monkey's uncle

notes on human ecology, population, and infectious disease

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Ebola Event at UCI: Planning, Not Panic

October 29th, 2014 · Infectious Disease

I am just back from an event at the University of California, Irvine organized by medical demographer Andrew Noymer. The event drew a big crowd, with probably 500-600 people in attendance.

There were five invited plenary speakers: Michael Buchmeier (UCI) spoke about the virology of Ebola and the Filovriuses more generally. Hearing Mike’s insights on the not one, but two vaccines for Ebola that have been shelved for a decade due to lack of interest was particularly illuminating. George Rutherford (UCSF) talked about the epidemiology of the current EVD epidemic and placed control efforts within the broader context of Global Health Initiatives. This is a guy with a ton of experience in global health and on the ground in Africa and his cool demeanor was calming for the crowd. Victoria Fan (Hawai’i) discussed the economic implications of the epidemic. Spoiler alert: they’re not good. Shruti Gohil (UCI Medical Center) talked about infection control in a hospital setting. Finally, I talked about the disease ecology, broadly construed, of Ebola. Following our talks, we got together as a panel and took questions for the audience.

Given the crazy hysteria surrounding the EVD epidemic and the arrival of a handful of cases in the United States, it was reassuring to participate in a couple hours of such sober, scientifically-informed discussion. Shruti’s insights as chief of infection control at the UCI medical center particularly struck me. She noted that Texas Health Presbyterian Hospital in Dallas, where the first American EVD case (Thomas Duncan) was treated, was clearly completely unprepared to handle an acute EVD case. Despite this, Shruti estimated that the attack rate of health care workers who attended to Duncan was about 4%. Not that horrible for an unprepared hospital. She also noted that no health care workers have become infected in the special units specifically designed to handle infectious diseases like EVD at Emory, Nebraska, and Bethesda. Planning, strict adherence to protocols, and personal protective gear work!

So, let’s summarize a bit about EVD in the US (these are the numbers as best as I can remember them, with citations where I can find them):

Number of cases of evacuated aid workers infected in Africa: 4

Number of deaths of evacuated aid workers infected in Africa: 0

Number of travel-associated cases in US: 4

Number of deaths of travel-associated cases in US: 1

Number of cases of American health care workers: 2

Number of deaths of American health care workers: 0

Note that the one death (Thomas Duncan) might have been prevented if he hadn’t been sent home from the emergency room and gotten so much sicker.

Another interesting point that Shruti made is that none of Duncan’s close personal contacts have contracted EVD and the 21-day window has now passed. The clear implication of all these data is that Ebola is not that infectious. It is controllable if we are prepared and follow protocols.

This gives me hope that we can control the EVD epidemic in West Africa if we were to decide to get serious about its control. But the international community needs to fight this epidemic where it is currently raging. This is clearly in the national interest of the United States and the collective interest of the international community. If we want to remain secure from EVD, we need to stop it where the epidemic continues to grow. World Bank President, and medical anthropologist extraordinaire, Jim Kim pulled out a great analogy in an interview on NPR on 17 October:

It’s like you’re in your room and the house is on fire, and your approach is to put wet towels under the door. That might work for a while, but unless you put the fire out, you’re still in trouble.

Let’s get over our fear, stop politicizing this crisis, stop demonizing the heroes. Let’s roll up our sleeves, get out our checkbooks, and bring a speedy end to this crisis.  Let’s put out the fire.

 

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Seriously, People, It's Selection, Not Mutation!

September 21st, 2014 · Evolution, Infectious Disease, science

I just read an excellent piece at Slate.com this morning by Benjamin Hale. He notes that the scariest, most insidious thing about Ebola Virus Disease is that the disease capitalizes on intimate contact for transmission. While diseases such as influenza or cholera are transmitted by casual contact, frequently to strangers, via aerosolized droplets (influenza) or fecally contaminated water (cholera). Caretakers, and especially women, are hit hard by EVD. Hale writes,

…the mechanism Ebola exploits is far more insidious. This virus preys on care and love, piggybacking on the deepest, most distinctively human virtues. Affected parties are almost all medical professionals and family members, snared by Ebola while in the business of caring for their fellow humans. More strikingly, 75 percent of Ebola victims are women, people who do much of the care work throughout Africa and the rest of the world. In short, Ebola parasitizes our humanity.

True, and tragic, enough. But this article falls prey to one of my biggest frustrations with the reporting of science, one that I have written about recently in the context of the current EVD epidemic ravaging West Africa.

In the list Hale presents of the major concerns about EVD, he notes: “The threat of mutation,” citing concern that Ebola virus might become airborne in a news report in Nature and the New York Times article that got me so worked up 10 days ago. Earlier this week, there was yet another longish piece in Nature/Scientific American that mentions “mutation” seven times but never once mentions selection. Or in another Nature piece,  UCSF infectious disease physician Charles Chiu is quoted: “The longer we allow the outbreak to continue, the greater the opportunity the virus has to mutate, and it’s possible that it will mutate into a form that would be an even greater threat than it is right now.” True, mutations accumulate over time. Not true, mutation alone will make Ebola virus a greater threat than it is now. That would require selection.

While the idea of airborne transmission of Ebola virus is terrifying, the development of the ability to be transmitted via droplet or aerosol would be an adaptation on the part of the virus. Adaptations arise from the action of selection on the phenotypic variation. Phenotypes with higher fitness come to dominate the population of entities of which they are a part. In the case of a virus such as Ebola virus, this means that the virus must make sufficient copies of itself to ensure transmission to new susceptible hosts before killing the current host or being cleared by the host’s immune system. While efficient transmission of EVD by aerosol or droplet would be horrible, equally horrible would be an adaptation that allowed it to transmit more efficiently from a dead host. It’s not entirely clear how long Ebola virus can persist in its infectious state in the environment. In a study designed to maximize its persistence (indoors, in the dark, under laboratory conditions), Sagripanti and colleagues found that Ebola virus can persist for six days. Under field conditions, it’s probably much shorter, but CDC suggests that 24 hours in a reasonably conservative estimate.

The lack of a strong relationship between host survival and pathogen transmission is why cholera can be so devastatingly pathogenic. The cholera patient can produce 10-20 liters of diarrhea (known as “rice water stools”) per day. These stools contain billions of Vibrio cholerae bacteria, which enter the water supply and can infect other people at a distance well after the original host has died. The breaking of the trade-off between host mortality and the transmissibility of the pathogen means that the natural break on virulence is removed and the case fatality ratio can exceed 50%. That’s high, kind of like the current round of EVD. Imagine if the trade-off between mortality and transmission in EVD were completely broken…

Changes in pathogen life histories like increased (or decreased) virulence or mode of transmission arise because of selection, not mutation, and this selection results from interactions with an environment that we are actively shaping. Sure, mutation matters because it provides raw material upon which selection can act, but the fact remains that we are talking primarily about selection here. Is this pervasive misunderstanding of the mechanisms of life the result of the war of misinformation being waged on science education in the US? I can’t help but think it must at least be a contributor, but if it’s true, it’s pretty depressing because this misunderstanding is finding its way to some of the world’s top news and opinion outlets.

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What Dinosaurs Teach Us About Approaching Stanford

September 18th, 2014 · Education

My wife, Libra Hilde, and I are resident fellows in a freshman dorm at Stanford. The RF residences are, shall we say, not quite as grand as the masters’ residences at Harvard (which have been know to get named in Top Five Lists of Apartments in Boston), but we fill a similar ceremonial role for our students that the masters at Harvard do. This means giving speeches to parents when students arrive and for important occasions like Parents’ Weekend.

Every year, the house staff (RFs and student staff) pick a theme and then decorate the dorm in anticipation of freshman arrivals. The standard Stanford gag is to pick a theme that somehow plays off the name of the house. These themes can be hilariously tenuous — that’s actually part of the gag — and some house names are easier to work with than others. I’m afraid we’re saddled with a particularly difficult name to play off of. We are Arroyo House. Our themes over the past few years have been: “Where the Wild Things Arroyo” (as in the classic Maurice Sendak book), “ATROYO” (an ancient Greek theme), and “Arroyosemite” (as in the National Park). After a long debate at our staff retreat, we finally decided on this year’s theme of “Dinosarroyo.” Lots of great decorating opportunities, as you can see from this picture of our common room.

Arroyo House LoungeA little game I play with myself in my ceremonial role of Arroyo House Resident Fellow is to welcome the parents with a brief speech on how our house theme relates to their kids’ careers at Stanford and beyond. Now bear in mind, we choose the theme on the basis of (1) how good a pun it makes with our house name (and we don’t have a lot to work with on that front!) and (2) the decoration possibilities it entails. How that theme fits into our larger vision is, frankly, pretty low on the list. This is what makes the game fun! After giving it a bit of thought, it occurred to me that Dinosarroyo actually has a lot to teach us. There are three big themes:

(1) College is about the spirit of discovery. Romantic tales of the expeditions of paleontologists such as Edward Drinker Cope or Roy Chapman Andrews of the American Museum of Natural History have inspired the early careers of countless scientists. Students’ experience at Stanford should inspire them to explore the boundaries of knowledge, whether they are future scientists, educators, lawyers, entrepreneurs, or whatever. Stanford students excel most when they eschew the easy path. This is a research university. Our students should take advantage of this and make new discoveries about the world. Embrace the spirt of discovery embodied by those romantic vertebrate paleontologists.

(2) The Dinosauria first appeared on Earth during the Triassic period and were the dominant form of animal life for over 135 million years. The age of the dinosaurs came to an abrupt end at the Cretaceous-Paleogene Boundary, about 65 million years ago. This 135 million years that dinosaurs dominated is approximately 100 times longer than anything recognizably human has been on the planet. In fact, what appears to us to be a geological ‘instant’ where the dinosaurs went extinct at the K-Pg boundary was, in fact, probably longer than humans have been in existence. That this mighty and diverse lineage of animals managed to die out in the blink of an evolutionary eye suggests to me that we should have some humility about our own dominion. Crucially, at this moment in human history we are faced with many enormous challenges, some of which are potentially existential. We should use the incredible opportunities that are afforded to us by our association with this incredible institution to address these challenges. Our society has given us so much to allow us to be here at this remarkable point in history. Let’s make the most of it!

(3) Those synapsid ancestors of mammals who managed to survive when all the (non-bird) dinosaurs went extinct give us a clue as to what our comparative advantage in this universe is. We are adaptable. We are opportunistic. Most remarkably of all, our particular lineage is blessed with the capacity for planning and foresight. We need to encourage our students to take advantage of the opportunities given them by this university to become adaptable lifelong learners. I can’t predict what the job market will look like in 10 years (and anyone who tells you they can is either fooling themselves or trying to sell you something). What I can say, is that it will be different than it is today. And the job market ten years beyond that will be even more different. This means that learning to be flexible, adaptable, and to never stop learning is probably the greatest ‘skill’ our students can learn.

 

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Selection is What Matters

September 12th, 2014 · Evolution, Infectious Disease

This has to be a quick one, but I wanted to go on the record is noting my frustration at the current concern that Ebola might “mutate” into something far worse, like a pathogen that is efficiently transmitted by aerosol. For example, Michael Osterholm wrote in the New York Times yesterday, “The second possibility is one that virologists are loath to discuss openly but are definitely considering in private: that an Ebola virus could mutate to become transmissible through the air.”  I heard Morning Edition host David Greene ask WHO Director Margaret Chan last week, “Is this virus mutating in a way that could be very dangerous, that could make it spread faster?”

I agree, Ebola Virus becoming more easily transmitted by casual contact would be a ‘nightmare scenario.’ However, what we need to worry about is not mutation per se, but selection! Yes, the virus is mutating. It’s a thing that viruses do. Ebola Virus is a Filovirus. It is composed of a single strand of negative-sense RNA. Like other viruses, and particularly RNA viruses, it is prone to high mutation rates. This is exacerbated by the fact that RNA polymerases lack the ability to correct mistakes. So mutations happen fast and they don’t get cleaned up. Viruses also have very short generation times and can produce prodigious copies of themselves. This means that there is lots of raw material on which selection can act, because variation is the foundation of selection. Add to that heritability, which pretty much goes without saying since we are talking about the raw material of genetic information here, and differential transmission success and voilà, selection!

And virulence certainly responds to selection. There is a large literature on experimental evolution of virulence. See for example the many citations at the linked to Ebert’s (1998) review in Science here. There are lots of different specific factors that can favor the evolution of greater or lesser virulence and this is where theoretical biology can come in and make some sense of things. Steve Frank wrote a terrific review paper in 1996, available on his website, that describes many different models for the evolution of virulence. Two interesting regularities in the the evolution of virulence may be relevant to the current outbreak of EVD in West Africa. The first comes from a model developed by van Baalen & Sabelis (1995). Noting that there is an inherent trade-off between transmissibility of a pathogen and the extent of disease-induced mortality that it causes (a virus that makes more copies of itself is more likely to be transmitted but more viral copies means the host is sicker and might die), they demonstrate that when the relative transmissibility of a pathogen declines, its virulence will increase. They present a marginal value theorem solution for optimal virulence, which we can represent graphically in the figure below. Equilibrium virulence occurs where a line, rooted at the origin, is tangent to the curve relating transmissibility to disease-induced mortality. When the curve  is shifted down, the equilibrium mortality increases. EVD is a zoonosis and it’s reasonable to think that when it makes the episodic jump into human populations, it is leaving the reservoir species the biology of which it is adapted to and entering a novel species to which it is not adapted. Transmission efficiency very plausibly would decrease in such a case and we would expect higher virulence.

Marginal Value Theorem

The second generality that may be of interest for EVD is discussed by Paul Ewald in his book on the evolution of infectious disease and (1998) paper. Ewald notes that when pathogens are released of the constraint between transmissibility and mortality — that is, when being really sick (or even dead) does not necessarily detract from transmission of the pathogen — then virulence can increase largely without bound. Ewald uses the difference in virulence between waterborne  and directly-transmitted pathogens to demonstrate this effect. At first glance, this seems to contradict the van Baalen & Sabelis model, but it doesn’t really. The constraint is represented by the curve in the above figure. When that constraint is released, the downward-sloping curve becomes a straight line (or maybe even an upward-sloping curve) and transmissibility continues to increase with mortality. There is no intermediate optimum, as predicted by the MVT, so virulence increases to the point where host mortality is very high.

A hemorrhagic fever, EVD is highly transmissible in the secretions (i.e., blood, vomit, stool) of infected people. Because these fluids can be voluminous and because so many of the cases in any EVD outbreak are healthcare workers, family members, and attendants to the ill, we might imagine that the constraints between transmissibility and disease-induced mortality on the Ebola Virus could be released, at least early in an outbreak. As behavior changes over the course of an outbreak — both because of public health interventions and other autochthonous adaptations to the disease conditions — these constraints become reinforced and selection for high-virulence strains is reduced.

These are some theoretically-informed speculations about the relevance of selection on virulence in the context of EVD. The reality is that while the theoretical models are often supported by experimental evidence, the devil is always in the details, as noted by Ebert & Bull (2003). One thing is certain, however. We will not make progress in our understanding of this horrifying and rapidly changing epidemic if all we are worried about is the virus mutating.

Selection is overwhelmingly the most powerful force shaping evolution. The selective regimes that pathogens face are affected by the physical and biotic environments in which pathogens are embedded. Critically, they are also shaped by host behavior. In the case of the current West African epidemic of EVD, the host behavior in question is that of many millions of people at risk, their governments, aid organizations, and the global community. People have a enormous potential to shape the selective regime that will, in turn, shape the pathogen that will infect future victims. This is what we need to be worrying about, not whether the virus will mutate. It saddens and frustrates me that we live in a country where evolution is so profoundly misunderstood that even our most esteemed, and otherwise outstanding sources of information and opinion don’t understand the way nature works and the way that human agency can change its workings for our benefit or detriment.

 

 

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Africa Is a Big Place

September 6th, 2014 · Uncategorized

Africa has been in the US news more than it usually is (which isn’t saying much) because of the ongoing outbreak of Ebola Virus Disease (EVD) in West Africa. One of the things that is always shocking when a new place appears in the news is the degree of geographic cluelessness of Americans. When it comes to Africa, my experience indicates that people generally greatly underestimate its size and, distressingly, sometimes don’t realize that Africa is actually a continent made up of over 50 sovereign states. Africa is, in fact, huge. It’s easy to underestimate its size, in large part, because of the projections we use to render a three dimensional space in two dimensions of a map. Most common projections compress the area of more equatorial regions and the African continent straddles the equator.

There is all sorts of anxiety about travel from African countries as a result of the EVD epidemic in West Africa. The deal is that the epidemic is localized to the far western portion of the continent.  Southern and eastern Africa, the destinations most likely to be visited by American tourists for example, are a long way from this part of the continent. While working on a paper with my colleague Simon Jackman today, I made an offhand comment about Freetown (Sierra Leone) probably being closer to Sao Paulo (Brazil) than it is to Nairobi (Kenya). Simon being Simon, said, “we can test that,” and he called up the wonderful Great Circle Mapper page. We figured out the distance from the Freetown to Nairobi airports, which turns out to be 3522 miles, and then plotted out a a circle with that radius centered on Freetown. The results can be seen here, and here is a screenshot of the resulting map:

 

Circle of radius 3522 mi (the distance from Freetown to Nairobi) centered on Freetown, Sierra Leone.

Circle of radius 3522 mi (the distance from Freetown to Nairobi) centered on Freetown, Sierra Leone.

So, what do you know, Sao Paulo is, in fact, closer to Freetown than Nairobi is. Cape Town and Johannesburg are outside the circle, but you know what’s in it? Pretty much all of western Europe. Of course, this doesn’t mean that Sao Paulo is socially closer to Freetown, but it is remarkable nonetheless. I just ran into this cool video of world air traffic on a 24-hour loop. One striking feature of this video is that there really isn’t much traffic between the corner of West Africa currently afflicted by EVD and just about anywhere in the world (including Nairobi!). Now, Nigeria would be a different story altogether. There are plenty of connections from Lagos or Port Harcourt to the rest of the world…

Along these lines of Africa being a big place, Kai Krause made this great graphic a few years ago showing the size of the African continent relative to a variety of other countries and other land masses.

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Quick and Dirty Analysis of Ebola

August 14th, 2014 · Infectious Disease, R

I've been traveling all summer while this largest Ebola Virus Disease (EVD) outbreak in recorded history has raged in the West African countries of Guinea, Sierra Leone, Liberia, and (worryingly) Nigeria. My peripatetic state has meant that I haven't been able to devote as much attention to this outbreak as I would like to. There is a great deal of concern -- some might say hysteria -- about EVD and the possibility that it may go pandemic. Tara Smith at least, on her Aetiology blog, has written something sensible, noting that EVD, while terrifying, is controllable with careful public health protective measures, as the historical record from Uganda shows. A recent post by Greg Laden got me to thinking about the numbers from the current EVD outbreak and what we might be able to learn.

EVD was the model disease for the terrible (1995) Dustin Hoffman movie, Outbreak. As we learned in the much more scientifically-accurate (2011) movie Contagion (which is based on an equally terrifying aerosolized Nipah virus), one of the key pieces of information regarding an epidemic is the basic reproduction number, R_0. The basic reproduction number tells us how many secondary infections are expected (i.e., on average) to be produced by a single, typical case at the outset of an epidemic before the pool of susceptible people has been depleted.  R_0 provides lots of information about epidemics, including: (1) the epidemic threshold (i.e., whether or not an epidemic will occur, which happens in the deterministic case when R_0 > 1), (2) the initial rate of increase of an epidemic, (3) the critical vaccination threshold (i.e., what fraction of the population you need to vaccinate to prevent an outbreak), (4) the endemic equilibrium of an infection (i.e., the fraction of the population that is infected in between outbreaks), and (5) the final size of the epidemic (i.e., the fraction of the total population that is ever infected when the epidemic is over).

Thus, for a novel outbreak, it's good to have an idea of R_0. I've been a bit out of the loop this summer and haven't seen any estimates so I figured that I would see what I could do. I fully realize that someone may have already done this and that I am not yet aware of it. I also recognize that, if someone has done this, they've probably done it better. This is a blog, not a peer-reviewed paper, and I am away from my usual resources, so please take this in the back-of-the-envelope spirit in which it is intended. I reserve the right to retract, etc. I will also post the R code that I used to make the calculations. I hope that this may prove helpful to others interested in the dynamics of outbreaks.

In their terrific (2003) paper on the SARS outbreak, Marc Lipsitch and colleagues provided a method for estimating the reproduction number from outbreak data. Note that this is a more generalized reproduction number, which we call R, than is the basic reproduction number, R_0. The key difference is that a reproduction number can be calculated at any point in an outbreak, whereas R_0 is only technically correct at the outset (the zero index in R_0 indicates the "generation" of the outbreak where "0" refers to the index case, a.k.a., "patient zero"). I've simply used the count of total cases from this week. It is straightforward to extend the calculation to previous counts. I haven't yet had a chance to do this because there is no convenient collection of data that I can find with my current access constraints.

The method involves equating R_0 for a simplified SEIR system to the observed rate of increase of the outbreak at some point in time t, using the fact that the reproduction number is approximately equivalent to the growth rate of the epidemic. See the supplementary information from Lipsitch et al. (2003) for details of the method. In brief, we calculate the dominant eigenvalue of the linearized SEIR model, for which it is straightforward to write an analytical formula, and equate this to log[Y(t)]/t, the empirical growth rate of the epidemic (where Y(t) is the cumulative number of cases at time t). Lipsitch et al. (2003) note that using the standard formula for the characteristic equation of the eigenvalues of the linearized SEIR model, we can solve for the reproduction number as:

 R = 1 + V \lambda + f(1-f) (V \lambda)^2,

where V is the serial interval (i.e., the summed duration of the incubation period, L, and the duration of the infectious period, D), \lambda is the positive root of the characteristic equation which we set equal to \log[Y(t)]/t, and f is the ratio of the infectious period of the serial interval.

I got the case data from the weekly WHO outbreak report for 11 August 2014. For this week Y(t)=1848. For the start time of the epidemic in the currently afflicted countries, I used the date of 10 March 2014, taken from this week's NEJM paper by Blaize et al. (2014). For the serial interval data, I used the values provided by the Legrand et al. (2007). Because Legrand et al. (2007) provide mean values of the relevant parameters -- and this is a different epidemic -- I used a variety of values for D and L to calculate R. It turns out that it doesn't matter all that much; the estimates of R are pretty stable.

I plot the values of R against the duration of the latent period. The different lines are for the different values of the duration of infectiousness. R increases with both. What we see is that at this point in the epidemic at least, R ranges from around 1.3 to 2.6, depending on specifics of the course of the disease. This is not all that high -- about the same as various flavors of influenza and considerably less than, say, pertussis. This is good news for potential control, if we could just rally some more international support for control of this serious infection...

Ebola-R0-plot1

 

Here is the R code for doing the calculations and creating this figure:

R:
  1. library(lubridate)
  2. # number of cases as of 11 August 2014
  3. # http://www.who.int/csr/don/2014_08_11_ebola/en/
  4. cases <- 1848
  5.  
  6. # start of epidemic in Guinea: 10 March 2014
  7. # Blaize et al. (2014), NEJM. DOI: 10.1056/NEJMoa1404505
  8. s <- dmy("10-03-14")
  9. e <- dmy("11-08-14")
  10. t <- e-s
  11. # Time difference of 154 days
  12.  
  13. ## incubation period 2-21 days
  14. ## http://www.who.int/mediacentre/factsheets/fs103/en/
  15. ## duration of infectiousness: virus detected in of lab-infected man 61 days!
  16.  
  17. ## Legrande et al. (2007) use L=7 and D=10
  18. ## doi:10.1017/S0950268806007217
  19.  
  20. lambda <- log(cases)/t
  21.  
  22. ## From Lipsitch et al. (2003)
  23. ## lambda is the dominant eigenvalue of the linearized SEIR model
  24. ## V is the serial interval V = D + L
  25. ## D is duration infectious period, L is duration of latent period
  26. ## f is the ratio of the the infectious period to the serial interval
  27. ## to solve for R set the eigenvalue equal to the observed exponential growth rate of the epidemic log(Y(t))/t
  28. Rapprox <- function(lambda,V,f) 1 + V*lambda + f*(1-f)*(V* lambda)^2
  29.  
  30. RR <- matrix(0, nr=10, nc=10)
  31. L <- seq(3,12)
  32. D <- seq(5,14)
  33. for(i in 1:length(L)){
  34. for(j in 1:length(D)){
  35. RR[i,j] <- Rapprox(lambda,L[i]+D[j],D[j]/(L[i]+D[j]))
  36. }
  37. }
  38.  
  39. cols <- topo.colors(10)
  40.  
  41. png(file="Ebola-R0-plot1.png")
  42. plot(L, RR[1,], type="n", xlab="Duration of Incubation", ylab="Reproduction Number",ylim=c(1,2.5))
  43. for(i in 1:10) lines(L, RR[i,], lwd=2, col=cols[i])
  44. dev.off()

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On Genetics and Human Behavioral Biology

August 13th, 2014 · Anthropology, Evolution, Human Ecology

Nicholas Wade, former science reporter for the New York Times has written a book, A Troublesome Inheritance, in which he argues that large-scale societal differences (e.g., the existence of capitalist democracies in the West or of paternalistic, authoritarian political systems in Asia) may be attributable to small genetic differences that were fixed at a population level through the action of natural selection since the emergence of anatomically modern humans and their subsequent dispersal from Africa. The fixation of these gene variants happened because the continents of Europe, Asia, and Africa (homes of the major "racial" groups) differed in systematic ways. David Dobbs recently reviewed it in the Sunday Review of Books, which prompted a kind of amicus brief letter-to-the-editor from over 120 population geneticists, affirming that Wade's writing misrepresents the current science of genetics. A full list of the signatories of this letter can be found here. It is a veritable who's who of contemporary population genetics.

As you might imagine, A Troublesome Inheritance has been quite controversial. A great deal has already been written on this book, both in formal publications and in the science (and economics) blogging ecosystem. To name just a few, Greg Laden, my old homie and fellow TF for Irv DeVore's famous Harvard class, Science B-29, Human Behavioral Biology, wrote a brief review here for American Scientist. Columbia statistician and political scientist, Andrew Gelman, wrote a review for Slate.com. Notre Dame professor and frequent contributor of popular work on human evolution, Agustin Fuentes, wrote a critique for Huffington Post, while UNC-C anthropology professor Jonathan Marks wrote a critique for the American Anthropological Association blog, which also appears in HuffPo.

Honestly, I think that Wade's book is so scientifically weak and ideological (despite his protestations that science should be apolitical) that it is likely to have a very short half-life in contemporary discourse on human diversity and science more broadly. In fact, I have advocated to the editorial boards of professional societies to which I belong not to do anything special about this book since I'm confident it will be soon forgotten for its sheer scientific mediocrity. I find it interesting that the great majority of the people who like the book seem not to be scientists but comment on Wade's "bravery" for spurning "political correctness" and the like. There are substantial parallels here to public debate over climate change or vaccination: the professional conclusions of the scientists who actually work on the topic only matter when they correspond with the social, political, or economic interests of the parties engaging in the debate. What do geneticists know about genetics anyway? So, it is with some hesitancy that I write about it, but my colleagues' letter has reminded me of a larger beef I have with the contemporary state of human evolutionary studies. This beef boils down to the fact that most contemporary students of human evolutionary biology know next to nothing about genetics. I've actually encountered a number of leading figures in human behavioral biology who maintain an outright hostility toward genetics. This is a topic that my colleague Charles Roseman and I have grumbled about for a few years now. We keep threatening to do something about it, but haven't quite gotten around to it yet. Perhaps this is a humble start...

This state of affairs is extremely problematic since genetics is the material cause (in the Aristotelean sense) or one of the mechanistic causes (in the Tinbergian sense) of much of the diversity of life. If we are going to make a scientific claim that some observed trait is the result of natural selection, we should be able to have a sense for how such a trait could evolve in the first place. The standard excuse for ignoring genetics in the adaptive analysis of a trait of interest is what Alan Grafen termed the "phenotypic gambit." The basic idea behind the phenotypic gambit is that natural selection is strong enough to overcome whatever constraints may be acting on it. The phenotypic gambit is a powerful idea and it has yielded some productive work in behavioral ecology. I use it. However, a complete evolutionary explanation of a trait's existence needs to consider all levels of explanation. In modern terms, and as nicely outlined a letter by Randolph Nesse, we need to answer questions about mechanism, ontogeny, phylogeny, and function. Explanations relying on the phenotypic gambit only address the functional question (i.e., fitness, or what Tinbergen called the "survival value" of the trait).

I could go on about this for a long time, so I will limit myself to three points: (1) complex traits will generally not be created by a single gene, (2) heritability and the response to selection are regularly misunderstood and misapplied, (3) we need to think about the strength of selection and the constancy of selective regimes when making statements about the adaptive evolution of specific traits.

First, we need to get over the whole one-gene thing. Among other things, the types of adaptive arguments that are made particularly for recent human behavioral innovations are simply highly implausible for single genes. There are a variety of formulae for calculating the time to fixation of advantageous alleles that depend on the particulars of the system (e.g., details about dominance, initial frequency, mutation rate). Using the approximation that the number of generations that it takes for the fixation of a highly advantageous allele with selection coefficient s is simply twice the natural logarithm of s divided by s, we can calculate the expected time to fixation for an advantageous allele. With a (very) substantial average selection coefficient of s=0.05 (think of lopping of 5% of the population each generation), the time to fixation of such a highly advantageous allele is about 120 generations generations. That's over 3,000 years for humans. This is interesting, of course, because it makes the type of recent evolution the John Hawks or Henry Harpending have discussed more than plausible. It makes it hard to imagine how the large changes in presumably complex behavioral complexes in historical time suggested by authors such as Wade or Gregory Clark, author of Farewell to Alms (which I actually find a fascinating book), pretty implausible.

In addition to the population-genetic implausibility of single-locus evolutionary models, complex traits are polygenic, meaning that they are constructed from multiple genes, each of which typically has a small effect. Now, this doesn't even address the issue of epigenetics, where genotype-environment interactions profoundly shape gene expression and can produce fundamentally different phenotypes in the absence of significant genetic difference, but that's another post. In many ways, this is good news for people who study whole organisms in a naturalistic context (like human behavioral ecologists!) because it means that we can work with quantitatively-measured trait values and apply regression models to understanding their dynamics. In short, the math is easier though, admittedly, the statistics can be pretty tricky. Further good news: there are lots of people who would probably be happy to collaborate and there are plenty of training opportunities in quantitative genetics through short courses, etc.

The masterful review paper that Marc Feldman and Dick Lewontin wrote for Science in 1975 amid the controversy surrounding Arthur Jensen's work on the genetics of intelligence, and its implications for racial educational achievement differentials, still applies. Heritability is a systematically misunderstood concept and its misuse seems to surface in policy debates approximately every twenty years. Heritability, in the strict sense, is a ratio of the total phenotypic variance that is attributable to additive genetic variance (i.e., the variance contributed by the mean effect of different alleles). Because total variance of the phenotype is in the denominator of this ratio, heritability is very much a population-specific measure. If a population has low total phenotypic variance because of a uniformly positive environment, for instance, there is more potential for a greater fraction of the total variance to be due to additive genetic variance. Think, for example, about children's intelligence (as measured through psychometric tests) in a wealthy community with an excellent school district where most parents are college-educated and therefore have the motivation to guide their children to high scholastic achievement, the resources to supplement their children's school instruction (e.g., hiring tutors or sending kids to enrichment programs), and the study skills and knowledge base to help their children with homework, etc. I have used this example in prior post. Given the relative uniformity of the environment, more of the variation in test scores may be attributable to additive genetic contributions and heritability would be higher than it would be in a more heterogeneous population. This is a hypothetical example, but it illustrates the rather constrained meaning of heritability and the problems associated with its application to cross-population comparisons. It is also suggestive of the problem of effect sizes of different contributions to phenotypic variance. The potential for environmental variance to swamp real additive genetic variance is quite large. What's a better predictor of life expectancy: having a genetic predisposition to high longevity or living in a neighborhood with a high homicide rate or a endemic cholera in the drinking water supply?

Heritability essentially measures the potential response to selection, everything else being equal. The so-called Breeder's Equation (Lush 1937) states that the change in a single quantitative phenotype (e.g., height) from one generation to the next is equal to the product of heritability and the force of selection. If there is lots of additive variability in a trait but not much selective advantage to it, the change in the mean phenotype will be small. Similarly, even if selection is very strong, the phenotype will not change much if the amount of additive variance is low. A famous, but frequently misunderstood result, known as Fisher's Fundamental Theorem shows that the change in fitness is directly proportional to variance in fitness. This is really just a special case of the breeder's equation, as shown in great detail in Lynch and Walsh's textbook (and their online draft chapter 6) or in Steve Frank's terrific book, in which the trait we care about is fitness itself. An important implication of Fisher's theorem is that selection should deplete variance in fitness -- and this makes sense if we think of selection as truncating a distribution. A corollary of Fisher's theorem is that traits which are highly correlated with fitness should not have high heritability. Oops. Does this mean that intelligence, with its putatively very high heritabilities is not important for fitness?

Everything in the last paragraph applies to the case where we are only considering a single trait. When we consider the joint response of two or more traits to selection, we must account for correlations between traits (technically, additive genetic covariances between the traits). Sometimes these covariances will be positive; sometimes they will be negative. When the additive genetic covariance between two traits is negative, it means that selection to increase the mean of one will reduce the mean of the other. In their fundamental (1983) paper, my Imperial College colleague Russ Lande and Steven Arnold generalized the breeder's equation to the multivariate case. The response to selection becomes a balancing act between the different force of selection, additive genetic variance, and additive genetic covariance for all the traits. Indeed, this is where constraints come from (or it's at least one place). Suppose there are two traits (1 and 2) that share a negative covariance. Further suppose that the force of selection is positive for both but is stronger on trait 1 than it is on trait 2. Depending on the amount of genetic variance present, this could mean that the mean of trait 2 will not change or even that the mean could decrease from one generation to the next.

The work of Lande and Arnold (and many others) has spawned a huge literature on evolvability (something that Charles has moved into and that we have some nascent collaborative work on in the area of human life-history evolution). This work is very important for understanding things like the evolution of human psychology. Consider the hypothesis, popular in evolutionary psychology, that the mind is divided into a large number of specific problem-solving "modules," each of which is the product of natural selection on the outcome of the problem-solving. How do you create so many of these "organs" in a relatively short time frame? Humans last shared a common ancestor with chimpanzees and bonobos around five million years ago and most likely human ancestors until about 1.8 million years ago seem awfully ape-like (and therefore probably not carrying around anything like the human mental toolkit in their heads). One of the key processes responsible for the creation of complex phenotypes is known as modularity (which is a bit confusing since this is also the term that evolutionary psychologists use for these mental organs!) and one of the fundamental mechanisms by which modularity is achieved is through the duplication of sets of genes responsible for existing structures. These duplicated "modules" are less constrained because of their redundancy and can evolve to form new structures. However, the fact that modules are duplicated means that they should experience substantial genetic correlation with their ancestral modules. This makes me skeptical that the diversity of hypothetical structures posited by the massive modularity hypothesis could be constructed by directional selection on each module. There is just bound to be too much correlation in the system to permit it to move in a fine-tuned way toward to phenotypic optimum for each module.

Trade-offs matter for the evolution of phenotypes. While I suspect that very few human evolutionary biologists would argue with that, I think that we generally fall short of considering the impact of trade-offs for adaptive optima. The multivariate breeders' equation of Lande and Arnold gives us an important (though incomplete) tool for looking at these trade-offs mechanistically. A few authors have done this. The example that comes immediately to mind is Virpi Luumaa and her research group, who have done some outstanding work on the quantitative genetics of human life histories using Finnish historical records.

My third, and last (for now), point addresses the constancy of selection. This is related to the concept of the Environment of Evolutionary Adaptedness (EEA), central to the reasoning of evolutionary psychology. A few years back, I wrote quite a longish piece on this topic and its attendant problems. Note that when we use population-genetic models like the one we discussed above for the expected time to fixation of an advantageous allele, the selection coefficient s is the average value of that coefficient over time. In reality, it will fluctuate, just as the demography of the population selection is working on will vary. Variation in vital rates can have huge impacts on demographic outcomes, as my Stanford colleague Shripad Tuljapurkar has spent a career showing. It can also have enormous effects on population-genetic outcomes, which shouldn't be too surprising since it's the population of individuals which is governed by the demography that is passing genetic material from on generation to the next!

When I read accounts of rapid selection that rely heavily on EEA-type environments or the type of generalizations found in the second half of Wade's book (e.g., Asians live in paternalistic, autocratic societies), my constant-environment alarm bells start to sound. I worry that we are essentializing societies. One of the all-time classic works of British Social Anthropology is Sir Edmund Leach's groundbreaking Political systems of Highland Burma. Leach found that the social systems of northern Burma were far more fluid than anthropologists of the time typically thought was the case. One of the key results is that there was a great deal of interchange between the two major social systems in northern Burma, the Kachin and and Shan. Interestingly, the Shan, who occupied lowland valleys, practiced wet-rice agriculture, and whose social systems were highly stratified were seen by western observers as being more "civilized" than the Kachin, who occupied the hills, practiced slash-and-burn agriculture, and had much more egalitarian social relations. Leach (1954: 264) writes, "within the general Kachin-Shan complex we have, I claim, a number of unstable sub-systems. Particular communities are capable of changing from one sub-system into another." Yale anthropologist/political scientist James Scott has extended Leach's analysis in his recent book, The Art of Not Being Governed, and suggested that the fluid mode of social organization, where people alternate between hierarchical agrarian states, and marginal tribes depending on political, historical, and ecological vicissitudes is, in fact, the norm for the societies of Southeast Asia.

The clear implication of this work for our present discussion is that a single lineage may find some of its members struggling for existence in hierarchical states where the type of docility that Wade suggests should be advantageous would be beneficial, while descendants just a generation or two distant might find themselves in egalitarian societies where physical dominance, initiative, and energy might be more likely to determine evolutionary success. I don't mean to imply that these generalizations regarding personality-type and evolutionary success are necessarily supported by evidence. The key here is that the social milieux of successive generations could be radically different if the models of Leach and Scott are right (and the evidence brought to bear by Scott is impressive and leads me to think that the models are right). At the very least, this will reduce the average selection differential on the putative genes for personality types that are adapted to particular socio-political environments. More likely, I suspect, it will establish quite different selective regimes -- say, for behavioral flexibility through strong genotype-environment interactions!

These are some of the big issues regarding genetics and the evolution of human behavior that have been bothering me recently. I'm not sure how we go about fixing this problem, but a great place to start is by fostering more collaborations between geneticists and behavioral biologists. Of course, this would be predicated on behavioral biologists' motivation to fully understand the origin and maintenance of phenotypes and I worry that the institutional incentives for this are not in place.

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EEID 2014 Wrap-Up

June 5th, 2014 · Evolution, Human Ecology, Infectious Disease, science

It's been a long time since I've written in monkey's uncle. Life has gotten pretty busy and my seeming inability to write brief entries has led me to neglect the blog this year. However, I am freshly back from the Ecology and Evolution of Infectious Disease Conference in Fort Collins, Colorado and feel compelled to give my annual run-down. The conference was hosted by friend and colleague Mike Antolin, Sue Vandewoude, and my erstwhile post-doc, now CSU researcher, Dan Salkeld. Nice job, folks, on a very successful conference.

EEID is pretty much the best meeting. As I noted in last year's post, I love its future-orientation. EEID is a meeting that foregrounds the work of junior scientists and there was, as ever, a tremendous array of human capital on display at this meeting. This drives home to me the importance of investment in professional training and research programs that specifically develop human capital. This community exists in large measure because of the innovative program jointly offered by NSF and NIH. Thanks as ever to the vision and hard work of Josh Rosenthal, Sam Scheiner, and all the funders (e.g., support from The Gates Foundation can be found all around this conference) for this area. It's always great to catch up with smart, fun friends. Plenty of time was spent talking science and drinking craft beer (what a beer town Ft. Collins is!) with the likes of Peter Hudson, Jessica Metcalf, Ottar Bjornstad, Aaron King, Mike Antolin, Tony Goldberg, Issa Cattadori, Maciej Boni, Marm Kilpatrick and, of course, Dan Salkeld. It was nice to meet and chat, if only briefly, with my sometime remote collaborator Paul Sharp, who gave what I understand to be an extremely stimulating keynote on the complicated and surprising evolution of malaria (alas, I missed it as I was delayed getting to Ft. Collins). I also spent some quality time learning about acquired immunity in dogs with Colin Parrish. This may come in handy for some ideas that Jess Metcalf and I have been playing around with.

There is a great tradition of the EEID hike and closing banquet/dance. Ft. Collins provided a beautiful and challenging hike out in Lory State Park. The view from the top of Arthur's Peak was pretty amazing.

View from the top of the trail on Arthur's Peak, Lory State Park, Ft. Collins.

View from the top of the trail on Arthur's Peak, Lory State Park, Ft. Collins.

At Wednesday's banquet, I'm afraid to say that Princeton once again dominated the dance floor as we all rocked out to the amazing Denver funk/rock/jam band Kinetix (great choice, Mike). The Stanford showing was disappointing in part because of the early departure of some of our most enthusiastic dancers. Don't get cocky though, Princeton. We'll be gunning for you next year.

The entirety of Tuesday morning's session was given over to communicating science. Dan Salkeld warmed up the crowd with some hilarious examples of the reporting frenzy that ensued following the publication of our paper on plague dynamics in prairie dog towns or, more recently, Hillary Young's work showing that excluding large ruminants increases rodent density in Kenya. Wow. Dan also used my Stanford colleague Rebecca Bird's work as an example of how an unexpected story can engage readers and listeners. My collaborator Tony Goldberg gave a talk that was also not lacking in ridiculous headlines thanks to his "viral" nose-tick work. David Quammen, author of outstanding popular science books such as The Song of the Dodo and Spillover (which Bill Durham and I use for our class on environmental change and emerging infectious disease), gave a terrific presentation in which he consolidated a lot of nice, practical advice on the craft of writing engaging work into 18 points, amply illustrated by anecdotes of characters from our field. Sonia Altizer from the University of Georgia introduced the crowd to the opportunities (and pitfalls) of citizen science and suggested that it might just be possible to engage the public in disease ecology data collection. Some examples she identified included the granddaddy of citizen-science in the US run by the Laboratory of Ornithology at Cornell, the ZomBee Watch at SFSU, and her own Project MonarchHealth. If I had to summarize this session in one pithy phrase, I think it would have to be "Yay, ecologists!"

Quammen took to Twitter to call us out for being behind the curve with respect to social media.

While there were, in fact, a few of us tweeting the occasional tidbit from the conference, I think his general point is valid. This stuff is intrinsically interesting and we can do a much better job communicating to broad publics.

Some talks that really caught my attention.

Ary Hoffmann gave a great talk about the complexities of using bacteria of the genus Wolbachia to control the Aedes mosquitoes that transmit dengue in Australia (and elsewhere). Wolbachia infects mosquitoes and can have a variety of effects on their biology. The reason artificial infection of mosquitoes wit this bacterium seems so promising as a means of biological control is that the offspring of crosses between infected and uninfected mosquitoes are not viable. This is obviously a very substantial fitness cost to the mosquitoes and this creates serious challenges for getting the infected mosquitoes to persist and take over local populations. Hoffmann presented a cool result about the invasibility of infected mosquitoes wherein in the early phases of introduction there is an unstable point in the mosquito dynamics. At this point, if the infected mosquitoes are above a threshold, they will successfully invade, otherwise, they will die out because of the inherent fitness costs of the Wolbachia infection. One policy challenge that arises is that to get a local population of mosquitoes above the invasibility threshold, researchers and vector-control specialists have to sometimes introduce a lot of mosquitoes. This means that the number of mosquitoes locally can increase substantially and, as you can imagine, this isn't always popular with communities.

Fellow Anthropologist Aaron Blackwell from UCSB gave a fantastic talk on our "old friends", the helminths (cue the freaky electron micrograph of a helminth's mouth!). Aaron participates in the Tsimane Health and Life History Project which was started by colleagues Mike Gurven (also at UCSB) and Hilly Kaplan (New Mexico). Using sophisticated multi-state Markov hazard models (go Anthropology!), Aaron showed that co-infection with helminths and Giardia is less frequent than expected among this population that experiences ubiquitous exposure to both pathogens and that, in fact, infection with the one appears to be protective against infection with the other. One of the most provocative results he presented showed that helminth infection actually lowered systolic blood pressure in men by an amount equivalent to the increase that comes from aging ten years. Chronic helminthic infection may be a reason why Tsimane men's systolic blood pressure does not rise precipitously with age as it does in the US. This result, which may provide fresh insights into the mechanisms of hypertension, a major source of morbidity in the US, struck me as particularly poignant given the demeaning comments made about NSF funding for work among the Tsimane from none other than Lamar Smith (R–TX), the chair of the House Committee on Science, Space, and Technology.

Anna Savage, a post-doc with the National Zoo in Washington DC, gave an awesome talk on the comparative immunogenetics of of frogs with respect to infection with the devastating fungal infection, chytridiomycosis. Chytridiomycosis has been identified as a major cause of amphibian extinction worldwide and Anna showed surprising heterogeneity in immune response across frog species. This is a subject with which I have only passing familiarity, but her talk demonstrated an amazing sophistication in integrating different levels of biological organization and making sense of a dauntingly complex problem. I would wager that Dr. Savage is one to keep an eye on.

The organizers tried a scheduling format that was a bit different from last year, wherein each session started with two half-hour talks generally given by somewhat more senior people. The second half of each session was then given over to brief ten-minute talks, typically delivered by more junior people. This format is nicely in keeping with the great EEID tradition of promoting the research of junior scientists. A few short talks that I found especially interesting included one by Sarah Hamer, from Texas A&M, on Chagas disease in the United States. She presented sobering data from national blood-bank surveillance showing a surprising number of Chagas-infected samples coming from donors with no history of travel to Latin America. When pushed by a questioner, she suggested that she would consider Chagas to be endemic in the US, at least in dogs and possibly even in people. Carrie Cizauskas, formerly of Wayne Getz's shop at Berkeley and now with Andy Dobson and Andrea Graham at Princeton, give a nice talk on the role of both stress and sex hormones in mediating macroparasite infection in wild ungulates in Etosha National Park, Namibia. Romain Garnier from Princeton described a very nifty image-processing approach to scanning large volumes of histological slides for indications of infection.

I perhaps didn't see as many posters as I should have. The problem with the poster sessions is that one keeps running into various people one wants to talk to. I did manage to check out the poster of my former freshman advisee and current Princeton EEB student Cara Brook. She's got an awesome PhD project studying the multi-host ecology of infectious disease in Malagasy fruit bats.

I'm looking forward to next year's meeting at the University of Georgia already. I'm also looking forward to resuscitating the pedagogical workshop that used to be a signature feature of this EEID meeting. More on that later...

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More Guilt Over Agricultural Disease Names

December 16th, 2013 · Infectious Disease

In the spirit of my professed guilty amusement about the names of agricultural diseases, I just chuckled a bit at a promedmail update of what sounded like a biblical plague that had to be sent directly to the Apocrypha: Crayfish plague in Israel. Watch out, Pharaoh...

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AAA Recap, 2013

November 26th, 2013 · Anthropology, science, Social Network Analysis

I guess it's that time of the year. You know, when I recap, in my bittersweet way, the annual meeting of the American Anthropological Association? I am an anthropologist, yes, but I am deeply torn in my feelings for my discipline, my department, and my flagship (?) professional organization. The question mark arises because I am also a physical anthropologist and a demographer, so an argument can be made that my flagship professional organization is actually AAPA or PAA, but there is something about the unmarked category that is AAA. It's supposed to represent anthropologists, broadly construed. I honestly don't think that it does a very good job at this, but the reasons behind that are complex and I've only allocated myself a bit of time to blog since I'm desperately trying to catch up from all the travel I've done recently.

The meeting this year was in Chicago, which is a pretty amazing town. I stayed in the the Blackstone Renaissance Hotel, which was recently renovated in a lovely Art Deco theme. We did Chicago stuff. Tube steaks were eaten, the quantity of cheese that can be crammed into a deep-dish pizza was marveled at, beer was drunk.

AAA is a pretty bizarre scene. For starters, it's at the weirdest time. It seems like the peculiar timing of AAA during November must be disruptive for just about every academic anthropology department, particularly because it is nearly a week-long endeavor. It seems that the life in an American university carries on just fine without the anthropologists around for a week in the middle of the Fall term, thank you very much. A couple innovations this year struck me as particularly incongruous, given the content of much current scholarship in anthropology. First, anyone who registered for the meeting as a non-member was given a yellow badge holder to mark them as outsiders. This seemed a bit gratuitous. I'm not sure what's gained from such marking -- they already pay a substantially higher rate for the privilege of attending, do they also need to be shamed for their lack of faith? Second, in the hall outside the main bunch of conference rooms, there was a television that played a loop of anthropologists talking about how important anthropology is. This struck me as unnecessarily propagandistic and it's not at all clear to me who the target audience for this performance was. Presumably, those of us who were there already think that anthropology is a worthwhile endeavor. Seems to me that it's the rest of the world we need to convince. Once again, there appears to be almost nothing considered newsworthy to emerge from this meeting of 6,000+ scholars with the exception of a paper on the similarities in street-scanning behaviors by police and fashion scouts.

Another strange feature of AAAs is that computers, cables, remotes, laser-pointers, etc. were not provided in the conference rooms but needed to be provided by the session chairs. This is the first time I've experienced this in years at a major conference and it definitely slowed us down quite a bit at the start of our session. I'm not sure what was going on with that. Maybe the budget to pay for AV services was already spent on the fancy video production that reminded us how important we all are?

This year, I organized and chaired a session, which was sponsored by EAS, on social network analysis in evolutionary anthropology. Unfortunately for the EAS party-goers from the previous night, the session ran at 08:00 on Saturday morning. Despite this challenge, the room was packed and the audience generally seemed into it. We had great talks by Stanford's own Elly Power and Ashley Hazel. Elly talked about her amazing dissertation research on using social capital to understand costly displays of religious devotion in southern India. Ashley talked about her dissertation work in the School of Natural Resources and the Environment on mobility and the changing landscape of STI risk in Kaokoland, northern Namibia. David Nolin, one of our discipline's most talented young methodologists, presented a very clever test of generalized reciprocity using dichotomous exchange data from his work in Lamalera in Indonesia. Ben Hannowell, yet another talented methodologist to come out of the WSU/UW IGERT program, discussed his collaborative work with Zack Almquist on inferring dominance structure from tournament graphs. The always marvelous Rebecca Sear talked about her recent synthetic work on the effects of kin on fertility (kinship, of course, is the classic application of networks in anthropology since genealogies are just special cases of graphs). John Ziker presented a network-based approach to understanding food sharing and reciprocity from his terrific ethnographic work in Siberia. I closed out the talks with my own combination history of anthropological (and ethological) contributions to social network analysis and pep talk to encourage anthropologists to be confident about their methods and have the courage to innovate new ones the way people like John Barnes or Clyde Mitchell or Elizabeth Bott or Kim Romney or Russ Bernard did!

After schmoozing for a bit post-session, I headed over to the Saturday EAS session on methodological advances in experimental games. While I didn't see all the talks, the ones I saw were pretty cool. In general, I have mixed feelings about experimental economic games. There are lots of results and some fairly convincing stories to go along with some of the results. However, absent of context, I really wonder what they are measuring and, if they are indeed measuring something, whether it is actually interesting. This session made some real progress in dealing with this question and I think it really highlighted the comparative advantage of anthropologists in the multi-disciplinary landscape of twenty-first century behavioral science. While economists such as Loewenstein (1999) might lament the fact that there is no way to play context-less games and that this jeopardizes the validity and generality of such experimental games, anthropologists are experts in thinking specifically about context and its effect on behavior. Furthermore, anthropologists are still the go-to researchers for providing contextual diversity. In this session, we heard about experimental games played in Bolivia, Siberia, Fiji, and on the streets of Las Vegas. One talk in this session that particularly impressed me was given by Drew Gerkey, who is currently a post-doc at SESYNC in Annapolis, Maryland (and soon to be an assistant professor at Oregon State University -- Go Beavs!). I was at SESYNC earlier in the week and got a chance to talk pretty extensively with him about this work. Drew makes the point that seems obvious now that I've heard (a sign of an important idea) that, in the evolution of cooperation literature, the counterfactual scenario to cooperation is frequently untenable. One does not simply go it alone when one is a hunter/fisher in Siberia. Drew also designed a number of very clever experimental games that fit the types of social dilemmas faced by his Siberian interlocutors. Very nice work indeed.

In addition to the sessions I attended, it was nice to see and chat with various smart, fun people I know who sometimes find their way to AAAs. I missed my partner in crime from last year's AAA, Charles Roseman, who left the day I arrived, probably too bloated from the binge on Chicago's amazing food he no doubt shared with Fernando Armstron-Fumero to be of much use to anyone. However, I got to see Siobhan Mattison, Brooke Scelza, Brian Wood, Rick Bribiescas, Mary Shenk, Aaron Blackwell, Pete Kirby and, briefly, Shauna Burnsilver and Dan Hruschka. Despite my general misgivings about the conference, it is nice to have an excuse to see so many cool people in one place at one time.

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