Dr. Paul Offit just wrote a book called Pandora’s Lab: Seven Stories of Science Gone Wrong, which not about an evil black dog that escaped from a box, but rather, seven instances when the march of scientific progress headed off a cliff rather than in the desired direction. People died. Many people died. Other bad things happened.

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Note: I interviewed Paul Offit about his book on Atheist Talk Radio. This interview will be aired on Sunday, May 28th, and will be available as a podcast. It should be HERE.
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Readers will have different reactions to, and ways to relate to, each of the seven different stories, because they are far flung and cover a great deal of time, diverse social settings, and a wide range of scientific endeavors. Some readers will get mad because he talks about DDT and Rachel Carson, though I assure you his argument is mostly reasonable (I did disagree with some parts). All readers will be amazed at the poppy plant and all it can do and has done, and astonished at the immense apparent ignorance displayed by that plant’s exploiters, from back in the early 19th century to, well, yesterday. Those interested in race and racism, the use of poison gas to kill people, will find things you didn’t know in Offit’s carefully researched histories. Also, don’t forget to take your vitamins. Or, maybe, forget to take your vitamins.

The chapter “The Great Margarine Mistake” is a great example of the very commonly screwed up interface between food science, food production and marketing, and the shaping of food preference among regular people. You know, that thing where “They tell us not to drink coffee. Then they tell us to drink coffee. They don’t know nothin'”

My biggest disagreement with Paul is over malaria. He did not incorporate an often overlooked fact about the disease into his discussion, and had he done so, may have written a somewhat different chapter. Briefly, in zones where there are two wet seasons (or one long wet season and a very short dry season) there has never really been success in curtailing malaria. In zones where there is a very long dry season but it is wet enough for part of the year for the mosquito that carries malaria to exist at least most years, malaria is relatively easy to beat down using a wide range of techniques, no one of which is supreme. So, for example, today, the distribution of malaria in South Africa, where it is not actually that common (thousands of cases in a normal year among tens of millions of people) is determined mainly by how wet the eastern wet season is, integrated with the movement into that area of people, usually refugees, who are a) infected and b) not getting medical treatment. (See this.)

Malaria was wiped out in country after country prior to the use of DDT, then the DDT came in and helped a great deal, in those relatively dry countries. But the wet countries, not so much. Indeed, in a place like Zaire, there are absolutely no reliable statistics on how common Malaria is or ever was over most of the country, but when I lived there in the 1980s, it was as common as the common cold in New Jersey, and DDT was theoretically in use. (That is a second correlation with causation: the wetter the equatorial country, the less we actually know about disease. I recall leaving the deep rain forest to visit the “city” to get hold of a few courses of leprosy medicine for a handful of people who visited our clinic who had it, where I had dinner with a guy from the UN who was on his victory lap for having wiped out leprosy in Africa.)

In some ways, Offit’s final chapter is the most interesting, the eighth chapter (combined with the Epilog) in which he does two things. One is to identify the kind of reasoning mistake, or methodological mistake, each of his seven examples exemplifies. Such as failure to pay attention to the data, or failure to pay attention to the man behind the curtain. The other is to go quickly through what may end up being similar stories of science gone wrong just starting to brew today or in recent decades, such as the long term unintended effects of widespread use of antibiotics.

A question that Offit’s book raises, indirectly, is this: When a Pandora-like box opens and some sort of monster creeps out, why did the box open to begin with? Sometimes it is jostled open, like in the case of unintended negative outcomes from the use of antibiotics. Sometimes it is opened because someone can’t resist the treasures that may be inside. Sometimes it is opened because science is an open process and must always seek knowledge etc. etc. I wonder if the recent development of an engineered polio virus (three instances), or the Spanish Flu, is an example of such. Sometimes it is opened because of (Godwin Warning!) HITLER. Seriously.

I don’t know what knowing these reasons gets us, but one possibility is this: when we find ignorance as a root cause of calamity, perhaps an appreciation of knowledge is gained. That is certainly the lesson of Offit’s review of the products of opium, their invention, intensification, deployment, and use. Apparently addiction was simply not understood at all until fairly recently, and that lack of understanding caused science, medical technology, and medical practice to do the exactly wrong thing over and over again.

And of course, lobotomies. The invention of the latter method of doing this useless and horrible procedure is something that, if put in a movie as a plot element, would kill the movie because it is not possible to suspend disbelief to the degree necessary to stay seated in the theater.

Pandora’s Lab: Seven Stories of Science Gone Wrong is a great read and a necessary addition to the bookshelf of any practicing skeptic or science enthusiast.

Paul Offit, who is a pediatrician and the inventor of a rotavirus vaccine (see this for an interesting podcast on a related topic), is the Maurice R. Hilleman Professor of Vaccinology and Professor of Pediatrics at the Perelman School of Medicine, University of Pennsylvania. He is also chief of Infectious Diseases and director of Vaccine Education at the Children’s Hospital of Philadelphia.

Aside from Pandra’s Lab, he also wrote Do You Believe in Magic?: Vitamins, Supplements, and All Things Natural: A Look Behind the Curtain, Deadly Choices: How the Anti-Vaccine Movement Threatens Us All, and Bad Faith: When Religious Belief Undermines Modern Medicine.

Since the Ebola outbreak began in February, around 300,000 people have died from malaria, while tuberculosis has likely claimed over 600,000 lives. Ebola might have our attention, but it’s not even close to being the biggest problem in Africa right now. Even Lassa fever, which shares many of the terrifying symptoms of Ebola (including bleeding from the eyelids), kills many more than Ebola – and frequently finds its way to the US.

I’m not picking on James Bell here. A lot of people said things like this, and the facts are true, though as I said, there is almost always (actually, in exactly N-1 scenarios within a given domain of scenarios) an argument that goes like this, and it really isn’t particularly relevant unless one is tasked with dividing up a fixed set of resources that will be used for a fixed set of problems. Resources rarely come that way and problems are rarely solved that way. As I pointed out earlier, consider the thought experiment where you have $10,000,000 that you want to give to either developing an Ebola vaccine, or a Malaria vaccine. Since billions have been spent on developing a Malaria vaccine and there still isn’t one, your donation would be a drop in the bucket. Retrospectively, it would be equivalent to something like the combined costs of couriers and mail by researchers working on a Malaria vaccine over the last few decades. Or the cost of coffee and donuts in the break room. Or conference travel fees. Or something like that. The point is, a bunch of millions of dollars might actually produce an Ebola vaccine given the starting point we have now, or at least, move us a good deal in that direction.

But now, we can ask if Ebola in the countries that are heavily affected right now is still “minor” compared to Malaria.

This is a matter of numbers and the numbers are hard to come by. James Bell notes that between February and July, inclusively, there had been over 300,000 malaria deaths, I assume world wide. So the comparison is not really relevant; we should be looking at what is happening specifically in, for instance, Liberia, Guinea, and Sierra Leone (or the three combined perhaps). Comparing world wide figures to a regional outbreak is a bit like reducing the Malaria death rate by shifting from numbers from countries that have endemic Malaria to include the global population.

It is hard to know how many people die of malaria every year, and the quality of the data varies considerably from country to country. A fairly recent study (here’s a discussion of it) suggests that an older estimate of 600,000 deaths per year should be doubles to 1,200,000 deaths per years. Having worked and lived in a region with some of the worst malaria (measured numerous ways) for several years, I can easily accept a doubling of numbers. If we assume that 1.2 million is right, by the way, Bell’s number of 300,000 is actually conservative.

Using data from that malaria study and WHO’s Ebola data, we can make some comparisons. I’m including all the information so you can check my work.

Here we have data from Liberia, Guinea, and Sierra Leone. The population number and malaria deaths per year are both from the aforementioned study and pertain to 2012. Then I divided malaria deaths per year by 12 to get a monthly value. I’m more comfortable working in months than years because an Ebola outbreak is normally short lived, and the number of deaths changes dramatically from month to month.

Following this we have the total number of Ebola deaths per country (summed in the right hand column as are the above mentioned data) and the approximate number of months of the outbreak. Then, the total deaths divided by the number of months. This constitutes a low-ball estimate of deaths per month from Ebola for the given expanding outbreak. Here we can see that in the comparison between Malaria and Ebola, it is not clear that one is a greater threat than the other (142:92, 49:67, 145:144).

Then we have the August-only monthly number of deaths. Here we dee that Ebola is huge compared to Malaria. So, back when people were saying “Malaria is worse,” in late July and early August, Ebola was starting to prove them wrong.

The last two numbers are calculated for all three countries combined. Here we are going out on a limb, and it is better statistically to crawl out on a thicker limb than a thinner limb. I made some estimates here, and those numbers conform to what is being talked about by WHO and others. If Ebola continues to spread at its current rate the daily number of new cases could be between 150 and 300 by the beginning of January. I state these as low vs high estimates, but actually, they are both conservative. Multiplying this by 30 days in a month, and dividing by 2 to approximate the ca 50% mortality rate, we have conservative numbers for Ebola that leave Malaria in the dust. Even if the doubling of estimated Malaria death rates should be doubled again, Ebola will be a bigger factor than Malaria.

So that is why we should stop saying that Ebola is not Malaria, so relax about Ebola.

More on Ebola:

• Two Ways Hollywood and Literature Have Confused The Ebola Problem
• Ebola in Dallas Texas: Is our response adequate?
• Ebola Will Not Become Airborne And Here Is Why
• Has the Ebola Death Toll Surpassed Malaria in West Africa?
• Which countries are the hardest hit?

We identify and evaluate 1916 immunization studies between 1965-February 2010, and exclude partially or nonprotective results to find 177 completely protective immunization experiments. Detailed reexamination reveals an unexpectedly mundane basis for selective vaccine failure: live malaria parasites in the skin inhibit vaccine function. We next show published molecular and cellular data support a testable, novel model where parasite-host interactions in the skin induce malaria-specific regulatory T cells, and subvert early antigen-specific immunity to parasite-specific immunotolerance. This ensures infection and tolerance to reinfection. Exposure to Plasmodium-infected mosquito bites therefore systematically triggers immunosuppression of endemic vaccine-elicited responses. The extensive vaccine trial data solidly substantiate this model experimentally.

Crap, that’s bad news.

But wait, there may be a way to make a malaria vaccine anyway, and the latest reports from Britain are quite positive.

The long-awaited results of the largest-ever malaria vaccine study, involving 15,460 babies and small children, show that it could massively reduce the impact of the much-feared killer disease. Malaria takes nearly 800,000 lives every year – most of them children under five. It damages many more.

The vaccine has been in development for two decades – the brainchild of scientists at the UK drug company GlaxoSmithKline, which has promised to sell it at no more than a fraction over cost-price, with the excess being ploughed back into further tropical disease research.

“This data bring us to the cusp of having the world’s first malaria vaccine, which has the potential to significantly improve the outlook for children living in malaria endemic regions across Africa,” said GSK’s chief executive, Andrew Witty.

“The addition of a malaria vaccine to existing control interventions such as bed nets and insecticide spraying could potentially help prevent millions of cases of this debilitating disease. It could also reduce the burden on hospital services, freeing up much needed beds to treat other patients who often live in remote villages, with little or no access to healthcare.”

Here it is in the Guardian.

Researchers working in Burkina Faso recently decided to test the hypothesis that beer drinking would have an effect on mosquito prey preference, and they found that it did. Twenty-five human volunteers drank beer and were explosed to 2,500 A. gambiae mosquitoes, and 18 volunteers drank only water and were exposed to 1,800 A. gambiae mosquitoes (100 mosquitoes per volunteer). The behavior of the mosquitoes was observed, and it was determined that they go after the beer-drinkers preferentially.

The volunteers, healthy adult male Burkinabe not using medicine of any kind were instructed to avoid deodorants and beer on the day of the trial. The beer was a local dolo made of sorghum, the commonly consumed beer for the region. The amount of beer or water consumed for each person was one liter.

There were two trials separated by 15 minutes, with the drinking of the beer or water in between. A gadget called the Y-olfactometer was used to measure the human odors, and was set up like so:

(A) The two tents set up outdoors and connected to the two traps of the Y-olfactometer by lay-flat tubing, and the olfactometer room located between the two tents. (B) Fan drawing air from a tent to the olfactometer via lay-flat tubing. (C) The Y tube-olfactometer.

Batches of 50 mosquitoes were released into the downwind box of the Y-olfactometer (figure 1C) and given a choice between outdoor air and human odour. They were allowed to respond for 30 min. During this time frame, mosquitoes that responded to the stimuli left the downwind box and flew upwind into the traps from which they were retrieved (figure 1C). At the end of each test, the mosquitoes inside the two traps were removed with an aspirator and counted.

Various statistical analyses were done, but the results are best indicated in the following graph:

(A) Effects of beer (n = 25 volunteers) or water (n = 18 volunteers) consumption on mosquito activation, expressed as the proportion of mosquitoes caught in both traps out of the total number released in the downwind box of the Y-olfactometer. In parentheses are the total numbers of mosquitoes entering both traps. (B) Effects of beer (n = 25 volunteers) or water (n = 18 volunteers) consumption on the mosquito orientation, expressed as the proportion of mosquitoes caught in the odour-baited trap out of the total number retrieved from both traps. In parentheses are indicated the numbers of mosquitoes entering the volunteer odour-baited trap. Error bars show 95% confidence interval of the mean proportion. Asterisks indicate significant effect of treatments on the response variables (GLMM); ns = not significant; *** = P<0.001.

So, drinking beer = more likely to get bit by potentially malaria-carrying A. gambiae mosquitoes. But why? It is not clear. Pregnant women seem to be more often targeted by A. gambiae because of increased body temperatures and exhaled breath. In this study, however, no increase in body temperature was observed; Temperatures of beer-drinkers actually went down, no up. There was no increase of exhaled breath either.

It is possible that mosquitoes track beer drinkers adaptively. It is probably easier to bite an intoxicated person and get away alive. There is no direct evidence for this in the current study, but it is an interesting idea.

We postulate that the metabolism of alcohol following beer consumption induces changes in breath and odour markers (i.e. increases the production of kairomones such as 1-octen-3-ol) that increases attractiveness to An. gambiae. Beyond this coincidental side effect of beer consumption, mosquitoes may have evolved preferences for people who recently consumed beer – possibly due to reduced host defensive behaviours or highly nutritious blood-meals. This hypothesis is appealing but requires further investigations.

The paper, published in PLoS ONE, is available here. Full citation:

Lefèvre, T., Gouagna, L., Dabiré, K., Elguero, E., Fontenille, D., Renaud, F., Costantini, C., & Thomas, F. (2010). Beer Consumption Increases Human Attractiveness to Malaria Mosquitoes PLoS ONE, 5 (3) DOI: 10.1371/journal.pone.0009546

Other references:

Lindsay S, Ansell J, Selman C, Cox V, Hamilton K, et al. (2000) Effect of pregnancy on exposure to malaria mosquitoes. Lancet 355: 1972.

Ansell J, Hamilton KA, Pinder M, Walraven GEL, Lindsay SW (2002) Short-range attractiveness of pregnant women to Anopheles gambiae mosquitoes. Trans R Soc Trop Med Hyg 96: 113-116.

Himeidan YE, Elbashir MI, Adam I (2004) Attractiveness of pregnant women to the malaria vector, Anopheles arabiensis, in Sudan. Ann Trop Med Parasitol 98: 631-3.