public health reasons and because people seem to have a good understanding of webs of social relations). On the other hand, it will probably mean we will need to work hard to clarify what types of networks we mean when we gather our network data.

Well, it certainly has been a while since I've written anything here. Life has gotten busy with new projects, new responsibilities, etc. Yesterday, I participated in a workshop on campus sponsored by the Woods Institute for the Environment, the Young Environmental Scholars Conference. I was asked to stand-in for a faculty member who had to cancel at the last minute. I threw together some rather hastily-written notes and figured I'd share them here (especially since I spoke quite a bit of the importance for public communication!).

The theme of the conference was "Environmental Policy, Behavior, and Norms" and we were asked to answer three questions: (1) What does doing normative research mean to you? (2) How do your own norms and values influence your research? (3) What room and role do you see for normative research in your field? So, in order, here are my answers.

What does doing normative research mean to you?

I actually don't particularly like the term "normative research" because it sounds a little too much like imposing one's values on other people. I am skeptical of the imposition of norms that have more to do with (often unrecognized) ideology and less about empirical truth – an idea that was later reinforced by a terrific concluding talk by Debra Satz. If I can define "normative" to mean with the intent to improve people’s lives, then OK.  Otherwise, I prefer to do "positive" research.

For me, normative research is about doing good science. As a biosocial scientist with broad interests, I wear a lot of hats. I have always been interested in questions about the natural world, and (deep) human history in particular. However, I find that the types of questions that really hold my interest these days are more and more engaged in the substantial challenges we face in the world with inequality and sustainability. In keeping with my deep pragmatist sympathies, I increasingly identify with Charles Sanders Pierce's idea that given the "great ocean of truth" that can potentially be uncovered by science, there is a moral burden to do things that have social value. (As an aside, I think that there is social value in understanding the natural world, so I don’t mean to imply a crude instrumentalism here.) In effect, there is a lot of cool science to be done; one may as well do something of relevance.  I personally have little patience for people who pursue racist or otherwise socially divisive agendas and cloak their work in a veil of  free scientific inquiry.  This said, I worry when advocacy interferes with intellectual fairness or an unwillingness to accept that one's position is not actually true.

I think that we are fooling ourselves if we believe that our norms somehow don't have an effect on our research.  Recognizing what these norms that shape your research – whether implicitly or explicitly – helps you manage your bias. Yes, I said manage. I'm not sure we can ever completely eliminate it. I see this as more of a management of a necessary trade-off, drawing an analogy between the practice of science and a classic problem in statistics, between bias and variance. The more biased one is, the less variance there is in the outcome of one’s investigation. The less bias, the greater the likelihood that results will differ from one’s expectations (or wishes). Recognizing how norms shape our research also deals with that murky area of pre-science: where do our ideas for what to study come from?

Some of the the norms that shape my own research and teaching include:

transparency: science works best when it is open. This places a premium on sharing data, methods, and communicating results in a manner that maximizes access to information. As a simple example, this norm shapes my belief that we should not train students from poor countries in the use of proprietary software (and other technologies) that they won't be able to afford when they return to their home countries when there are free or otherwise open-source alternatives.

fairness: this naturally includes a sense of social justice or people playing on an equal playing field, but it also includes fairness to different ideas, alternative hypotheses, the possibility that one is wrong. This type of fairness is essential for one's credibility as a public intellectual in science (particularly supporting policy), as noted eloquently in this interview with Dick Lewontin.

respect for people's ultimate rationality: Trying to understand the social, ecological, and economic context of people's decision-making, even if it violates our own normative – particularly market-based economic – expectations.

flexibility: solving real problems means that we need to be flexible in our approach, willing to go where the solutions lead us, learning new tools and collaborating. Flexibility also means a willingness to give up on a research program that is doing harm.

good-faith communication: I believe that there is no room for obscurantism in the academy of the 21st century. This includes public communication. There are, of course, complexities here with regard to the professional development of young scholars.  One of the key trade-offs for young scholars is the need for professional advancement (which comes from academic production) and activism, policy, and public communication. Within the elite universities, the reality is that neither public communication nor activism count much for tenure. However, as Jon Krosnick noted, tenure is a remarkable privilege and, while it may seem impossibly far away for a student just finishing a Ph.D., it’s not really. Once you prove that you have the requisite disciplinary chops, you have plenty of time to to use tenure for what it is designed for (i.e., protecting intellectual freedom) and engaging in critical public debate and communication.

humility: solving problems (in science and society) means caring more about the answer to a problem than one's own pet theory. Humility is intimately related to respect for others' rationality.  It also means recognizing the inherently collaborative nature of contemporary science: giving credit where it is due, seeking help when one is in over one’s head, etc. John DeGioia, President of Georgetown University, quoted St. Augustine in his letter of support for Georgetown Law Student, Sandra Fluke against the crude attacks by radio personality Rush Limbaugh and I think those words are quite applicable here as well.  Augustine implored his interlocutors to "lay aside arrogance" and to "let neither of us assert that he has found the truth; let us seek it as if it were unknown to both." This is not a bad description of the way that science really should work.

What room and role do you see for normative research in your field?

I believe that there is actually an enormous amount of room for normative research, if by "normative research," we mean research that has the potential to have a positive effect on people's lives. If instead we mean imposing values on people, then I am less sure of its role.

Anthropology is often criticized from outside the field, and to a lesser extent, from within it for being overly politicized. You can see this in Nicholas Wade’s critical pieces in the New York Times Science Times section following the American Anthropological Association’s executive committee excising of the word "science" from the field’s long-range planning document. Wade writes,

The decision [to remove the word 'science' from the long-range planning document] has reopened a long-simmering tension between researchers in science-based anthropological disciplines — including archaeologists, physical anthropologists and some cultural anthropologists — and members of the profession who study race, ethnicity and gender and see themselves as advocates for native peoples or human rights.

This is a common sentiment. And it is a complete misunderstanding. It suggests that scientists can't be advocates for native peoples or human rights.  It also suggests that one can't study race, ethnicity, or gender from a scientific perspective.  Both these ideas are complete nonsense.  For all the leftist rhetoric, I am not impressed with the actual political practice of what I see in contemporary anthropology. There is plenty of posturing about power asymmetries and identity politics but it is always done in such a mind-numbingly opaque language and with no apparent practical tie-in to policies that make people's lives better. And, of course, there is the outright disdain for "applied" work one sees in elite anthropology departments.

Writing specifically about Foucault, Chomsky captured my take on this whole mode of intellectual production:

The only way to understand [the mode of scholarship] is if you are a graduate student or you are attending a university and have been trained in this particular style of discourse. That's a way of guaranteeing...that intellectuals will have power, prestige and influence. If something can be said simply, say it simply, so that the carpenter next door can understand you. Anything that is at all well understood about human affairs is pretty simple.

Ultimately, the simple truths about human affairs that I find anyone can relate to are subsistence, health, and the well-being of one’s children. These are the themes at the core of my own research and I hope that the work I do ultimately can effect some good in these areas.

# New Grant, Post-Doc Opportunity

Biological and Human Dimensions of Primate Retroviral Transmission
One of the great enduring mysteries in disease ecology is the timing of the AIDS pandemic. AIDS emerged as a clinical entity in the late 1970s, but HIV-1, the retrovirus that causes pandemic AIDS, entered the human population from wild primates many decades earlier, probably near the turn of the 20th century. Where was HIV during this long interval? We propose a novel ecological model for the delayed emergence of AIDS. Conceptually, in a metapopulation consisting of multiple, loosely interconnected sub-populations, a pathogen could persist at low levels indefinitely through a dynamic balance between localized transmission, localized extinction, and long-distance migration between sub-populations. This situation might accurately describe a network of villages in which population sizes are small and rates of migration are low, as would have been the case in Sub-Saharan Africa over a century ago.
We will test our model in a highly relevant non-human primate system. In 2009, we documented three simian retroviruses co-circulating in a metapopulation of wild red colobus monkeys (Procolobus rufomitratus) in Kibale National Park, Uganda, where we have conducted research for over two decades. We will collect detailed data on social interactions, demography, health, and infection from animals in a core social group.
We will also study a series of 20 red colobus sub-populations, each inhabiting a separate, isolated forest fragment. We will determine the historical connectivity of these sub-populations using a time series of remotely sensed images of forest cover going back to 1955, as well as using population genetic analyses of hypervariable nuclear DNA markers. We will assess the infection status of each animal over time and use viral molecular data to reconstruct transmission pathways.
Our transmission models will define the necessary conditions for a retrovirus to persist, but they will not be sufficient to explain why a retrovirus might emerge. This is because human social factors ultimately create the conditions that allow zoonotic diseases to be transmitted from animal reservoirs and to spread. We will therefore conduct an integrated analysis of the root eco-social drivers of human-primate contact and zoonotic transmission in this system. We will study social networks to understand how social resources structure key activities relevant to human-primate contact and zoonotic transmission risk, and we will explore knowledge, beliefs, and perceptions of human-primate contact and disease transmission for a broad sample of the population. We will reconcile perceived risk with actual risk through a linked human health survey and diagnostic testing for zoonotic primate retroviruses.
The ultimate product of our research will a data-driven set of transmission models to explain the long-term persistence of retroviruses within a metapopulation of hosts, as well as a linked analysis of how human social factors contribute to zoonotic infection risk in a relevant Sub-Saharan African population. Our study will elucidate not only the origins of HIV/AIDS, but also how early-stage zoonoses in general progress from "smoldering" subclinical infections to full-fledged pandemics.

I am thrilled to report that our latest EID project proposal, Biological and Human Dimensions of Primate Retroviral Transmission, has now been funded (by NIAID nonetheless!).  I will briefly describe the project here and then shamelessly tack on the full text of our advertisement for a post-doc to work as the project manager with Tony Goldberg, PI for this grant, in the College of Veterinary Medicine, University of Wisconsin, Madison.  This project will complement the ongoing work of the Kibale EcoHealth Project. The research team includes: Tony, Colin Chapman (McGill), Bill Switzer (CDC), Nelson Ting (Iowa), Mhairi Gibson (Bristol), Simon Frost (Cambridge), Jennifer Mason (Manchester), and me. This is a pretty great line-up of interdisciplinary scholars and I am honored to be included in the list.

Biological and Human Dimensions of Primate Retroviral Transmission

One of the great enduring mysteries in disease ecology is the timing of the AIDS pandemic. AIDS emerged as a clinical entity in the late 1970s, but HIV-1, the retrovirus that causes pandemic AIDS, entered the human population from wild primates many decades earlier, probably near the turn of the 20th century. Where was HIV during this long interval? We propose a novel ecological model for the delayed emergence of AIDS. Conceptually, in a metapopulation consisting of multiple, loosely interconnected sub-populations, a pathogen could persist at low levels indefinitely through a dynamic balance between localized transmission, localized extinction, and long-distance migration between sub-populations. This situation might accurately describe a network of villages in which population sizes are small and rates of migration are low, as would have been the case in Sub-Saharan Africa over a century ago.

We will test our model in a highly relevant non-human primate system. In 2009, we documented three simian retroviruses co-circulating in a metapopulation of wild red colobus monkeys (Procolobus rufomitratus) in Kibale National Park, Uganda, where we have conducted research for over two decades. We will collect detailed data on social interactions, demography, health, and infection from animals in a core social group.

We will also study a series of 20 red colobus sub-populations, each inhabiting a separate, isolated forest fragment. We will determine the historical connectivity of these sub-populations using a time series of remotely sensed images of forest cover going back to 1955, as well as using population genetic analyses of hypervariable nuclear DNA markers. We will assess the infection status of each animal over time and use viral molecular data to reconstruct transmission pathways.

Our transmission models will define the necessary conditions for a retrovirus to persist, but they will not be sufficient to explain why a retrovirus might emerge. This is because human social factors ultimately create the conditions that allow zoonotic diseases to be transmitted from animal reservoirs and to spread. We will therefore conduct an integrated analysis of the root eco-social drivers of human-primate contact and zoonotic transmission in this system. We will study social networks to understand how social resources structure key activities relevant to human-primate contact and zoonotic transmission risk, and we will explore knowledge, beliefs, and perceptions of human-primate contact and disease transmission for a broad sample of the population. We will reconcile perceived risk with actual risk through a linked human health survey and diagnostic testing for zoonotic primate retroviruses.

The ultimate product of our research will a data-driven set of transmission models to explain the long-term persistence of retroviruses within a metapopulation of hosts, as well as a linked analysis of how human social factors contribute to zoonotic infection risk in a relevant Sub-Saharan African population. Our study will elucidate not only the origins of HIV/AIDS, but also how early-stage zoonoses in general progress from "smoldering" subclinical infections to full-fledged pandemics.

Post Doctoral Opportunity

The Goldberg Lab at the University of Wisconsin-Madison invites applications for a post-doctoral researcher to study human social drivers of zoonotic disease in Sub-Saharan Africa.   The post-doc will be an integral member of a new, international, NIH-funded project focused on the biological and human dimensions of primate infectious disease transmission in Uganda, including social drivers of human-primate contact and zoonotic transmission.  This is a unique opportunity for a post-doctoral scholar with training in the social sciences to study human-wildlife conflict/contact and health and disease in a highly relevant ecological setting.  The following criteria apply.

1. Candidates must have completed or be near to completing a PhD in the social sciences, in a discipline such as anthropology, geography, sociology, behavioral epidemiology, or a relevant discipline within the public health fields.
2. Candidates must have a demonstrated interest in health and infectious disease.
3. Candidates must have prior field experience in Sub-Saharan Africa.
4. Candidates must be willing to relocate to Madison, Wisconsin for three years.
5. Candidates must be willing to spend substantial time abroad, including in Sub-Saharan Africa and at partner institutions in the United Kingdom.
6. Candidates must have experience with collection and analysis of both quantitative and qualitative data.  Familiarity with methods such as social network analysis, GIS, participatory methods, and survey design would be advantageous.

The successful candidate will help lead a dynamic international team of students and other post-docs in a multi-institutional, multidisciplinary project.  Duties involve a flexible combination of fieldwork, analyses, and project coordination, in addition to helping to mentor students from North America, Europe, and Africa.  The successful applicant will be expected to explore new research directions of her/his choosing, assisted by a strong team of collaborators.

University of Wisconsin-Madison is a top-notch institution for research and training in the social and health sciences.  Madison, WI, is a vibrant city with outstanding culture and exceptional opportunities for outdoor recreation.

Applicants should send a current CV, a statement of research interests and qualifications (be sure to address the six criteria above), and a list of three people (names, addresses, e-mails) who can serve as references.

Materials and inquiries should be sent to Dr. Tony L. Goldberg (tgoldberg@vetmed.wisc.edu).  Application materials must be received by September 12, 2011 for full consideration; the position is available starting immediately and requires a three-year commitment.

# A New Vector for Leishmania

It isn't every day that we learn about the discovery of an entirely new vector for an important vector-borne disease. A new report by the Australian Department of Agriculture and Fisheries has identified a new species of Leishmania that is transmitted by midges, not the usual vector, sandflies. Leishmania is a vector-borne protozoan parasite that causes an ulcerative disease known as Leishmaniasis or Kala-azar. Leishmaniasis is a disease primarily of the tropics and subtropics and is considered one of the most neglected infectious diseases in the world. The usual vectors are phlebotomine sandflies.

Australia (along with Antarctica) was thought to be the only continent free of Leishmania when locally-acquired infection was detected in kangaroos in Northern Territory in 2003.  Researchers investigating this infection thought that the local sandflies (Sergentomyia spp.) seemed highly unlikely vectors because they show a strong preference for feeding on reptiles. Indeed, screening for Leishmania in 3046 Sergentomyia sandflies yielded none infected with Leishmania. This led the researchers to expand the vectors tested. What they found was an unnamed species of day-feeding midge (Lasiohelea sp.) that was infected with a prevalence of up to 15 percent. This is the first identified vector for Leishmania that is not a phlebotomine sandfly. Not much is known about this midge.  The researchers were unable to find breeding sites, for example. The presence of prolegs on the midge larvae suggest that it is not aquatic but is terrestrial or semi-acquatic.  The authors suggest looking for midge breeding sites in the moist soil near water troughs where kangaroos drink.

Finding a totally new vector for a disease carries with it implications for eradication and control. One possibility raised by this work is that the difficulty some control programs have experienced may reflect the fact that Leishmania is being transmitted by multiple vectors. This is an hypothesis well worth investigating in areas other than Australia.

This work formed the basis of the Ph.D. dissertation for Annette Dougall at Charles Darwin University, Menzies School of Health Research.  Nice work, Annette!

# Measuring Epidemiological Contacts in Schools

I am happy to report that our paper describing the measurement of casual contacts within an American high school is finally out in the early edition of PNAS. Stanford's great social science reporter, Adam Gorlick, has written a very nice overview of our paper for the Stanford Report (also here in the LA Times and here on Medical News Today). The lead author, and general force of nature behind this paper, is Marcel Salathé, who until recently was a post-doc here at Stanford in Marc Feldman's lab.  This summer, Marcel moved to the Center for Infectious Disease Dynamics at Penn State, a truly remarkable place and now all the better for having Marcel.  From the Penn State end, there is a nice video describing our results as well as well as a brief note on Marcel's blog.  This paper has not been picked up quite like our paper on plague dynamics this summer, probably because measuring casual contacts in an American high school generally does not involve carnivorous mice.

With generous NSF funding, we were able to buy a lot of wireless sensor motes -- enough to outfit every student, teacher, and staff member at a largish American high school so that we could record all of their close contacts in a single, typical day. By "close contact," we mean any more-or-less face-to-face interaction within a radius of three meters.  As Marcel was putting together this project, we were (once again) exceptionally lucky to find ourselves at Stanford along with one of the world authorities on wireless sensor technology, Phil Levis, of Stanford's Computer Science department.  Phil and his students, Maria and Jung Woo Lee, made this work come together in ways that I can't even begin to fathom.  This actually leads me to a brief diversion to reflect on the nature of collaboration.  As with our plague paper or SIV mortality paper, this paper is one where collaboration between very different types of researchers (viz., Biologists, Computer Scientists, Anthropologists) is absolutely fundamental to the success of the work.  In coming up for tenure -- and generally living in an anthropology department -- the question of what I might call the partible paternity of papers (PPP) comes up fairly regularly. "I see you have a paper with five co-authors; I guess that means you contributed 17% to this paper, no?"  Well, no, actually.  I call this the "additive fallacy of collaboration." When a paper is truly collaborative, then the contributions of the paper are not mutually exclusive from each other and so do not simply sum.  To use a familiar phrase, the whole is greater than the sum of the parts.  Our current paper is an example of such a truly collaborative project.  Without the contributions of all the collaborators, it's not that the paper would be 17% less complete; it probably wouldn't exist. I can't speak particularly fluently to what Phil, Maria, and Jung Woo did other than by saying, "wow" (thus our collaboration), but I can say that we couldn't have done it without them.

I'll talk more about our actual results later.  For now, you'll either have to read the paper (which is open access), watch the video, or read the overview in the Stanford Report.

# Ah, Ape-Scat, Pleasing is the Fragrance of Your Perfumes

One of the fundamental ontological questions of our day is surely, "is there anything you can't do with ape scat?" Well, OK, this might be pushing it a bit far, but a recent article in the New York Times makes a pretty strong case for the blessings of this pungent goo.  My collaborator Beatrice Hahn, quoted in this article as saying that ape scat is "worth its weight in gold," has been collecting fecal samples gathered by far-flung ape researchers throughout Africa. In addition to providing fundamental data on the landscape-level distribution of SIV (the work on which I have collaborated with her), Beatrice's ape scat collection has now yielded the secret of the origin of Plasmodium falciparum, the most deadly of the five species that cause human malaria infection. The paper by Liu and colleagues appeared in the 23 September issue of Nature.  There is a nice accompanying piece by Eddie Holmes as well. It turns out that P. falciparum malaria spilled over into human populations from western gorillas, rather than from chimpanzees as had long been thought. Makes all that smelly collecting actually seem worthwhile...