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Juliet Bowater

Could parasites be making vaccinations less effective in developing countries?

According to a recent study, they could be.

An NIH-funded paper published earlier this year 

if mothers-to-be had malaria, schistosomiasis, or hookworm infections during their pregnancy, their babies were less well-protected by some vaccines.

 This may help to explain why some vaccines are less effective in areas of developing nations 

In the study, babies were given a vaccination which protects against five diseases – diphtheria, tetanus, pertussis, Hib (a cause of meningitis and septicaemia) and hepatitis B – and the level of protection produced in response to the Hib, hepatitis B, diphtheria and tetanus components were then measured. Parasite infections affected how much protection was given by the Hib and diphtheria components of the vaccine.

For the Hib component, babies from mothers who had been infected with malaria, filariasis or hook-worm gained less protection from the vaccine than those whose mothers did not have those infections. This suggests that the worm infection in the mother reduced the effect of the vaccines in the babies.

The picture gets more complicated when the mother has more than one infection. It has been known for some time that parasites use high level evasion tactics to avoid the immune system, and that this may stop vaccines from working so well

. As an example, BCG vaccinations provide less protection against tuberculosis in people who have a worm burden than those who don’t 

.In their attempts to avoid elimination by the immune system, parasites end up triggering off a range of immunological functions, sometimes with counter-intuitive effects.

For instance, babies whose mothers had malaria had less protection from the Hib vaccine than those whose mothers were malaria-free. Babies whose mothers had worm infection also had less protection. But babies whose mothers had BOTH malaria and worm infection had a better response to the vaccine than those whose mothers only had malaria. So, in this case, the combination of worms and malaria works on the side of the vaccine, making the response less bad.

To make it even more complicated, there is a different response to the part of the vaccine that protects against diphtheria. Here, malaria infection in the mother had little effect, and worm infection in the mother also had little effect, but babies whose mothers suffered from both malaria and worms had a worse response to the vaccine.

So what’s going on here? Why the different response?

Parasites’ tactics include complex communications trickery, signalling the immune system to err towards tolerance rather than aggression. The signals caused by the parasites in pregnant mothers may end up pushing their babies’ immune systems into having a more tolerant and less aggressive response as well. Unfortunately, the processes which are involved in producing an aggressive immune response are important in gaining protection from many vaccines 

The constant balancing act between tolerance and aggression is in part controlled by immune players called Th1 and Th2 cells. Each produces a cocktail of self-interested chemicals to keep its philosophy on top. Once a Th1 response starts, it tends to keep going at the expense of the Th2 response, and vice-versa 

. Any upset to the normal Th1:Th2 balance is likely to make the vaccine response less effective.

Parasites like intestinal worms push for a Th2 response 

, which is less aggressive and more tolerant. But the more aggressive Th1 response is normally what’s required for vaccines to give good protection against diseases.

Malaria is well-known for suppressing the immune system and paralysing vital components to suit its own ends, as well as being hugely damaging to pregnancies, increasing the risk of premature birth, miscarriage, low birth weight and infant mortality 

, so treatment during pregnancy is important 

. However, in this situation, the malaria parasite may be inadvertently causing some immune-system rebalancing. Malaria parasites can infect the placenta, pushing towards a more aggressive, Th1 response in the baby 

 and potentially contributing to re-balancing the Th1:Th2 response. The malaria parasite in the mother may also increase the work of an immune-balancing cell in the baby 

To top off this complex immunological mash-up, material from infections in pregnant mothers doesn’t tend have a hostile reception when it reaches their unborn children. Instead, it causes the production of cells and chemicals designed to avoid immunological warfare between the mother and baby during pregnancy 

. But the result is a calming of the immune system, which doesn’t fit well with good protection from the vaccine.

What does this mean for reducing disease?

The interactions between parasites and the immune system are by no means simple, so predicting what will happen if you remove one of the players is often not straightforward. However, this paper does provide more evidence that 

removal of parasite burden would be a good thing for vaccination efforts. It also shows the importance of considering how different infections interact with each other during pregnancy, and understanding the full implications of channelling resources towards any one particular disease.

The Giving What We Can top charity recommendations currently include organisations devoted to tackling neglected tropical diseases, such as 

, which distributes insecticide-treated mosquito nets. 

Research like this further improves the case for donating to these highly effective charities, highlighting the multi-faceted and potentially surprising effects of parasite infection.

Thomas Sittler

Did iodized salt raise the IQ of 50 million Americans by 15 points?

Iodine deficiency disorders are prevalent in many African countries, where they make up a substantial part of the overall disease burden. But iodine deficiency can be treated cheaply by iodizing table salt on an industrial scale.

A recent meta-analysis of randomized controlled trials found that iodine fortified foods are associated with increased urinary iodine concentration among children

. This is particularly important given that iodine seems to be crucial for normal physiological and cognitive growth and development of children

Iodine nutrition based on the median urinary iodine concentration, by country 

 and its relationship to mental development in children. We had found a systematic review and meta-analysis that looked at the effects of iodine supplementation on the 

. The authors concluded that evidence from recent studies suggests iodine-deficient children suffer a loss of 6.9-10.2 IQ points as compared with children who are not iodine-deficient. However, the authors caution that some study designs were weak and call for more research on the relation between iodized salt and mental development.

Disability-adjusted life years (DALYs) (thousands) lost due to iodine deficiency in children younger than 5 years of age, by region 

Now two recent natural experiments provide more evidence that salt iodization might be beneficial for mental development: one study showed that in iodine-deficient regions of the United States in the 1920s, salt iodization raised IQ scores of millions of people by 15 IQ points! 

 The other study suggests that in Switzerland, iodization has improved female labour participation rates. As these studies could substantially update our views on the relative effectiveness of salt iodization programmes - we have reviewed and scrutinized the studies in more detail below.

Iodine deficiency, a leading cause of preventable neurodevelopmental disorders, has been largely eliminated in developed countries due to the addition of iodine to table salt, but remains a problem in many developing countries. Iodine is inexpensive and salt is already being consumed being consumed by most people in the world, and so large-scale salt iodisation programmes may be highly cost effective.

Figure 1: Iodine deficiency global map 2014-2015

 on salt iodisation. GiveWell investigated “Several small-scale randomized controlled trials (RCTs) [which] examined the effect of iodine supplementation of children on their mental function”, and estimated the effect size to be 0.24 standard deviations, or about 4 IQ points increase due to iodine supplements. In these trials, iodised products were given directly to the families. Therefore, GiveWell also separately looked at the track record of large-scale salt iodization in order to determine whether such programmes really do increase iodine intake, and concluded “We believe there is a reasonably strong case that countrywide salt iodization efforts have successfully reduced iodine deficiency”.

Some new evidence about salt iodisation has not been considered so far. Two recent papers, 

, look at the effects of the large-scale introduction of iodised salt in the 1920s in the United States and Switzerland, respectively. They consider the impact of salt iodisation during pregnancy on cognitive performance later in life. 

The headline claim of these studies is that salt iodisation had large effects on cognitive outcomes: iodisation increased the IQ of iodine deficient people by 15 IQ points in the United States, and accounts for roughly 10% of a 20-year increase in school graduation rates in Switzerland. Should we believe these claims?

, and as “standout charities”, and explains that the major unresolved issue with these charities is that GiveWell has “thus far been unable to document a demonstrable track record of impact; we believe it may have had significant impacts but we are unable to be confident in this with what we know now.” Essentially, since these charities assist governments and salt producers in iodising salt, the counterfactual impact (what would have happened if not for the charity?) is very difficult to assess.

It’s reasonable at this point to ask: If we agree that salt iodisation is effective, but we have difficulty finding charities to recommend, then what is the point of looking at other evidence? Can any evidence about the effect size of salt iodisation change our view about which charities we should donate to? The answer is that even if we remain very uncertain about the counterfactual impact of iodine charities, increasing our estimate of the effect size of iodisation increases the expected value of donating to these charities. If we believe that the effect size of iodization on intelligence is larger than previously estimated, then it may become worthwhile to donate to iodisation charities despite the uncertainty. A second reason is that a bigger increase in IQ would warrant additional evaluation of whether iodine charities really do have counterfactual impact.

There are two other reasons why the evidence from Weil and colleagues (2013) and Politi (2010) is interesting to look at. First, these papers primarily look at the effect of salt iodisation during pregnancy, which might be a particularly critical neurodevelopmental period, and not only during childhood. Second, the randomized trials separately examine (i) the evidence for the cognitive benefits of higher iodine intake and (ii) the evidence that large-scale iodisation programmes really lead to higher iodine intake. But the papers discussed in this post sidestep the need for such external validity checks by looking directly at the effects of large-scale iodisation.

What are the claims made by Politi (2010) and Weil et al. (2013)?

These studies are so-called natural experiments. Natural experiments are observational studies that exploit the natural occurrence of quasi-random assignment to a treatment or control group. The advantages of natural experiments are that there is no need to do the costly randomisation oneself, and that they usually have much larger sample sizes and can follow ‘participants’ over long stretches of time. Their main disadvantage is that we can never be certain that the assignment was sufficiently random; the claim of randomness must be carefully checked. Rather than using heuristics such as “only look at true randomisations”, it may be better to carefully check the quality of individual quasi-randomised studies, especially when they claim large effect sizes.

Iodised salt was rapidly introduced in the 1920s in Switzerland and the United States. The level of iodine deficiency varied considerably between geographical regions. We would expect iodine supplementation from salt to have an effect on iodine-deficient regions (treatment) and no effect on iodine-sufficient regions (control). We can measure the effect of iodisation by looking at the 

 between deficient and sufficient regions, before and after iodisation. The essential assumption underlying this approach is that the response to iodine is not linear, i.e. that the effect is much larger for people who are iodine deficient than for people who have sufficient iodine. I will now examine the two studies in more detail.

Evaluating Weil et al. (2013): Salt iodisation in the United States

In the United States, salt iodization programmes were rapidly rolled out at the beginning of 1924. The authors exploit this by comparing the outcomes of children born before and after 1924, from iodine deficient and iodine sufficient regions. To find out whether iodine had an effect on IQ, they collect data on both iodine levels in different areas before iodization, and data on cognitive abilities of people born before and after 1924.

The authors of this paper went to great lengths to infer this information from existing data sets. Understanding their process requires a bit of background information. Goitre is a swelling of the thyroid gland caused by iodine deficiency. During WW1, all draftees were given a medical examination, which included a test for goitre, because an inflated thyroid made soldiers’ necks too big to wear the uniform. In 1920, the war department published 

 which “summarises the results of all the physical exams performed on draftees during World War I for both accepted and rejected men. Data on prevalence rates per 1,000 are recorded for 269 different medical conditions [including goitre]. The data are regional, organized by units called sections. All but the lowest population states are broken down into multiple sections.” Are goitre rates a good proxy for iodine deficiency? To attempt to check this, the authors unearthed a 1924 paper (McClendon 1924) that measured iodine levels in groundwater across 69 US localities, which they then correlated with the goitre rates.

There is a negative correlation, as we would expect. But this correlation seems to be largely driven by about 10 localities in the top left corner. Does this undermine the authors’ argument? I claim that it does not. We are interested in the level of iodine in groundwater only in so far as it is a proxy for total iodine consumption; but there may be other sources of iodine intake in the diet, such as seafood or yogurt

. On the other hand, alternative causes of goitre, such as selenium deficiency or Hashimoto's thyroiditis, are far less common than iodine deficiency

, and goitre has long been recommended by the WHO

How did the authors acquire the second key piece of data, about cognitive abilities of people born around 1924? Men born around this age were drafted when the United States entered World War II (1924+18=1942). All WW2 enlistees were given the Army General Classification Test (AGCT), a close approximation to an IQ test. Unfortunately, test scores were only collected for a short period during the war. However, the authors explain that they are able to make inferences about the test scores by examining which military branch the enlistees were assigned to. There is historical evidence, which the authors discuss at length, that the recruitment policies gave the air force preferential treatment: it received higher-IQ recruits than the ground forces. For most of the war 75% of Air Force recruits had test scores above the mean. In an incredible twist, there happens to be a way to independently verify this. As the authors explain, from March to May 1943, test scores were recorded in the fields marked “weight” for almost all recruits”. Plotting these scores for the air force vs other branches, we get:

Airforce enlistees had scores of 124 rather than 100, 1.2 standard deviations higher than other branches. This provides strong evidence that the probability of being enlisted in the air force is a good proxy for IQ.

Now that we have the data, let’s have a look at the results.

The difference between high and low goitre groups (the distance between the curves) shows an impressive spike for birth years 1925 and 1926. (The absence of an effect for the 1927 cohort and its reversal for 1928 are actually consistent with historical evidence that towards the end of the war, the infantry crisis gave priority to the ground forces over the air force. I did not mention this fact before in order to keep this blog post simple to understand, but the paper includes a detailed discussion of the issue.) To try to quantify the effect more precisely, let’s have a look at the following regression (note by the way the enormous sample size of more than 2 million):

Note that all four specifications control for section (=region) and some combination of birth year and enlistment year. This means that for each data point, we are only trying to explain how it differs from the average for its section and its cohort. The interaction term highgoiter x birthyearZ asks the question: if you are from a high-goitre region 

 you were born in year Z, how much does this increase your probability of joining the air force, relative to the average for your section and year? In other words, how exceptional is year Z for high-goitre regions relative to non-high-goitre regions, having accounted for cohort average and section average? The coefficients are given in percentage points: for instance, in specification (1), being born in a high-goitre region in 1926 makes you 8.7 percentage points more likely to join the Air force than being from a non-high-goitre region and born in another year. The results are relatively consistent across the four regressions.

How do the authors translate this finding into an effect on IQ points? Given that 75% of air force recruits had an ACGT score above the mean (and 50% of all recruits had a score above the mean) the authors construct a model of the difference in the probability of joining the AAF between high- and low-goitre regions, as a function of IQ score difference in each region. I have not carefully vetted this model, but as far as I can tell it relies on very innocuous assumptions. The estimates of the effect of salt iodisation from table 5 range from 2.5 to 8.7 percentage points. Plugging the lower end of the range of into this model yields an impressive increase in IQ of 15 points for draftees from high-goitre regions potentially due to iodization. The upper range yields IQ increases well over 30 points. The authors consider this finding implausible, and I am inclined to agree. But what should we make of this? We could consider this a small piece of evidence for a very implausible claim, thus resulting in a very small increase in our credence that iodisation increases IQ by more than 30 points. An alternative interpretation is that these effects are too big to be believed, and this would increase our credence that the effect is somehow confounded (i.e. one of the assumptions is not met).

Doubts, reservations, and unanswered questions

As you can see in figure 17, the high and low goitre regions are systematically different in their probability of joining the air force (and surely in other respects too). This means we do not have a natural experiment in the strictest sense of the term. However, this is not a problem as long as we assume that the way in which they are systematically different does not happen to also cause a spike in their probability of joining the Air Force in 1925 or 1926. This seems like a reasonable assumption to make, especially given that our sample covers the entire United States.

I am further reassured by the falsification exercises conducted by the authors. They ran the same regressions using 58 other disorders instead of goitre. Data for these disorder was randomly selected from among disorders reported in 

. The authors suggest that their results show that “the time pattern for goiter is replicated exactly […] in only six of 58 defects: exophthalmic goiter, acromegaly, multiple sclerosis, tabes dorsalis, curvature of the spine, and haemophilia. […] for all of these disorders there exists a link connecting them to iodine deficiency.” This falsification exercise makes less likely the possibility that the effect is caused by some other health improvement that co-occurred with iodisation.

The WW2 enlistment data does not include the county of birth, but only the state. The authors suggest that this limits their sample “to individuals whose birth state is identical to their state of residence” and make the assumption that “the county of residence upon enlistment is the county of birth". There are two potential problems with this assumption. First, there could be systematic migration away from or to high goitre areas within the same state, and so treatment individuals might have been counted as controls or vice versa. This would underestimate the difference between treatment and control and thus underestimate the effect. Second, excluding those who move to another state (close to half the sample) could mean excluding some systematically different sub-group. Overall, I do not believe that these problems undermine the central result.

Publication bias (selective reporting of the correlations that support a thesis) is always a potential problem when a study was conducted on pre-existing data, because several statistical tests could be run until a significant result is found. However, in footnote 40, the authors are open about the trying to use education as an outcome but finding no effect. If this was the only other analysis they ran then, adjusting the results for two tests would likely still leave the results significant (c.f. Multiple comparisons problem).

Evaluating Politi (2010): Salt iodization in Switzerland

This paper uses the same natural experiment design as Weil et al. (2013), so it should be easier to explain now that you are familiar with it.

Salt iodisation began in 1922 in Switzerland. Information on goitre prevalence comes from an 1883 monograph

, which recorded “goiter data taken from recruits during the period 1875- 1880 for all towns and villages in Switzerland”.

Cognitive outcomes were measured using data from the 1970 census, which recorded the place of birth and education level of each individual. This allows us to infer the share of the population born in a certain town or village that has completed secondary of tertiary education.

As in Weil et al. (2013), the date of the introduction of salt iodisation can be used as the date of treatment for a differences-in-differences analysis.

In this graph, the Y-axis indicates the probability of graduating from secondary education. The author explains that this is a regression-adjusted graph: it shows the probability of graduating from secondary education after controlling for district fixed effects and a district time trend. A district fixed effects control would mean we are only looking at how each data point differs from the average for its district. Looking at the top panel, the line for high-goitre regions is consistently higher than the low goitre regions. I do not understand how this could happen when controlling for district fixed effects.

Let’s look at the bottom panel, which shows the difference between high and low goitre districts. If salt iodisation had an effect on graduation rates, we would expect an increase in the difference between high and low goitre regions after 1922. There is an unexplained downward trend before 1922, which makes the increase after 1922 hard to assess: depending on what value is taken to represent the situation before 1922, there is more or less of an increase after 1922. On the most generous interpretation, there is an increase of less than one percentage point in the difference between high and low goitre regions.

In order to better quantify this effect, the author runs a regression with a “born-after-1922” dummy variable. This means she takes the average of the pre-1922 and of the post-1922 period to represent each period. This dummy variable interacts with a high-goitre dummy. The regressions highlighted in red in the table below correspond to the bottom panel in figure 6. It is not clear to me how this coefficient can be so much higher than what we inferred from the graph.

As you can see in this table, the author also ran regressions for looking at tertiary education, at the effect on males and females separately

, and at a shorter range of cohorts. Looking at males vs females we see that the effect is almost entirely driven by females. While coefficients for males are only small and statistically insignificant, coefficients for females are large and significant. This regression attributed to iodisation between a 1.2 and a 2.7 percentage point increase in secondary graduation rates of females. The 1.2 figure appears roughly to match figure 8.

How uniform was the availability of iodised salt?

Was iodised salt introduced quickly and uniformly across Switzerland? There is in fact data on this, drawn from Wespi (1962).

Iodised salt was introduced much later in high-goitre areas. To what extent does this undermine the natural experiment? The fact that low goitre areas (the control group) received a large increase in iodised salt at the time may not be as bad as it seems: we are already assuming, as the basis for this whole analysis, that the effect of iodisation on iodine sufficient districts is very low and thus this might lead to underestimating the effect size. What is more worrying is that high goitre areas (the treatment group) only appear to have received 5% salt iodisation exposure after 1922. We would have to assume that the aforementioned effects are due to this increase, from 0% iodised salt to 5% iodised salt. The author tries to reconcile the findings by suggesting that the effect of iodine is strongly degressive: the first 5% have a disproportionate effect on iodine deficiency. I have not carefully examined whether this is biologically plausible, but a priori I am sceptical.

Results using the jump in iodised salt sales

The data from Wespi 1962 opens up a new possibility. The author writes:

“A closer look into the iodized salt sales data reveals that the transition to iodized salt happened pretty rapidly for most cantons. I take advantage of such sudden jumps in iodized salt sales, as they correspond to jumps in the probability of being treated. Based on the year of the jump in iodized salt sales, which is particular to each canton, I construct a new variable, “age relative to iodization””

The author then looks at the difference between high and low goitre districts, before and after a jump in iodised salt sales. The advantage is that as you can see in figure 12, we now have a large treatment size rather than 5%. The problem is that we are now no longer looking at a simultaneous introduction of salt, making this even less of a natural experiment than it was before. The effect could be confounded by economic development (when districts become more developed, they acquire access to iodised salt 

 there is more of an incentive to finish secondary school), or by myriad other things. In order to conclude that Weil et al. (2013) is confounded, we would have had to assume that high-goitre regions happen to get a simultaneous spike in cognitive performance, a strong assumption. In contradistinction, for Politi (2010) we only have to assume that graduation rates happen to increase simultaneously with local salt sales in order to conclude that the effect is confounded.

A further potential source of bias is the limitations of the pre-existing goiter data (Bircher 1883). In addition to being simply quite old and perhaps more prone to measurement error, these data were collected in 1875-1880, so that the goitre distribution in Switzerland in 1921 might have looked quite different.

Sudden large increases in iodine consumption of chronically iodine deficient people can lead to a deadly type of thyroid inflation called exophthalmic goiter. This is because the body cannot quickly adapt to the sudden intake of otherwise adequate levels of iodine. Weil et al. (2013) finds evidence that iodine deficient regions saw increased death rates from exophthalmic goitre after salt iodisation was introduced.

While this is a large increase, thyroid related mortality is still only between 2 and 3 people per 100 000, or two or three thousandths of one percent. This cost must be weighed against other non-cognitive potential benefits to larger numbers of people such as the reduction of cretinism and deaf-mutism born to highly deficient mothers

I find Weil et al. (2013) to be the more convincing paper. The strongest point against it may be that its results imply an effect too large to be plausible.

The benefits of iodisation may depend on other factors in the environment. Even if there were large effects in the United States and Switzerland in the 1920s, they may depend on conditions that are not met in developing countries today.

, I am not aware of any other literature on iodisation that is not already included the GiveWell’s report. Please email me if you are aware of any such study.

Overall, how much should this evidence change our views? 15 IQ points corresponds to an effect size 3.75 times bigger than GiveWell’s best guess. However, I have less than 20% credence that there will truly be such a benefit when salt iodisation is introduced in developing countries.

Ali Ladak

Why I am taking the pledge this New Year's

 to donate 10% of my income to the most effective charities. You can join me and many others in doing so through our 

I made this decision after coming across some of 

's ideas about our responsibility to people in extreme poverty and becoming involved with the Effective Altruism group in Brighton. These two things really convinced me that I should take the pledge and by doing so make a meaningful difference to the lives of many people living in extreme poverty.

Peter Singer and the Drowning Child Analogy

I have been interested in the problem of extreme poverty since studying economics at university. It seemed crazy to me that in a world full of so much wealth so many people die because they cannot meet their basic needs.

Until recently, though, I never understood what I could do that would actually make any difference to this. I thought that, although it would be good thing to try to help, I was not actually able to contribute to the problem in any meaningful way.

 was a really important part of changing my views on this.

Briefly, the Drowning Child Analogy goes like this: Imagine you are walking through a park and, on your way, you notice that there is a child drowning in a pond. You could jump into the pond and save the child. However, you are wearing a new pair of shoes and by jumping in you would ruin them. So, to avoid ruining your new shoes, you decide to keep walking and you let the child drown. Most people would say that a person who ignores the child in this situation has done something wrong.

there are many children (metaphorically) drowning, and, at a low cost to ourselves, we could save them. The only difference is that they are not drowning right in front of us. They are drowning further away. Does the distance make any difference?

And, if the distance does not make any difference, do we have some further responsibility to people living in extreme poverty, if we can prevent their suffering at a low cost to ourselves?

After coming across this idea I realised that my distance from the suffering does not matter. Rather than just being something good to do, I have a moral responsibility to help the children who are drowning far away from me. If I can help them at a low cost to myself, then I should.

This realisation might sound really burdensome. But it hasn't felt that way. 

It's made me realise that my life actually means something. My choices actually matter.

So if there's something that I can do, at a low cost to myself, then I should do it. But what can I do?

Until recently, I worried that a lot of work that was being done in this area was ineffective, and some of it even having a negative impact. I didn't want to get involved with something that was well-intentioned but ended up doing more harm than good.

there are a number of charities which focus on delivering only the most evidence-based and cost-effective interventions, such as providing insecticide treated bed nets to protect people against malaria, which still causes over half a million unnecessary deaths every year.

 carry out incredibly detailed research on the effectiveness of different charities. Based on its research, GiveWell recommends where to donate to have the most impact.

Reading through some of this research, I realised that there is something I can do, something that good evidence suggests will prevent children from drowning: donate to these effective charities.

And although donating to the charities recommended by GiveWell will not immediately fix the whole problem of extreme poverty, it will still prevent a huge amount of unnecessary suffering that would have otherwise occurred.

If there were five children drowning in a pond, and we only knew how to save one, we would not let them all drown. We would save the one child, and continue to try and figure out how to save the rest.

By shifting my focus to individuals rather than the bigger picture, I realised that despite not being able to fix the whole problem, there is a lot that I can do, right now. And 

Blog

Could parasites be making vaccinations less effective in developing countries?

Did iodized salt raise the IQ of 50 million Americans by 15 points?

Why I am taking the pledge this New Year's

Why you should be public about your good deeds

Six ways to double your impact this New Year's

Bednets Have Prevented 450 Million Cases of Malaria

Giving What We Can’s Recommendations for Giving Season 2015

Do something incredible this New Year

What can the Reach Act do for Global Health?

Mental Health interventions may be more cost-effective than we think