I focus on 4 major challenges for malaria control with which economics can assist: In the first chapter I use optimal control and dynamic programming techniques to focus on the problem of insecticide resistance in malaria control, and to understand how different models of mosquito evolution can affect our policy prescriptions for dealing with the problem of insecticide resistance. In the 2nd chapter, I consider the interaction between parasite resistance to drugs and mosquito resistance to insecticides, and use a mass-action epidemiological model to analyze cost-effective malaria control portfolios that balance these 2 dynamics. In the 3rd chapter, I analyze results from a discrete choice experiment (DCE) of households in northern Uganda to elicit preferences for different attributes of indoor residual spraying programs (IRS) to control malaria-transmitting mosquitoes. In particular, I evaluate: (a) the elasticity of household participation levels in IRS programs with respect to malaria risk; and (b) households’ perceived value of programs aimed at reducing malaria risk, such as IRS. Continue reading
Most of you will probably be familiar with the practice of female genital mutilation (FGM), in which a woman’s external genitalia is partially or totally removed. As per Wikipedia, there are four types of FGM:
The main three are Type I, removal of the clitoral hood, almost invariably accompanied by removal of the clitoris itself (clitoridectomy); Type II, removal of the clitoris and inner labia; and Type III (infibulation), removal of all or part of the inner and outer labia, and usually the clitoris, and the fusion of the wound, leaving a small hole for the passage of urine and menstrual blood—the fused wound is opened for intercourse and childbirth.
The fourth type of FGM covers procedures that do not neatly fit in the above three categories.
I am currently working on a paper on FGM with a former student of mine, Tara Steinmetz. But because we are planning on submitting our paper to a medical journal (and because medical journals are serious about researchers not posting their findings anywhere pre-publication), you will have to wait until our paper is published to hear about our findings.
Rather, the reason why I bring up FGM is because Linda Raftree had an excellent write up on her blog last week about another similarly disturbing practice which I had not yet heard of — breast flattening:
“Breast flattening,” also known as “breast ironing” or “breast massage,” is a practice whereby a young girl’s developing breasts are massaged, pounded, pressed, or patted with an object, usually heated in a wooden fire, to make them stop developing, grow more slowly or disappear completely.
(…) [B]reast flattening is practiced out of a desire to delay a girl’s physical development and reduce the risk of promiscuous behavior. Proponents of the practice consider that “men will pursue ‘developed’ girls and that girl children are not able to cope with or deter men’s attention. They see that promiscuity can result in early pregnancy, which limits educational, career, and marriage opportunities, shames the family, increases costs to family (newborn, loss of bride price, health complications from early childbirth or unsafe abortion).” In addition, there is the belief that girls are not sufficiently intellectually developed to learn about puberty, and therefore should not yet develop breasts. Another reason given for the practice is the belief that girls who develop before their classmates will be the target of teasing and become social outcasts. There is also, for some, the belief that large breasts are unattractive or not fashionable.
My colleague and mentor Don Taylor claims that the existence of FGM can serve as a litmus test to assess whether someone is a true relativist — a true-blue relativist would be okay with FGM.
While I agree that promiscuity can result in very bad outcomes for young women, I find the argument that girls are not sufficiently intellectually developed to learn about sexual and reproductive health particularly repugnant, especially when it leads to practices such as breast flattening. But then again, I am most definitely not a relativist.
Last Thursday was an important day for me, for personal reasons: it was the third anniversary of my quitting smoking.
After about 15 years of heavy smoking — a little over one, but sometimes up to two packs a day — I finally managed to quit in February 2009.
That last attempt at quitting smoking was my sixth or seventh attempt at quitting smoking. The first time I tried to quit smoking, when I was 19, I lasted a few hours. The penultimate time, I did not smoke for about six months.
This leads me to the following little-known fact about quitting smoking:
“Most people who quit smoking for good only do so at their fifth or sixth quitting attempt.”
I had no idea until I walked in my colleague Don Taylor‘s office one day after yet another failed attempt at quitting and said: “Screw it, I don’t think I’ll ever be able to quit smoking.” Don, who is a health policy scholar and who blogs over at the Incidental Economist, responded by quoting the stylized fact above, which is apparently well-known among health policy scholars.
It might be well-known among health policy scholars, but I feel like it deserves to be publicized widely. Every failed attempt at quitting smoking is very disheartening, as it brings a real sense of failure. How many people might have given up on the idea of quitting because of that sense of failure? How many people would have kept going had they been told that most people who quit smoking for good only do so at their fifth or sixth attempt?
If you know anyone who smokes and wants to quit smoking — and what smoker does not want to quit smoking? — the best thing you can do for them is to tell them about the stylized fact above, and not to give up. There is definitely a learning process. And if they want an actual source, they can check out the 1990 report of the surgeon general on smoking cessation.
One caveat is observational studies, where you identify a large cohort of people – say 80,000 people like in the Nurse’s Health Study – and you ask them what they eat. You give them diet and food frequency questionnaires that are almost impossible to fill out and you follow them for 20 years. If you look and see who is healthier, you’ll find out that people who were mostly vegetarians tend to live longer and have less cancer and diabetes than people who get most of their fat and protein from animal products. The assumption by the researchers is that this is causal – that the only difference between mostly vegetarians and mostly meat-eaters is how many vegetables and how much meat they eat.
I’ve argued that this assumption is naïve almost beyond belief. In this case, vegetarians or mostly vegetarian people are more health conscious. That’s why they’ve chosen to eat like this. They’re better educated than the mostly meat-eaters, they’re in a higher socioeconomic bracket, they have better doctors, they have better medical advice, they engage in other health conscious activities like walking, they smoke less. There’s a whole slew of things that goes with vegetarianism and leaning towards a vegetarian diet. You can’t use these observational studies to imply cause and effect. To me, it’s one of the most extreme examples of bad science in the nutrition field.
That’s Gary Taubes in a FiveBooks interview over at The Browser. Taubes is better known for his book Good Calories, Bad Calories, in which he argues that a diet rich in carbohydrates is what makes us fat and, eventually, sick, and in which he argues in favor of an alternative diet rich in fats.
I really don’t know what kind of diet is best for weight loss, but I do want to stress Taubes’ point about the weakness of observational studies, even longitudinal ones. It is not uncommon for social science researchers to say “Well, we’ve been following these people over time, so we can use fixed effects to control for unobserved heterogeneity.” That is, they control for what remains constant for each unit of observation over time, which is made possible because they have more than one observation for each unit of observation. I have certainly been guilty of that. Continue reading