Archive for the ‘public health’Category

Refreshing the RSS: best global health & development blogs?

World! I started a new job 6 months ago, providing technical support and strategic guidance on research activities for 11 country offices of Population Services International (PSI), a large public health NGO with a focus on social marketing and social franchising. While I’ve been active on Twitter (@brettkeller) in the meantime, I haven’t prioritized writing anything (publicly) much lately.

I’m not the only one though: the global health and development blogosphere is a bit quieter than it used to be. Maybe it’s past its prime? But I still find most of my reading on health, data, statistics, development, and politics through RSS feeds (using Feedly). Here are some recent highlights from folks who are still writing:

As many old bloggers have moved on, I want to update my RSS feeds and add any new voices I should be reading. So either on Twitter or in the comments here, please let me know if you’ve spotted a new global health or development-oriented blog I should be following. What makes you think? What highlights good research, data, and visualization? What inspires you? I need new material.


04 2016

Merci, FIFA

This is a French-language FIFA billboard about Ebola:


It has 11 anti-Ebola messages from famous footballers, which happen to be printed small enough to be unreadable from the street or sidewalk.

Not that it would matter anyway: it’s on a major road in Monrovia, Liberia, where no one speaks French.


04 2015

Adaptive Ebola vaccine trials

There’s a New York Times Room for Debate feature has an excellent discussion of the ethics of trials for Ebola treatments and vaccines. Here’s part of the essay by Nancy Kass and Steven Goodman:

Ethics is not just figuring out which side poses better arguments; often it’s best to find a third way. Given the breadth and deadly nature of the current Ebola outbreak, and unknowns about treatments, an “adaptive approach” seems most appropriate. Adaptive approaches allow researchers to plan a sequence of studies, or modify a single study in almost real time, as they learn more about a drug. In West Africa, for example, the first 40 Ebola patients in a trial could all get an experimental treatment, and nobody would take a placebo. If nearly all patients survived, in settings where most others were dying with the same supportive care, then it is possible that placebo testing could be avoided, and subsequent trials could randomize to different doses or treatments.

But if the results of the first trial, without placebos, revealed anything less than an almost certain cure, a design with proper controls would have to be initiated, and explained to those participating in the trial. Patients must be told that the drug is not a guaranteed life-saver, so they can see the point of the control group. (And given the multiple beliefs about Ebola among West Africans, creative approaches to promoting understanding and consent are important as well.) These placebo-controlled trials could themselves be adaptive in design, randomizing more patients to whichever therapy appears most effective, until the verdict is clear. If we are to design trials to minimize suffering and death in a whole population, we must temper our compassion with humility about what we think we know.


12 2014

Terrible choices

Les Roberts, an epidemiologist who teaches at Columbia, is currently working with WHO on the Ebola epidemic in Sierra Leone. Columbia is sharing his blog posts here.

The latest post, from 3 days ago in Freetown, details efforts to triage patients to prevent additional infections. Things just keep getting worse, and it’s to a point where there are no good choices, only terrible choices and slightly less terrible ones. An excerpt:

We are about to assist thousands and thousands of people to die an excruciating death at home without even the most mild of pain relief. We are going to set up treatment facilities in hundreds of villages for one of the most deadly of diseases to be largely run by volunteers who will be lucky to get 3 days of training. Dozens, perhaps hundreds of them will die. And the most surreal aspect of this triage for me is that I completely think that this is the right thing to do given where we are and the limited ability to respond.

Read the rest.


10 2014

Ebola and health workers

It starts with familiar flu-like symptoms: a mild fever, headache, muscle and joint pains.

But within days this can quickly descend into something more exotic and frightening: vomiting and diarrhoea, followed by bleeding from the gums, the nose and gastrointestinal tract.

Death comes in the form of either organ failure or low blood pressure caused by the extreme loss of fluids.

Such fear-inducing descriptions have been doing the rounds in the media lately.

However, this is not Ebola but rather Dengue Shock Syndrome, an extreme form of dengue fever, a mosquito-borne disease that struggles to make the news.

That’s Seth Berkley, CEO of the GAVI Alliance, writing an opinion piece for the BBC. Berkley argues that Ebola grabs headlines not because it is particularly infectious or deadly, but because those of us from wealthy countries have otherwise forgotten what it’s like to be confronted with a disease we do not know how to or cannot afford to treat.

However, in wealthy countries, thanks to the availability of modern medicines, many of these diseases can now usually be treated or cured, and thanks to vaccines they rarely have to be. Because of this blessing we have simply forgotten what it is like to live under threat of such infectious and deadly diseases, and forgotten what it means to fear them.

Ebola does combine infectiousness and rapid lethality, even with treatment, in a way that few diseases do, and it’s been uniquely exoticized by books like the Hot Zone. But as Berkley and many others have pointed out, the fear isn’t really justified in wealthy countries. They have health systems that can effectively contain Ebola cases if they arrive — which I’d guess is more likely than not. So please ignore the sensationalism on CNN and elsewhere. (See for example Tara Smith on other cases when hemorraghic fevers were imported into the US and contained.)

But one way that Ebola is different — in degree if not in kind — to the other diseases Berkley cites (dengue, measles, childhood diseases) is that its outbreaks are both symptomatic of weak health systems and then extremely destructive to the fragile health systems that were least able to cope with it in the first place.

Like the proverbial canary in the coal mine, an Ebola outbreak reveals underlying weaknesses in health systems. Shelby Grossman highlights this article from Africa Confidential:

MSF set up an emergency clinic in Kailahun [Sierra Leone] in June but several nurses had already died in Kenema. By early July, over a dozen health workers, nurses and drivers in Kenema had contracted Ebola and five nurses had died. They had not been properly equipped with biohazard gear of whole-body suit, a hood with an opening for the eyes, safety goggles, a breathing mask over the mouth and nose, nitrile gloves and rubber boots.

On 21 July, the remaining nurses went on strike. They had been working twelve-hour days, in biohazard suits at high temperatures in a hospital mostly without air conditioning. The government had promised them an extra US$30 a week in danger money but despite complaints, no payment was made. Worse yet, on 17 June, the inexperienced Health and Sanitation Minister, Miatta Kargbo, told Parliament that some of the nurses who had died in Kenema had contracted Ebola through promiscuous sexual activity.

Only one nurse showed up for work on 22 July, we hear, with more than 30 Ebola patients in the hospital. Visitors to the ward reported finding a mess of vomit, splattered blood and urine. Two days later, Khan, who was leading the Ebola fight at the hospital and now with very few nurses, tested positive. The 43-year-old was credited with treating more than 100 patients. He died in Kailahun at the MSF clinic on 29 July…

In addition to the tragic loss of life, there’s also the matter of distrust of health facilities that will last long after the epidemic is contained. Here’s Adam Nossiter, writing for the NYT on the state of that same hospital in Kenema as of two days ago:

The surviving hospital workers feel the stigma of the hospital acutely.

“Unfortunately, people are not coming, because they are afraid,” said Halimatu Vangahun, the head matron at the hospital and a survivor of the deadly wave that decimated her nursing staff. She knew, all throughout the preceding months, that one of her nurses had died whenever a crowd gathered around her office in the mornings.

There’s much to read on the current outbreak — see also this article by Denise Grady and Sheri Fink (one of my favorite authors) on tracing the index patient (first case) back to a child who died in December 2013. One of the saddest things I’ve read about previous Ebola outbreaks is this profile of Dr. Matthew Lukwiya, a physician who died fighting Ebola in Uganda.

The current outbreak is different in terms of scale and its having reached urban areas, but if you read through these brief descriptions of past Ebola outbreaks (via Wikipedia) you’ll quickly see that the transmission to health workers at hospitals is far too typical. Early transmission seems to be amplified by health facilities that weren’t properly equipped to handle the disease. (See also this article article (PDF) on a 1976 outbreak.) The community and the brave health workers responding to the epidemic then pay the price.

Ebola’s toll on health workers is particularly harsh given that the affected countries are starting with an incredible deficit. I was recently looking up WHO statistics on health worker density, and it struck me that the three countries at the center of the current Ebola outbreak are all close to the very bottom of rankings by health worker density. Here’s the most recent figures for the ratio of physicians and nurses to the population of each country:* 

Liberia has already lost three physicians to Ebola, which is especially tragic given that there are so few Liberian physicians to begin with: somewhere around 60 (in 2008). The equivalent health systems impact in the United States would be something like losing 40,000 physicians in a single outbreak.

After the initial emergency response subsides — which will now be on an unprecedented scale and for an unprecedented length of time — I hope donors will make the massive investments in health worker training and systems strengthening that these countries needed prior to the epidemic. More and better trained and equipped health workers will save lives otherwise lost to all the other infectious diseases Berkley mentioned in the article linked above, but they will also stave off future outbreaks of Ebola or new diseases yet unknown. And greater investments in health systems years ago would have been a much less costly way — in terms of money and lives — to limit the damage of the current outbreak.  

(*Note on data: this is quick-and-dirty, just to illustrate the scale of the problem. Ie, ideally you’d use more recent data, compare health worker numbers with population numbers from the same year, and note data quality issues surrounding counts of health workers)

(Disclaimer: I’ve remotely supported some of CHAI’s work on health systems in Liberia, but these are my personal views.)

Have recent global health gains gone to the poor?

Have recent global gains gone to the poor in developing countries? Or the relatively rich? An answer:

We find that with the exception of HIV prevalence, where progress has, on average, been markedly pro-rich, progress on the MDG health outcome (health status) indicators has, on average, been neither pro-rich nor pro-poor. Average rates of progress are similar among the poorest 40 percent and among the richest 60 percent.

That’s Adam Wagstaff, Caryn Bredenkamp, and Leander Buisman in a new article titled “Progress on Global Health Goals: are the Poor Being Left Behind?” (full text here). The answer seems to be “mostly no, sometimes yes”, but the exceptions to the trend are as important as the trend itself.

I originally flagged this article to read because Wagstaff is one of the authors, and I drew on a lot of his work for my masters thesis (which looked at trends in global health inequities in Ethiopia). One example is this handy World Bank report (PDF) which is a how-to for creating concentration indexes and other measures of inequality, complete with Stata. A concentration index is essentially a health inequality version of the Gini index: instead of showing the concentration of wealth by wealth, or income by income, you measure the concentration of some measure of health by a measure of wealth or income, often the DHS wealth index since it’s widely available.

If your chosen measure of health — let’s say, infant mortality — doesn’t vary by wealth, then you’d graph a straight line at a 45 degree angle — sometimes called the line of equality. But in most societies the poor get relatively more of a bad health outcome (like mortality) and rather less of good things like access to vaccination. In both cases the graphed line would be a curve that differs from the line of equality, which is called a concentration curve. The further away from the line of equality the concentration curve is, the more unequal the distribution of the health outcome is. And the concentration index is simply twice the area between the two lines (again, the Gini index is the equivalent number when comparing income vs. income). The relationship between the two is illustrated in this example graph from my thesis:

You can also just compare, say, mortality rates for the top and bottom quintiles of the wealth distribution, or comparing the top 1% vs. bottom 99%, or virtually any other division, but all of those measures essential ignore a large amount of information in middle of the distribution, or require arbitrary cutoffs. The beauty of concentration curves and indexes is that they use all available information. An even better approach is to use multiple measures of inequality and see if the changes you see are sensitive to your choice of measures; it’s a more a convincing case if they’re not.

The new Wagstaff, Bredenkamp, and Buisman paper uses such concentration indexes, and other measures of inequity, to “examine differential progress on health Millennium Development Goals (MDGs) between the poor and the better off within countries.” They use a whopping 235 DHS and MICs surveys between 1990-2011, and find the following:

On average, the concentration index (the measure of relative inequality that we use) neither rose nor fell. A rosier picture emerges for MDG intervention indicators: whether we compare rates of change for the poorest 40 percent and richest 60 percent or consider changes in the concentration index, we find that progress has, on average, been pro-poor.

However, behind these broad-brush findings lie variations around the mean. Not all countries have progressed in an equally pro-poor way. In almost half of countries, (relative) inequality in child malnutrition and child mortality fell, but it also increased in almost half of countries, often quite markedly.We find some geographic concentration of pro-rich progress; in almost all countries in Asia, progress on underweight has been pro-rich, and in much of Africa, inequalities in under-five mortality have been growing. Even on the MDG intervention indicators, we find that a sizable fraction of countries have progressed in a pro-rich fashion.

They also compared variations that were common across countries vs. common across indicators — in other words, to see whether the differences across countries and indicators were because, say, some health interventions are just easier to reach the poorest with, and found that more of the variation came from differences between countries, rather than differences between indicators.

One discussion point they stress is that it’s been easier to promote equality in interventions, rather than equality in outcomes, and that part of the story is related to the quality of care that poorer citizens receive. From the discussion:

One hypothesis is that the quality of health care is worse for lower socioeconomic groups; though the poorest 40 percent may have experienced a larger percentage increase in, for example, antenatal visits, they have not observed the same improvement in the survival prospects of their babies. If true, this finding would point to the need for a monitoring framework that captures not only the quantity of care (as is currently the case) but also its quality.


08 2014

Is there a global health bubble? (Or: should you get an MPH?)

There’s a LinkedIn group for Global Public Health that occasionally has good discussion. One example, albeit a sobering one, is the current discussion of employment opportunities after MPH. I’ve been meaning to write about jobs for a while because now that I’m on the other side of the picture — an employed professional with a job at a reputable organization, rather than a grad student — I find myself doing an increasing number of informational interviews, and saying much the same thing each time.

[First, some caveats on the generalizability of the advice below: first, folks with an MPH from another country often have less debt burden than Americans, so may find it easier to do long unpaid or underpaid internships. Second, folks from low- to middle-income countries are and should be more employable, especially in their own countries. Why? Because they have incredibly valuable linguistic and cultural talents (see Alanna Shaikh’s recent post on this), so much so that an organization choosing between an outsider and a local with the same technical skills, communication skills, etc, should almost always choose the local. If they don’t, that’s generally a sign of a dysfunctional or discriminatory organizations.]

The problem is that there is something of an MPH bubble, especially in global health. The size of MPH classes has increased and – more importantly – the number of schools granting degrees has risen rapidly. Degrees focusing on global health also seem to be growing faster than the rest of the field.  (I’d welcome data on class size and jobs in the industry if anyone knows where to find it.) This is happening in part because public health attracts a lot of idealists who are interested in the field because they want to make a difference, rather than rationally choosing between the best paying jobs, and global health has gotten a lot of good press over the last decade. Call this the Mountains Beyond Mountains Effect if you like.

If you know this, and still go into the field, and don’t have an MD or PhD that qualifies you for a different sort of job altogether, then you need to distinguish yourself from the crowd to be employable. I’m assuming your goal is to get a good job in global health, where “good job” is defined as a full-time professional position with a good (not necessarily big-name) organization, working on fulfilling projects and being paid well enough to live comfortably while paying off the loans that most American MPH grads will have. For some, though not all, a good job might also mean one that’s either based abroad or involves frequent international travel. If that’s the goal, then there are several ways to distinguish yourself:

  1. get some sort of hard, transferable skills. This can be research or M&E skills, especially quantitative data crunching ability, or it can be management/coordination experience with serious responsibility. Or other things. The key point is that your skillset should match jobs that are out there, and be something that not everyone has. A lot of MPH programs feature concentrations — or the lack thereof — that are more appealing to students than they are to employers. A biostatistics concentration will likely serve you better than a global health concentration, for instance, and with some exceptions.
  2. get solid international experience, preferably a year or more. Professional experience in public health — even with a lesser-known organization — is much more valuable than experience teaching, or studying abroad. Travel doesn’t count much, and it’s better to have experience in the region you’re interested in working in. There’s a huge catch-22 here, as you need international experience to get it, so that many global health folks start off doing work they’re critical of later in their careers.
  3. relatedly, speak an in-demand language, though this will only help you to work in the region where it’s spoken.
  4. have professional work experience. Even if it’s not in global health, having worked an office job for a year or two makes you more desirable to employers. No one wants to be your first employer, so folks who go straight to an MPH may find themselves less employable than peers who worked for a bit first.
  5. go to a top school, which signals that you’re smarter or better qualified than others (this often isn’t true, the key part is the signalling, and the networks you acquire). Also, graduates of top schools often get good jobs in part because those schools select people with good work experience, skills, and connections to begin with, so that a superior candidate at a school that’s perceived to be a second or third-tier school can do just fine.
  6. avoid debt (which often conflicts with ‘go to a top school’) to give yourself the flexibility to work for less or for nothing at first, until you can do the above.

Any one or two items from this list probably won’t cut it: you need to acquire several.  For example, I’ve known peers with a solid technical degree from a top school and some international experience who still struggled to get jobs at first because they had never had a regular office job before grad school. Also, the relative importance of each will vary according to the subfield of global health you’re interested in. For instance, learning languages might be more important for an implementation person (program coordinator or manager) or a qualitative researcher than it is for a data cruncher.

I used to be pre-med, until I realized I was more interested in policy and did not want to be a clinician, and the path to doing so in the US is long and expensive. Like many former pre-med students who decided not to go to medical school, it took me a while to figure out what I wanted to do, and how to do that without an MD. A couple years post-undergrad I found myself working a job that was interesting enough but not what I ultimately wanted to do, and unable to get a first job in global health without the requisite skills or longer international experience, and I didn’t have the resources to just up and move abroad on my own. So, I went to go to grad school with a technical focus (epidemiology) at a top school, and then used the practicum requirement to build more international experience (Ethiopia). The combination of school and work experience gave me solid quantitative skills because I chose to focus on that each step of the way. But, it also meant taking on quite a bit of debt, and the international practicum would have required even more had I not had generous funding from the econ/policy degree I did. This has worked out well for me, though that same path won’t necessarily work for everyone — especially if you have different interests from mine! — and I think it’s instructive enough to share.

The upside of this bubble is that organizations often hire well-educated, experienced people for even entry level position. The downside is that people from less privileged educational or financial backgrounds often get blocked out of the sector, given that you might have to volunteer for an extended period of time to get the requisite experience, or take on a lot of debt to get a good graduate degree.

In conclusion, getting an MPH — and trying to break into global health — is a personal decision that might work out differently depending on your personal goals, the lifestyle you’re looking for, and your financial background. But if you do get one, be aware that the job market is not the easiest to navigate, and many MPH grads end up unemployed or underemployed for a stretch. Focus on acquiring the skills and experience that will make organizations want to hire you.


02 2014

Data: big, small, and meta

When I read this New York Times piece back in August, I was in the midst of preparation and training for data collection at rural health facilities in Zambia. The Times piece profiles a group called Global Pulse that is doing good work on the ‘big data’ side of global health:

The efforts by Global Pulse and a growing collection of scientists at universities, companies and nonprofit groups have been given the label “Big Data for development.” It is a field of great opportunity and challenge. The goal, the scientists involved agree, is to bring real-time monitoring and prediction to development and aid programs. Projects and policies, they say, can move faster, adapt to changing circumstances and be more effective, helping to lift more communities out of poverty and even save lives.

Since I was gearing up for ‘field work’ (more on that here; I’ll get to it soon), I was struck at the time by the very different challenges one faces at the other end of the spectrum. Call it small data? And I connected the Global Pulse profile with this, by Wayan Vota, from just a few days before:

The Sneakernet Reality of Big Data in Africa

When I hear people talking about “big data” in the developing world, I always picture the school administrator I met in Tanzania and the reality of sneakernet data transmissions processes.

The school level administrator has more data than he knows what to do with. Years and years of student grades recorded in notebooks – the hand-written on paper kind of notebooks. Each teacher records her student attendance and grades in one notebook, which the principal then records in his notebook. At the local district level, each principal’s notebook is recorded into a master dataset for that area, which is then aggregated at the regional, state, and national level in even more hand-written journals… Finally, it reaches the Minister of Education as a printed-out computer-generated report, complied by ministerial staff from those journals that finally make it to the ministry, and are not destroyed by water, rot, insects, or just plain misplacement or loss. Note that no where along the way is this data digitized and even at the ministerial level, the data isn’t necessarily deeply analyzed or shared widely….

And to be realistic, until countries invest in this basic, unsexy, and often ignored level of infrastructure, we’ll never have “big data” nor Open Data in Tanzania or anywhere else. (Read the rest here.)

Right on. And sure enough two weeks later I found myself elbow-deep in data that looked like this — “Sneakernet” in action:

In many countries a quite a lot of data — of varying quality — exists, but it’s often formatted like the above. Optimistically, it may get used for local decisions, and eventually for high-level policy decisions when it’s months or years out of date. There’s a lot of hard, good work being done to improve these systems (more often by residents of low-income countries, sometimes by foreigners), but still far too little. This data is certainly primary, in the sense that was collected on individuals, or by facilities, or about communities, but there are huge problems with quality, and with the sneakernet by which it gets back to policymakers, researchers, and (sometimes) citizens.

For the sake of quick reference, I keep a folder on my computer that has — for each of the countries I work in — most of the major recent ultimate sources of nationally-representative health data. All too often the only high-quality ultimate source is the most recent Demographic and Health Survey, surely one of the greatest public goods provided by the US government’s aid agency. (I think I’m paraphrasing Angus Deaton here, but can’t recall the source.) When I spent a summer doing epidemiology research with the New York City Department of Health and Mental Hygiene, I was struck by just how many rich data sources there were to draw on, at least compared to low-income countries. Very often there just isn’t much primary data on which to build.

On the other end of the spectrum is what you might call the metadata of global health. When I think about the work the folks I know in global health — classmates, professors, acquaintances, and occasionally thought not often me — do day to day, much of it is generating metadata. This is research or analysis derived from the primary data, and thus relying on its quality. It’s usually smart, almost always well-intentioned, and often well-packaged, but this towering edifice of effort is erected over a foundation of primary data; the metadata sometimes gives the appearance of being primary, when you dig down the sources often point back to those one or three ultimate data sources.

That’s not to say that generating this metadata is bad: for instance, modeling impacts of policy decisions given the best available data is still the best way to sift through competing health policy priorities if you want to have the greatest impact. Or a more cynical take: the technocratic nature of global health decision-making requires that we either have this data or, in its absence, impute it. But regardless of the value of certain targeted bits of the metadata, there’s the question of the overall balance of investment in primary vs. secondary-to-meta data, and my view — somewhat ironically derived entirely from anecdotes — is that we should be investing a lot more in the former.

One way to frame this trade-off is to ask, when considering a research project or academic institute or whatnot, whether the money spent on that project might result in more value for money if it was spent instead training data collectors and statistics offices, or supporting primary data collection (e.g., funding household surveys) in low-income countries. I think in many cases the answer will be clear, perhaps to everyone except those directly generating the metadata.

That does not mean that none of this metadata is worthwhile. On the contrary, some of it is absolutely essential. But a lot isn’t, and there are opportunity costs to any investment, a choice between investing in data collection and statistics systems in low-income countries, vs. research projects where most of the money will ultimately stay in high-income countries, and the causal pathway to impact is much less direct.  

Looping back to the original link, one way to think of the ‘big data’ efforts like Global Pulse is that they’re not metadata at all, but an attempt to find new sources of primary data. Because there are so few good sources of data that get funded, or that filter through the sneakernet, the hope is that mobile phone usage and search terms and whatnot can be mined to give us entirely new primary data, on which to build new pyramids of metadata, and with which to make policy decisions, skipping the sneakernet altogether. That would be pretty cool if it works out.

A more useful aid debate

Ken Opalo highlights recent entries on the great aid debate from Bill Gates, Jeff Sachs, Bill Easterly, and Chris Blattman.

Much has been said on this debate, and sometimes it feels like it’s hard to add anything new. But since having a monosyllabic first name seem sufficient qualification to weigh in, I will. First, this part of Ken’s post resonates with me:

I think most reasonable people would agree that Sachs kind of oversold his big push idea in The End of Poverty. Or may be this was just a result of his attempt to shock the donor world into reaching the 0.7 percent mark in contributions. In any event it is unfortunate that the debate on the relative efficacy of aid left the pages of journal articles in its current form. It would have been more helpful if the debate spilled into the public in a policy-relevant form, with questions like: under what conditions does aid make a difference? What can we do to increase the efficacy of aid? What kinds of aid should we continue and what kinds should we abolish all together? (emphasis added)

Lee Crawfurd wrote something along these lines too: “Does Policy Work?”  Lee wrote that on Jan 10, 2013, and I jokingly said it was the best aid blog post of the year (so far). Now that 2013 has wrapped up, I’ll extend that evaluation to ‘best aid blog post of 2013’. It’s worth sharing again:

The question “does policy work” is jarring, because we immediately realise that it makes little sense. Governments have about 20-30 different Ministries, which immediately implies at least 20-30 different areas of policy. Does which one work? We have health and education policy, infrastructure policy (roads, water, energy), trade policy, monetary policy, public financial management, employment policy, disaster response, financial sector policy, climate and environment policy, to name just a few. It makes very little sense to ask if they all collectively “work” or are “effective”. Foreign aid is similar. Aid supports all of these different areas of policy….

A common concern is about the impact of aid on growth… Some aid is specifically targeted at growth – such as financing infrastructure or private sector development. But much of it is not. One of the few papers which looks at the macroeconomic impact of aid and actually bothers to disaggregate even a little the different types of aid, finds that the aid that could be considered to have growth as a target, does increase growth. It’s the aid that was never intended to impact growth at all, such as humanitarian assistance, which doesn’t have any impact on growth.

I like to think that most smart folks working on these issues — and that includes both Sachs and Easterly — would agree with the following summaries of our collective state of knowledge:

  •  A lot of aid projects don’t work, and some of them do harm.
  • Some aid, especially certain types of health projects, works extremely well.

The disagreement is on the balance of good and bad, so I wish — as Ken wrote — the debate spilled into the public sphere along those lines (which is good? which is bad? how can we get a better mix?) rather than the blanket statements both sides are driven to by the very publicness of the debate. It reminds me a bit of debates in theology: if you put a fundamentalist and Einstein in the same room, they’ll both be talking about “God” but meaning very different things with the same words. (This is not a direct analogy, so don’t ask who is who…)

When Sachs and Easterly talk about whether aid “works”, it would be nice if we could get everyone to first agree on a definition of “aid” and “works”. But much of this seems to be driven by personal animosity between Easterly and Sachs, or more broadly, by personal animosity of a lot of aid experts vs. Sachs. Why’s that? I think part of the answer is that it’s hard to tell when Sachs is trying to be a scientist, and when he’s trying to be an advocate. He benefits from being perceived as the former, but in reality is much more the latter. Nina Munk’s The Idealist — an excellent profile of Sachs I’ve been meaning to review — explores this tension at some length. The more scientifically-minded get riled up by this confusion — rightfully, I think. At the same time, public health folks tend to love Sachs precisely because he’s been a powerful advocate for some types of health aid that demonstrably work — also rightfully, I think. There’s a tension there, and it’s hard to completely dismiss one side as wrong, because the world is complicated and there are many overlapping debates and conversations; academic and lay, public and private, science and advocacy.

So, back to Ken’s questions that would be answered by a more useful aid debate:

  • Under what conditions does aid make a difference?
  • What can we do to increase the efficacy of aid?
  • What kinds of aid should we continue and what kinds should we abolish all together?

Wouldn’t it be amazing if the public debate were focused on these questions? Actually, something like that was done: Boston Review had a forum a while back on “Making Aid Work” with responses by Abhijit Banerjee, Angus Deaton, Howard White, Ruth Levine, and others. I think that series of questions is much more informative than another un-moderated round of Sachs vs Easterly.


01 2014

Spreading the word

If you haven’t already read Atul Gawande’s latest New Yorker piece on why some ideas spread fast and other spread slow, get to it:

 In the era of the iPhone, Facebook, and Twitter, we’ve become enamored of ideas that spread as effortlessly as ether. We want frictionless, “turnkey” solutions to the major difficulties of the world—hunger, disease, poverty. We prefer instructional videos to teachers, drones to troops, incentives to institutions. People and institutions can feel messy and anachronistic. They introduce, as the engineers put it, uncontrolled variability.

But technology and incentive programs are not enough. “Diffusion is essentially a social process through which people talking to people spread an innovation,” wrote Everett Rogers, the great scholar of how new ideas are communicated and spread. Mass media can introduce a new idea to people. But, Rogers showed, people follow the lead of other people they know and trust when they decide whether to take it up. Every change requires effort, and the decision to make that effort is a social process.

Much of the material is Gawande’s essay won’t be new if you’re already interested in or working on maternal and child health, but Gawande presents it incredibly well. His comparison of spreading social innovation with the work of salesman also reminded me of another parallel: the parallels between diffusing secular, health-enhancing ideas and missionaries’ evangelistic techniques.

If that last sentence scares you off, hold on a moment for some background. I grew up in a small religious town in Arkansas and my first trips to developing countries were as a missionary. Over time my interests shifted from the preaching and teaching side of things to the medical side, and eventually to health and development policy as an entirely secular pursuit. When I first got to grad school for public health this resulted in some awkward moments, as many conversations would start with “so what first interested you in global health?” If I led with “well, I grew up wanting to be a missionary” I would often get one of two reactions: immediate skepticism of my motivations from my secular liberal classmates, or enthusiastic endorsement of my work (as they misunderstood it) from religious classmates. All that to say: while I think there are very good general reasons to keep public health and missionary efforts as separate as possible, both in theory and praxis, there are several things we secular liberals can still learn from the more devout.

One example is the neverending debates amongst evangelists between those who seek technological shortcuts and those who stick with old-fashioned person-to-person contact. This is a frequent topic at missions conferences (if you didn’t know such conferences existed, it might be an interesting google). You can view the rise of Christian radio broadcasts, followed by Christian TV and televangelists, as the great technological shortcuts: they give a single preacher the ability to reach millions, and if the message is just as good as when delivered in person, why shouldn’t it be just as effective? Some people are persuaded by televangelists, of course, but the effectiveness of the individual doesn’t scale easily to mass media. Likewise, in recent years there’s been much enthusiasm for social media and its potential to save more souls — but the results rarely pan out.  So despite all of the advances in mass and social media, most evangelists still harp on the importance of individual contact, of building relationships. One of the most effective (in terms of growth rate) groups in the world are Mormons, who, no coincidence, devote years of effort to one-on-one contact.

Gawande’s essay tells the story of how BRAC precipitated oral rehydration solution in Bangladesh, and I couldn’t help thinking of their campaign  as a sort of especially successful roving gospel meeting. And here’s Gawande’s closing, where he talks with a nurse who was convinced by a younger, less-experienced trainer to adopt some best practices for safe childbirth:

 “Why did you listen to her?” I [Gawande] asked. “She had only a fraction of your experience.”

In the beginning, she didn’t, the nurse admitted. “The first day she came, I felt the workload on my head was increasing.” From the second time, however, the nurse began feeling better about the visits. She even began looking forward to them.

“Why?” I asked.

All the nurse could think to say was “She was nice.”

“She was nice?”

“She smiled a lot.”

“That was it?”

“It wasn’t like talking to someone who was trying to find mistakes,” she said. “It was like talking to a friend.”

Shortcuts are nice: in public health, unlike evangelism, it’s usually actions rather than beliefs that ultimately count, so I’m all for technological shortcuts when they’re available and effective. But they’re too few and far between, and much of the low-hanging fruit in global health has already been picked. To climb the next step require a lot more effort at improving the “messy and anachronistic”  processes of people and institutions.


08 2013