# Something Newsworthy From the AAAs!

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.

# Ebola Event at UCI: Planning, Not Panic

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.

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

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.

# Selection is What Matters

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.

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.

# Quick and Dirty Analysis of Ebola

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:

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:

[r]

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