Does smoking weed really result in brain abnormalities? Maybe not.

554px-Cannabis_leaf_2.svgA study purporting to find that marijuana use (even casual marijuana use) may be associated with brain abnormalities has been getting a lot of press lately. You can check out some of the coverage at CNN Health, the Huffington Post, and Fox News. And you can check out the original paper in the Journal of Neuroscience, Cannabis use is quantitatively associated with nucleus accumbens and amygdala abnormalities in young adult recreational users by Gilman et al., here.

Shortly after the study came out, Lior Pachter posted an analysis of some major problems with the study on his blog. I’m posting a link to his post because I think it’s a great example of something science bloggers do very well: they share important information about the quality of recent studies in real time. This is essential stuff you just don’t typically see in media coverage.

I’d also like to note that the statistical issues he points out are very basic ones. Adjusting p-values for multiple testing is something that I think most researchers understand they have to do even after an introductory stats class. So I’m having a difficult time understanding how this manuscript sailed through peer review in its present form. The Journal of Neuroscience is not some fly-by-night journal! I hope that journal editors will see what happened here and realize that if a manuscript contains statistics, it’s probably a good idea to choose at least one reviewer with knowledge of statistics. Failure to control for multiple testing appropriately is something I see over and over again in the articles I review. There is definitely a need for the statistics police in the peer review process.

My take on “Is Breast Truly Best?”

So I’m a little late to this party, but I thought I’d add my two cents about the “Is Breast Truly Best?” study that recently came out in the journal Social Science and Medicine. This study, which analyzed the effects of breastfeeding using 25 years of data from the National Longitudinal Survey of Youth, got a ton of media coverage. You might have seen the Daily Mail headline, for example: “Breast milk is no better for a baby than bottled milk.”

Naturally, in light of the horrendous media coverage, researchers and other folks interested in breastfeeding felt they needed to put their interpretations of the study out there. People used blogs to point out the problems with the media coverage and to help readers better understand how the study was performed and what it actually showed. If you are interested, you can take a look at the posts about this study on Mammals Suck, Biomarkers and MilkResearch The Headlines, Behind the HeadlinesEvolutionary Parenting. There has been a lot of great coverage already, but I think all of this attention has also highlighted some frequent concerns about population health research. I got in touch with Cynthia Colen, the study’s lead author and another Robert Wood Johnson Health & Society Scholar alum to help set the record straight about some of the aspects of the study that have proven more controversial. And, of course, I’d like to provide my take on what this study adds to the field.

The Study: Design and Rationale

I’ll start with just a little background on epidemiological studies of breastfeeding. If you have done much research or reading in this area, then you know population-scale studies of the benefits of breastfeeding are TOUGH. Breastfeeding is so tied to other factors with a strong effect on health and wellbeing outcomes, like socioeconomic status and race, that even when we try to control for those things we usually can’t completely remove their influence upon the data. For example, in the US, roughly 75% of white mothers breastfeed whereas only 60% of black mothers breastfeed. And even in places like Sweden, where there is strong support for new families, women of higher socioeconomic status are more likely to breastfeed. Therefore, when a study shows, for example, that breastfed infants have higher IQs, we can’t be entirely confident that this result isn’t just due to residual confounding associated with the general boost in wellbeing that comes along with belonging to a more affluent family.

In population health studies, one way that researchers try to get around this confounding problem is by performing within-family comparisons. In a normal epidemiological study, we try our hardest to adjust for things like socioeconomic status, hoping that we can make fair comparisons between families–but knowing that we can never completely account for the effects of these factors. By performing within-family comparisons, we are relieved of having to make these tough adjustments. Because we are comparing kids that belong to the same family, if we find that breastfeeding, for example, is associated with some health benefit, we can be more confident that this is not just the result of residual confounding. After all, these kids share exactly the same home environment. In the population health researcher’s bag of tricks, this is an important one!

Given the problems so many existing studies on breastfeeding and health/development studies have encountered, Colen decided to find a dataset she could use to perform this type of within-family comparison. This is what led her to the National Longitudinal Survey of Youth study. This dataset has a number of strengths. First, it’s relatively large. It contains information on 11,504 children and 4,932 mothers. Second, the information on breastfeeding was collected prospectively. That is, the mothers were asked whether they breastfed while their kids were babies, rather than being asked years later (when the outcomes were assessed). This is important, as memory really fades as time goes by!  Third, there was information on 11 different health, behavior, and academic outcomes: (1) BMI; (2) obesity; (3) asthma; (4) hyperactivity; (5) parental attachment; (6) behavioral compliance; (7) reading comprehension; (8) vocabulary recognition; (9) math ability; (10) memory-based intelligence; and (11) scholastic competence. Not bad!

So armed with this data, Colen et al did a two-tiered analysis. After excluding multiple births (which can complicate an analysis like this one), they analyzed the full panel, 8,237 children from 4,071 families, using standard multiple regression models. They controlled for all of the things you would expect (age, race, mom’s marital status, region of the country, maternal education, family income, maternal employment status, insurance status, birth order, preterm birth, maternal smoking during pregnancy, maternal alcohol consumption during pregnancy, prenatal care initiation during first trimester). Their results indicated that breastfed children 4 to 14 did better on every outcome measured except for asthma. So in this part of the study, the benefits of breastfeeding appeared to be impressively wide-ranging. But remember: the potential for confounding was still present in this part of the study.

Next, they moved on to the heart of the study, in which they compared outcomes within families. In 665 of the families studied, siblings had different breastfeeding experiences. That is, one sibling was breastfed while another was not. When the authors investigated the 1,773 children from these families, the results changed. Big time. All of those outcome measures that looked better in breastfed kids in the first part of the study? They lost statistical significance. One interpretation of these results–the authors’ interpretation–is that when we are better able to control for factors like socioeconomic status and race, many of the apparent benefits of breastfeeding in the US disappear. They may not exist at all, or they may be too subtle to detect. If this information is correct, it is important to provide to mothers, as breastfeeding is often a very difficult process, especially for working women. If the benefits aren’t as large as advertised, some mothers may decide not to do it.

Some Potential Limitations

We already talked about the insidious role that residual confounding plays in population health studies. There is another big problem that we face when we study breastfeeding in large populations, though. And that problem is measuring breastfeeding. Getting good measures of breastfeeding for the huge number of kids in a population-based study like this one is next to impossible. These big studies are our primary source of large-scale breastfeeding data, but most of the time whether or not a woman is breastfeeding is just one box of many to be ticked off in a long survey. Breastfeeding is complicated, and these studies don’t do nuance. They’re just not designed that way. What if a mother only breastfeeds a baby in the hospital after delivery? Should we count that baby as breastfed? Is it fair to expect that the benefits associated with breastfeeding for a couple weeks are similar to those associated with breastfeeding for six months or more? Also, many babies are fed a mixture of breastmilk and formula. Typically, surveys don’t ask about this. So measuring the “exposure” being studied, breastfeeding, is really problematic. In this study, breastfeeding was coded as either “yes” (for any length of time) or “no.” However, information on the duration of breastfeeding was also collected (that is, how old the baby was when breastfeeding ceased entirely).

As EA Quinn has pointed out, one key feature of this study that is not described in the article is what “breastfeeding” means in the families in which one child was breastfed and another was not. What are we comparing? It seems as though it would be a little unusual for a woman to be super gung-ho about breastfeeding one kid while not breastfeeding another at all, barring health problems in mother or baby. For that reason, it’s natural to worry that maybe in this particular group, we’re comparing kids who were not breastfed to kids who were breastfed for only a very short time (maybe only days or weeks). If the kids in the intra-family comparison were only breastfed for a very short period relative to the kids in the larger sample, we would expect any beneficial effects of breastfeeding to be much attenuated, which could explain the results. In other words, it’s not that the results from the entire sample were wrong–it’s that the statistical power to detect those beneficial effects in the within-family comparison disappeared. For that reason, I asked Colen about the mean duration of breastfeeding in the within-family comparison. She acknowledged that the duration of breastfeeding WAS significantly shorter than in the full sample (in which the mean duration of breastfeeding was 23 weeks). However, when we talked she wasn’t sure what, exactly, that duration was. If I get that information, I’ll be happy to update the post for any interested readers.

Another important limitation is that these results are primarily relevant to mothers in the US. I think the authors did a fine job of making it clear that these results were relevant to US families. The media, not so much. It’s important to remember that the breastfeeding environment in the US is pretty unique. On the plus side, we have access to clean water, which makes formula-feeding a much safer alternative than it is in many low-income countries. On the minus side, pro-breastfeeding policies in the US are pretty terrible. Our family leave policies are awful, making it very hard for many women who want to breastfeed to do so. Workplace daycares are few and far between. There may be no space/time for women to pump at work. Therefore, this study was geared towards addressing an issue that is particularly problematic for mothers in the US: when breastfeeding is so damn hard, and may even endanger a woman’s livelihood, just how many resources should be devoted to it?

Why Keep Doing These Population Health Studies of Breastfeeding if They Are So Tough to Interpret?

Over at Mammals Suck, understandably frustrated guest poster Melanie Martin asked “What if we stopped looking for small statistical effects of breastfeeding on IQ, and put more of our money and effort into researching the unique and variable aspects of human milk composition and synthesis? What if we conducted clinical studies to determine if different ratios of breast milk intake, or different durations of breastfeeding, result in observable, biologically meaningful differences in metabolic, immune, and neurological function?”

I’m sympathetic. Trying to decipher what’s going on in the tangle of epidemiological studies of breastfeeding in high-income countries is an exercise in frustration. I agree with Martin that we need more information on the proximate effects of breastfeeding. However, I also think it’s incredibly important to keep studying distal outcomes like the ones examined in this study–even if it’s exceedingly difficult. Why? Because the path leading from proximate to distal health outcomes is a winding, confusing one. We need data for every step along the way. In public health, often what we expect to happen, based on what we know about proximal effects, does not actually happen. Consider, for example, the literature on vitamins and cancer. There are all sorts of reasons to suppose that taking vitamins and minerals could help prevent cancer. But big randomized controlled trials have shown us that they actually appear to raise cancer rates in at-risk groups. Now just to be clear, I’m not comparing breastfeeding to cancer! And I’m not predicting that someday, as a result of better studies, we will be shocked to find that breastfeeding is actually bad for kids. Not at all. But given the difficult choices that mothers in this country do have to make, I think it IS important to figure out how the effects of breastfeeding on metabolic, immune, and neurological function translate into actual health outcomes. I think this will be especially important if we want to use breastfeeding research to influence policy.

I truly believe we are making strides. For example, we now have results from randomized controlled trials of breastfeeding. In a trial in Belarus, breastfed babies were less likely to experience gastrointestinal illnesses and atopic eczema, but no reduction in respiratory tract infections was found. That’s valuable information! And George Davey Smith and colleagues have taken another creative approach to the problem of confounding in breastfeeding studies:  they investigated the effects of breastfeeding in two samples in which the structure of confounding differed. One sample was from the UK, where breastfeeding is associated with higher socioeconomic status. The other sample was from Brazil, where there is no association between family income and breastfeeding. After examining effects on blood pressure, body mass index, and IQ, they found that only the beneficial effect of breastfeeding on IQ was present in both samples. This, too, is valuable information! I think we have to be cognizant that no one study is going to give us all of the answers. But studies like these do provide the puzzle pieces we can begin to fit together to learn more about the benefits of breastfeeding.

My Take On The “Is Breast Truly Best?” Study

This study, like any population-based study, certainly has limitations. Based on the available data, it does seem possible that the lack of beneficial effects observed in the intra-family comparison may simply be due to a lack of statistical power. But I think the approach taken by Colen et al., in which siblings were compared to avoid confounding, is a good one. If we can find enough families in which one sibling is breastfed for significant periods of time and another is not, barring extraordinary circumstances like health problems, we can gather some interesting information. I’d be really interested in hearing what the mean duration of breastfeeding was in that intra-family comparison group.

The benefits of breastfeeding as measured in older children may be subtle. And the presence/absence and magnitude of different benefits is bound to be information that struggling new mothers will find valuable, so I believe these findings are worth following up on. As Colen et. al state, “Total commitment to 6 months of exclusive breastfeeding is a very high expectation of mothers, especially in an era when a majority of women work outside the home, often in jobs with little flexibility and limited maternity leave, and in a country that offers few family policies to support newborns or their mothers. The line between providing information about the benefits of breastfeeding and stigmatizing mothers facing structured, valid, and often difficult trade-offs in the care and financial support of their children or in fulfilling their own human potential must be drawn sensitively.”

So let’s push for more breastfeeding research. Let’s let funders know that instead of gathering vague breastfeeding information as an afterthought in big studies, it’s important to gather quality, detailed data. Yes, it will be expensive. But it’s important. This is a subject worth studying, and any good cohort will take years to follow. Let’s get started now!


Vaccine refusal: it ain’t nothing new

imgres-1I’ve been fascinated by vaccine refusal for a long time, but for whatever reason I had never thought much about its history–at least not stretching back more than a few decades.

Perhaps it shouldn’t be surprising, but turns out that powerful anti-vaccine sentiment has been around for a long time! I just finished Pox: An American History by Michael Willrich, which explores the anti-smallpox vaccine movement during the last major epidemic in the US. Around the year 1900, smallpox emerged from the American South, where it had been festering, and started rampaging across the country, sparking epidemics in major cities like New York and Boston.

Desperate public health officials imposed mandatory vaccine drives. When people didn’t want to be vaccinated–and a lot didn’t–they risked being fined, thrown in jail, or physically restrained while somebody gave them the vaccination. Of course, vaccination laws were applied very differently depending on whether someone was wealthy or poor. In New York’s tenements, brute squads literally chased down and vaccinated every person they could find, breaking down doors and tearing children out of the arms of their mothers. The same was not true on Park Avenue.

All kinds of people joined anti-vaccine societies around the country. Celebrities weighed in too, although at that time people like Mark Twain and Williams James were voicing anti-vaccine sentiments. A little different from today, when anti-vaccine stars tend to be people like Jenny McCarthy and  Jim Carrey. It’s also striking how little the reasons for vaccine refusal have changed in 100+ years. Parents then were primarily concerned about their children’s safety. They cited all sorts of cases in which vaccines had been followed by death or terrible illness. Many believed that it was better to risk smallpox (especially in its milder variola minor form) than to receive the vaccine.

Of course then they had a point. People had very real reasons to worry about vaccine safety. Although local governments could compel people to be vaccinated, they could not guarantee the safety of the vaccines being administered. In the early days, when people were vaccinated with material from the lesions of another vaccinated person, the risk of some unwanted pathogen being transmitted alongside the vaccine virus was significant. In a particularly awful example from 19th century Italy, 63 children were vaccinated with infectious material taken from an infant who appeared to be healthy. Forty-four of those kids developed syphilis. Some also infected their mothers and nurses. And keep in mind this was before we had antibiotics–when syphilis often proved a death sentence.

Later, cows were used to produce the smallpox vaccine, which really helped ramp up production. It also meant that anyone with a cow and access to some virus could join the vaccine business–small, filthy operations were literally operating out of backyards in places like Brooklyn. There simply was no quality control or regulation.

Not surprisingly, vaccines at that time were often horribly contaminated. The vaccine site often became infected. A man or woman might lose days or weeks of work due to their inability to use the vaccinated arm–and the family that depended on them would suffer. That was sort of a best-case scenario, though. A number of children died of tetanus or other infections after vaccination. You can imagine how that stoked fear of the vaccine! It also horrified many of the doctors who unwittingly administered tainted vaccines and saw their patients suffer the results. Eventually, the attention these cases drew to the lack of quality control in vaccine production would revolutionize the way vaccines were produced, and quality control would become one of the industry’s major concerns. The government would also eventually recognize that it had a responsibility to regulate vaccine production and care for people harmed by vaccines.

The book also draws attention to a major divide in the medical community that was emerging at the time. Homeopaths and other alternative medicine practitioners were very active in the anti-vaccine movement. At the same time, allopaths were coming out strong in favor of vaccination and consolidating their hold over the medical profession. This is another source of tension that seems to have changed very little during the last century.

Willrich gives a sympathetic portrayal of the very real conflicts posed by mandatory vaccination as he follows the outcomes of court cases challenging mandatory vaccination laws. What are the rights of the individual weighed against the many? Especially when the risk of bodily harm to the individual is real? It’s interesting that a lot of passionate vaccine critics then were also active in the women’s rights and civil rights movements of the day. He makes a good case that society’s struggles with vaccine refusal have helped shape our understanding of civil rights. It’s a fascinating book, definitely worth a read!

Syphilis: Then and Now (Or What I’ve Been Doing For the Last 10 Years)

syphilisAn article about our work called Syphilis: Then and Now appeared in this month’s edition of The Scientist.

In it, Molly Zuckerman (U. Mississippi), George Armelagos (Emory U.), and I describe the work we’ve done together on the origins of syphilis. This was a great opportunity to look back at the last ten years, weaving together many different strands of research to figure out what exactly we have learned.

We talk about all the different approaches we’ve employed to try and learn more about the past of T. pallidum, the bacterium that causes syphilis, as well as the lesser-known non-sexually transmitted diseases, yaws and bejel. Looking at old bones in dusty basements? Building a phylogeny with T. pallidum samples collected from all over the world, including remote Amazonian villages? Getting to the bottom of a gruesome disease that causes wild baboons’ genitals to drop off? We’ve done it all! (With a lot of help from other people, of course.)

I will always feel incredibly lucky that I got to carry out my dream dissertation project. Every research project has its highs and lows, but throughout my PhD research I marveled that somebody was paying me to do what I would have gladly done for free. I will also be forever grateful that I had the privilege to work with so many amazing scientists. Thinking back on all this work was a really pleasant endeavor.

Writing this article also forced us to think about the future of this line of research. As we make clear in the article, although our work has shed some new light on the centuries-old debate about syphilis’s origins, there are plenty of questions left. As our ability to obtain whole genome sequences from even poor-quality samples improves, I’m really looking forward to seeing what we learn. The history of this bacterium is just as fascinating to me now as it was when I began my work.

Anyway, writing this article was a lot of fun–and if you are interested in the history of infectious diseases, I hope you will check it out!

And thanks to the folks at The Scientist, especially Jef Akst, for the chance to share our work. It was a pleasure to work with them on this.

A side effect of the flu vaccine teaches us something new about narcolepsy

images-3You’ve heard of narcolepsy. Probably the most famous symptom is someone falling asleep during the course of normal, daytime activities (like conversations). It’s a neurological disorder in which the brain is unable to properly regulate sleep-wake cycles. Experiencing sudden muscle weakness when you feel strong emotions is another symptom, as is sleep paralysis (when you wake up but cannot move or talk). Reading these symptoms makes me wonder if I have it! But it’s rare–it has been estimated to affect about 2 out of every 10,000 people.

We don’t have a great handle on what causes narcolepsy. Over the past few decades, evidence has started mounting in favor of a new hypothesis: that narcolepsy is an autoimmune disease. It became clear that the disease is  associated with a certain HLA genotype, DQBq*0602 positive (the human leukocyte antigen or HLA genes are involved in immunity). About 30% of the general population carries this genotype, but it’s found in 99% of narcolepsy cases, implicating the immune system. In addition, when researchers injected antibodies from narcoleptic humans into mice, the mice developed narcolepsy-like symptoms.

Now we’ve got a new source of evidence supporting the autoimmune hypothesis: a link between a flu vaccine used in 2009 and a scattering of childhood narcolepsy cases. As you may remember, 2009 was the year of the big H191 flu scare. In Europe, some countries used a vaccine called Pandemrix that was produced by GlaxoSmithKline. Researchers in Scandinavia were the first to discover that getting the flu shot was a risk factor for developing narcolepsy. In western Sweden, the odds of developing narcolepsy were roughly 25x greater for kids that got the Pandemrix shot than those who did not; in Finland, they were 13x greater; and in England, they were about 16x greater. Eventually, similar results were found in children who had received the vaccine in France too. Here, you can see a graph depicting the spike in cases following the 2009 vaccination campaign in Finland. Pretty striking!


Spike in childhood narcolepsy cases in Finland following H1N1 vaccination. From: Partinen M, Saarenpää-Heikkilä O, Ilveskoski I, Hublin C, Linna M, et al. (2012) Increased Incidence and Clinical Picture of Childhood Narcolepsy following the 2009 H1N1 Pandemic Vaccination Campaign in Finland. PLoS ONE 7(3): e33723. doi:10.1371/journal.pone.0033723

Now this is scary stuff, but I’d  like to point out that narcolepsy is actually a rare side effect of the shot. Only 1 of every 16,000 vaccinated children developed narcolepsy. And it’s important to remember the H1N flu itself can be pretty nasty, which is why the vaccine was developed in the first place. In Sweden, for example, even with the vaccination campaign there were 4,753 cases of H1N1 flu in children: 571 needed hospital care, 27 needed intensive care, and 4 died. So death occurs in about 1 of 500 kids who get the flu ,and narcolepsy occurs in about 1 of 16,000 kids who get vaccinated with this particular shot. Balancing the risk associated with the shot and the risk associated with the flu is tough–but for my kids, I would still favor the odds on the shot. Nevertheless, by 2011 the WHO had restricted the use of Pandemrix in children. This makes sense since other types of flu shots — that have not been linked to narcolepsy — are available.

Because narcolepsy seemed to be a side effect primarily of the European vaccine, attention centered on an ingredient found only in Pandemrix. This vaccine contained an adjuvant called ASO3 (an adjuvant is a material that helps create a strong immune response), whereas US versions did not. Thus, scientists hypothesized that it could be the strength of the immune response, which is greater when an adjuvant is involved, that leads to increased narcolepsy risk.

Now here is where things get tricky. It seems pretty clear at this point that in rare cases, the Pandemrix H1N1 vaccine triggers narcolepsy. But it looks as though the flu itself can trigger narcolepsy too. Getting the H1N1 flu, in particular, seems to be an important risk factor. Researchers at the People’s Hospital of Beijing University compared the number of new narcolepsy cases diagnosed every year from 1998–2012. They found a huge spike in new cases in 2010, following the H1N1 winter flu epidemic there. In 2010, 201 new cases were identified–more than the 187 new cases identified in all of 1998–2009 combined! By 2011 and 2012 the number of cases were back down to normal. So it looks like both the vaccine AND the flu can lead to narcolepsy. Doesn’t this remind you of the post I wrote about the flu vaccine and Guillain-Barré syndrome a few weeks ago?

The kind of risk associated with flu is not entirely clear yet, however, as H1N1 infection doesn’t seem to have contributed to the narcolepsy spike in Finland or in some other countries. Perhaps infection was more intense in China, in terms of both the numbers of infected people and the strength of the immune response. It’s not clear yet, but it will be interesting to see what we learn as time goes by.

So why would the flu vaccine/flu cause narcolepsy? In a recent article in Science Translational Medicine, researchers found that patients with narcolepsy have immune cells primed to attack a hormone called hypocretin. The brains of people with narcolepsy are missing the neurons that produce hypocretin, so this makes sense. Their immune system appears to have killed them off. And here’s where it all comes together: part of the H1N1 hemagglutinin protein closely resembles the parts of hypocretin visible to immune cells. In the laboratory, exposing immune cells from narcolepsy patients to these viral fragments increases the frequency of hypocretin-reactive cells! This is no good for the cells that produce hypocretin and suddenly become attractive targets for the immune system.

Who is most at risk for developing narcolepsy after the shot? All post-vaccine cases identified by three big narcolepsy centers in France, Canada, and the US have had a specific HLA genotype: DQBq*0602 positive. That was the genotype I mentioned before, the one that 99% of narcoleptics have. The post-vaccination cases identified in Sweden also had this genotype. So it seems as though the shot isn’t causing narcolepsy in just anyone. Instead, Pandemrix seems to be a precipitating factor for children who are already susceptible to developing the disease. Therefore, researchers have proposed HLA typing individuals prior to administering flu vaccines like Pandemrix.

Researchers have also called for additional studies examining whether non-adjuvant flu vaccines increase the risk of narcolepsy. The H191 vaccination campaign was unusual in that it involved the mass vaccination of tons of kids in a short period of time, facilitating our ability to recognize side-effects, like narcolepsy, linked with the shot. It’s also notable, but not surprising, that the narcolepsy connection was discovered in Scandinavia, where over 75% of kids were immunized and the health reporting is of excellent quality. It’s still possible that other flu vaccines carry a risk, probably less pronounced, that is hard to detect under normal conditions (like the relative chaos that is the US healthcare system). I think we are going to see some interesting research emerge in this area!

Do people get yaws from monkeys and apes? A potential roadblock for eradication.

Recently, a letter I co-authored called Treponemal infection in nonhuman primates as possible reservoir for human yaws was published in Emerging Infectious Diseases. It’s free if you want to check it out!

imgresMost people I know have never heard of yaws, but at one time it was very, very common in tropical regions across Africa, Asia, and the Americas. It’s a chronic, debilitating infection that is usually contracted during childhood, and it is caused by a bacterium closely related to the one responsible for syphilis. Luckily, it’s easily treated. You can cure it in its early stages with a single shot of penicillin, and recently we have learned that a single course of oral antibiotics appear to work just as well. In short, there is really no reason for anybody to have to suffer from this horrible disease.

Many other people feel the same way. In fact, a huge yaws eradication campaign took place in the mid-20th century. After World War II, this was one of the first big public health campaigns planned by a brand new World Health Organization. More than 40 million people were treated, and the number of new cases fell by as much as 95%. Not bad! The campaign wasn’t successful, though, in that it never achieved its ultimate goal: wiping this disease from the face of the earth.

There are multiple reasons why the first campaign failed. One big reason is that it simply didn’t have the resources to keep on top of things. After a while, the WHO turned over the responsibility for yaws surveillance and treatment to local governments. Unfortunately, the whole reason the campaign was necessary in the first place was that local governments weren’t capable of carrying out these kinds of tasks without support. Not surprisingly, yaws resurged in a number of countries and is still around today.

There is another important reason that the eradication campaign may have run into trouble: a potential animal reservoir. One of the most important criteria for an eradicable disease is that there is no animal reservoir. Otherwise, you can totally eliminate the infection from a population, only to have it re-enter via an infected animal. A single infected person spreads it throughout a newly susceptible population, and all of your hard work is for naught. In this situation, eradication is not an acceptable goal–though control certainly is. In our EID article, we outline all the evidence that supports the hypothesis (around since the 1960s) that (1) African monkeys and apes are infected with yaws and (2) they may be capable of spreading the infection to humans. Infection via animals could help explain the mysterious cases encountered during the first campaign, when infected individuals would turn up in a previously treated population, having had no contact with any infected people as far as anyone could tell.

The WHO announced a second yaws eradication campaign recently, but it doesn’t seem as though much thought has been given to the problem of an animal reservoir. People involved in the first eradication campaign were calling for further research into the potential problem of simian yaws as early as the 1960s, but this history seems to have been largely forgotten. That’s unfortunate. Eradication campaigns are incredibly expensive. In the end, the cost of finding and treating cases skyrockets, because it entails going to remote and dangerous places to treat the very last hidden cases of an infection on earth. The polio eradication campaign has been going on for years and years longer than was originally planned, and we have spent much, much more than was originally budgeted because of these difficulties. Eradication campaigns also put a tremendous financial burden on the countries involved, as well as sponsor organizations such as the WHO. Money spent on yaws eradication (vs. simple yaws control) is money that low income countries cannot spend on other important health problems, like HIV, tuberculosis, and the childhood infections that represent huge sources of mortality. There is a huge opportunity cost involved. (Side note: a great book on the drawbacks of the polio eradication campaign, relevant to eradication campaigns in general, is William Muraskin’s Polio Eradication and its Discontents.) If we decide to launch a new eradication campaign, we need to make sure that we can actually carry it out, so that the resources we expend will have been well spent.

Our argument in this letter in a nutshell: before throwing a massive amount of resources behind another eradication campaign, it makes sense to do our due diligence and make sure that an animal reservoir is not going to torpedo yaws eradication for a second time.

Does the flu vaccine cause Guillain-Barré syndrome or not?

urlGuillain-Barré syndrome (GBS) is a pretty scary condition. It starts with weakness and tingling in the extremities and can eventually leading to paralysis. Although most people recover in time, death can occur. Luckily, it’s a rare disease. It’s thought to result from an autoimmune process in which peripheral nerves are demyelinated and destroyed.

What causes GBS? Infections seem to be a major trigger. In about two-thirds of cases, the syndrome is preceded by either a gastrointestinal or respiratory infection. Campylobacter enteritis seems to be the most common trigger, but influenza, cytomegalovirus, Epstein-Barr virus, and HIV have all been implicated too. It appears that, in rare cases, these pathogens trigger the autoimmune cascade that leads to the diseases.

The 1976 H1N1 vaccine and GBS

Way back in 1976, researchers noticed something scary. 1976 was the year of the big swine flu epidemic scare. In February of that year, two army recruits at Fort Dix, in New Jersey, tested positive for swine flu. Researchers believed the strain they were infected with was similar to the one that had caused the 1918 flu pandemic that had killed millions. When they looked a little harder, they found that hundreds of other recruits at the base had been infected as well. Because these were not folks that had contact with pigs, it meant that the virus was spreading from person to person. Naturally, people were nervous. The government decided it would produce a vaccine against this strain and vaccinate as many people as possible, in order to head off what it feared might be a terrible pandemic.

Something strange happened though. Cases of GBS in people who had received the flu vaccine started cropping up. Hundreds of them. In 2009, The New York Times ran the story of Janet Kinny, a woman who developed GBS after receiving the shot in 1976. GBS put this young mother in the hospital for a month, paralyzed from the neck down. She recovered, but not everyone was so lucky. More than 30 of the people who developed GBS after getting a flu shot that year died. Epidemiologists spent a while debating whether or not this cluster was just a coincidence. In the end, most agreed that the shot really was associated with an increased risk of GBS. Researcher Lawrence Schonberger estimated that people who received the 1976 flu shot were roughly 7 times more likely to develop GBS than people who did not. For every 100,000 people vaccinated, approximately one got GBS. In December 1976, after having immunized more than 40 million people and failing to see evidence that the H1N1 pandemic was actually going to materialize, government officials called off the vaccination campaign due to the GBS risk.

Not surprisingly, people became wary of flu vaccines. Nobody wants to get GBS. A lot of work has been done over the years to try to clarify the risk that flu shots pose, but GBS is such a rare condition that it has been hard to put together studies large enough to shed light on this problem. Well, this year, three important studies on the flu vaccine and GBS came out. These were huge studies that each looked at millions of people, and they’ve provided a lot of insight into the relationship between vaccines and GBS.

2013: The year of gigantic flu shot/GBS studies

The first study appeared in Clinical Infectious Diseases. The authors mined data collected over 13 years (from 1994–2006) by Kaiser Permanente. Those of you from the West Coast know that Kaiser Permanente is a big insurer/hospital system with tons of clients. Using records for 3 million of patients, they were able to identify 415 confirmed cases of GBS. Sure enough, exactly two-thirds of these patients had suffered a respiratory and/or gastrointestinal illness in the 90 days preceding the onset of their GBS. But only 25 had received a vaccine of any kind in the 6 weeks prior to onset. In this study, GBS was NOT associated with getting a prior flu shot. However, the authors pointed out they could not rule out a very small increased risk of GBS; it’s always possible that with a larger sample size (i.e. more cases) they would have increased power to identify a small association.

Another even larger study appeared in the Lancet Infectious Diseases, and it, too, focused on seasonal flu vaccines. Carried out using the universal health care system records in Ontario, Canada, it was able to identify 2,831 incidents of GBS between the years of 1993 and 2011. The authors of this study found that the risk of developing GBS was roughly 50% higher in the six weeks following a seasonal flu shot, vs the risk experienced 9–42 weeks after. Thus, there really did seem to be a small, increased risk of GBS associated with seasonal flu shots. However, the authors found that actually GETTING the flu was a much bigger risk factor for GBS. In the six weeks after seeking medical help for the flu, the risk of GBS was roughly 16 times greater (vs 1.5 times for the shot) than in the weeks following the danger period. To put these findings in context: For every million people vaccinated with the flu shot, about 1 would get GBS, and for every million people who got the flu, 17 would get GBS.

The third study appeared in The Lancet, and it focused on the flu vaccine in one special year: 2009. You may remember that 2009 was the year of another H1N1 swine flu scare (and thus another H1N1 swine flu vaccine). So if any flu shot was linked to a greater risk of GBS, as in 1976, it seems like it would be this one. When focusing on this single year, researchers found an increase in GBS cases associated with the vaccine. Of the 23 million people who received the H1N1 vaccine and were included in the study, 54 developed GBS within 6 weeks of the shot. This works out to be about 1.6 extra GBS cases for every million people vaccinated. Thus, there WAS a slightly higher risk of GBS linked to the shot–but it was tiny. So tiny, the authors point out, that most studies of seasonal flu vaccines simply wouldn’t be large enough to detect the association. The sample size issue may well explain why the first study (based on the Kaiser Permanente data) did not identify an association between flu vaccines and GBS.

The take-home message: the extremely low risk of vaccine-related GBS is outweighed by the much higher risk of flu complications

So it appears that there is a small risk of GBS associated with flu vaccines. But, as flu researchers have been quick to point out, the risk associated with actually GETTING the flu is much higher. Poland and colleagues have posed a thought experiment in the Lancet on this subject. They point out that if everyone in the US had gotten the 2009 H1N1 vaccine, it’s estimated that 22 vaccine-related deaths would have occurred. But it everyone had gotten the H1N1 flu, 12,470 deaths would have occurred. Although the side-effects of a vaccine loom large in our minds, it’s important to put these risks in perspective: most vaccines prevent dangerous diseases, so foregoing a vaccine poses its own (often much greater) risks.

These modern studies still don’t explain exactly what happened in 1976. Why did that particular vaccine cause the syndrome at such a high rate (1 per 100,000 vs. 1 per 1,000,000 for modern vaccines)? Nobody knows. One explanation for the increased GBS risk is that the vaccine was contaminated with a bacterial trigger like Campylobacter.  Another explanation, which seems more plausible, is that something in the vaccine resembled nerve cells–so that when a recipient’s body mounted an attack against the vaccine, the attack might have hurt nerve cells as well. It would be comforting if, eventually, we could identify the problem.