monkey's uncle

notes on human ecology, population, and infectious disease

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Winter Anthropology Colloquium, Part 2

January 18th, 2015 · Anthropology, Human Ecology

We had the second of our speakers in the winter anthropology colloquium Friday. Daniel Nettle came on Friday. Daniel’s talk was co-sponsored by the Institute for Research in the Social Sciences. Daniel is a human behavioral ecologist with extremely broad interests and a penchant for using HBE as a tool for studying social inequality and human health. Somehow, we’d never met before. I’m glad that’s been taken care of now. Of the dozens of things that Daniel could have talked about, he chose to talk about his ethnographic project in Newcastle on Tyne.

Given my interests in demography and epidemiology, I’ve seen lots of talks on social deprivation, inequality, neighborhood effects, etc., but Daniel’s talk showed a refreshing creativity. A large fraction of the data he presented came from deceptively simple ethological methods. I think that there is a lot that both the methods and theory of behavioral ecology and ethology have to offer studies of social inequality and health. Of course, I’m not alone in this belief. Mhairi Gibson (my collaborator in Uganda) and David Lawson (this week’s speaker!) published a terrific  book last year on the application of HBE to applied problems.

Much of the work Daniel’s work in this area is published in open-access journals (e.g., here and here). I’m intrigued by the relatively new journal, PeerJ, where he has published a number of papers now, and am planning to submit something there soon.

The flyer for Daniel’s talk:


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Winter Anthropology Colloquium, Part 1

January 14th, 2015 · Anthropology, Demography, Evolution

I am organizing the colloquium for the Stanford Anthropology department this winter. I believe it may be the first time that a faculty member for the Ecology and Environment group has organized the colloquium since the Blessed Event that merged departments back in 2008 (though I’m not certain of that). There have been a few scheduling glitches, as it seems winter quarter 2015 has the highest density of talks I’ve yet encountered in 11 years at Stanford, but we’re off to a great start. Our first speaker came all the way from the UK to speak to us about social dilemmas and cooperation. Shakti Lamba is an ESRC Research Fellow and Lecturer in Human Behavioural Ecology in the Centre for Ecology and Conservation at the University of Exeter.

Shakti talked about her very exciting work on behavioral norms. She uses a variety of methods, including ethnography, experimental games, and advanced statistical techniques to understand the nature of variation in cooperative norms within and between populations (see, e.g., papers here or here for examples of her work). I generally have mixed feelings about experimental games, but I think there is a small cadre of anthropologists, including Shakti and Drew Gerkey, among others, who use them as a tool for eliciting much richer behavioral and social observations than do most field researchers (whether or not they use experimental games!). I was impressed by the sophistication of her approach, her keen experimental design, and the excellent population thinking that it entails. However, I was most impressed with her coolness and eloquence under some pretty heated questioning from a number of senior faculty members who simply misunderstand evolutionary process.  Looking forward to seeing more of her work, especially forthcoming longitudinal research with Alex Alvergne, in the future!

Here is the poster for her talk:


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Something Newsworthy From the AAAs!

December 15th, 2014 · Anthropology, Infectious Disease

About this time of the year, I generally do a re-cap of the American Anthropological Association’s annual meeting. However, I didn’t attend AAAs this year for the first time in five years, so I don’t have much to report. Anthropologists’ annual awkwardly-timed professional ritual just went down in Washington DC and I thought I would see if anything newsworthy came of it. Doing a Google news search with a variety of permutations of the association name (American Anthropological Association in quotes and not, AAA, etc.) and other keywords (Washington, annual, meeting, 2014, etc.), I managed to find one or two things. As I (and others) have noted before, the AAA meetings don’t attract a lot of press. New discoveries or items of broad public interest are apparently not generally discussed at AAA. This year, the most notable item in a news search is the rejection of a resolution to boycott Israel over what the resolution referred to as “Israel’s ongoing, systematic, and widespread violations of Palestinian academic freedom and human rights.”

One other item popped up which actually resembles something newsworthy on the scholarly front (as opposed to the business of the association).  Kari Lyderson at the Crux writes about a movement to bring anthropological expertise to bear on the ongoing Ebola Virus Disease epidemic in West Africa. Sharon Abramowitz, a terrific medical anthropologist at the University of Florida, has helped to found an initiative called the Ebola Emergency Response Initiative, the aim of which is to provide social and cultural expertise to help with control of the EVD epidemic. This is good news and exactly the sort of thing I would like to see more of at AAA. There are many ways that improved cultural understanding by medical personnel and public health practitioners could help to bring this epidemic under control – a point that anthropologist/human behavioral ecologist Barry Hewlett been making for years now. These are issues we’ve thought about a bit here and that my Ph.D. student Gene Richardson is actively working on in Sierra Leone right now.

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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 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...



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

  1. library(lubridate)
  2. # number of cases as of 11 August 2014
  3. #
  4. cases <- 1848
  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
  13. ## incubation period 2-21 days
  14. ##
  15. ## duration of infectiousness: virus detected in of lab-infected man 61 days!
  17. ## Legrande et al. (2007) use L=7 and D=10
  18. ## doi:10.1017/S0950268806007217
  20. lambda <- log(cases)/t
  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
  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. }
  39. cols <- topo.colors(10)
  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])

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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 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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