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Suhail Patel

Malaria scales new heights

Researchers have warned that future climate warming could lead to an increase in malaria cases, according to a study published in the journal 

Last week, scientists from the University of Michigan and London School of Hygiene & Tropical Medicine, published strong evidence linking increases in temperature with the movement of malaria to higher altitude areas which have normally been safe from the disease. According to the paper 'The impact of global warming on insect-borne diseases and on highland malaria in particular remains controversial. We provide evidence for an increase in the altitude of malaria distribution in warmer years, which implies that climate change will, without mitigation, result in an increase of the malaria burden in the densely populated highlands.' The study found that when temperatures increase, mosquitos infected with the Plasmodium parasite are able to move to colder areas, whereas before the lower temperatures would slow down both the mosquito and the development of the parasite within it.

As mosquitos are able to move outside the 'malaria belt' due to global warming, densely populated regions of South America and Africa would be left vulnerable to a malaria epidemic. Using records spanning over 15 years from the highland regions of Ethiopia and Colombia, the scientists predicated a three million increase in annual cases if temperatures were to rise by 1.8 degrees Fahrenheit. 'This is indisputable evidence of a climate effect,' said Mercedes Pascual, a disease ecologist at Michigan and one of authors of the 

 paper. 'Our findings here underscore the size of the problem and emphasize the need for sustained intervention efforts in these regions, especially in Africa.'

Sam Donald

Why We (Still) Don’t Recommend Microfinance

Microfinance is the provision of financial services - loans, savings, and insurance - to those living in poverty. Like those in the developed world, the poor benefit from access to financial services through the ability to fund short and long term consumption needs, cope with unexpected shocks to income and expenses, and invest in business or household items (Matin et al 1999). However, the poor have limited access to more formal financial services, and have thus traditionally relied on a range of institutions, which often charge high premiums or interest rates (Matin et al 1999, Steel et al 1997). Microfinance institutions hope to provide access to those services to a wider range of people living in poverty, in the hope that they will benefit from them. The majority of microfinance institutions, charities, and research projects focus on microcredit - the provision of small collateral-free loans to those who cannot usually get access to credit. We shall do the same here, as the profile and scale of microcredit mean it is the most likely recipient of donations within the microfinance category, and there is more evidence for which we are able to judge its effectiveness.

There are three main benefits to microcredit which have been most commonly mentioned. Firstly, small landholders and businessmen can use credit to make investments in their farms/businesses to create a return greater than the cost of the loan, creating a cycle of improvement and growth which brings them out of poverty. These are the case studies most typically cited by microfinance charities, and have an intuitive appeal and logic, as well as fitting well with the 'poverty trap' model espoused by Jeffrey Sachs. Secondly, that the provision of credit can enhance the freedom of those in poverty, by giving them options and choices which were otherwise unavailable to them. Thirdly, that microcredit may empower and enhance the status of women, and improve the allocation of household resources towards women and children.

Although there have been studies which have shown positive effects of microcredit on labour supply, school enrolment, expenditure per capita and non-land assets (Pitt & Khandler 1998, USAID studies in Peru, India, Zimbabwe), others have failed to replicate the results and similar studies have received significantly less favourable results and criticised the methodology and data involved (Duvendack et al 2011). Randomised controlled trials (RCTs), often seen as the gold standard for assessing the impact of interventions (although not without issues) have previously been thin on the ground in the area of microcredit, but they have increased in number over the last year, and the majority of recent studies have shown that as a tool to escape poverty - the most commonly cited benefit of microcredit - it does not perform well. Studies from the past year have found no statistically significant evidence of an increase in socio-economic indicators such as income, consumption, health, and education (despite businesses expanding) after RCTS of microcredit in a variety of countries: Morocco (Crépon et al. 2013), Ethiopia (Tarozzi et al. 2013) Bosnia-Herzegovina (Augsburg et al. 2014), Mexico (Angelucci et al. 2013) and India (Banerjee et al. 2013). This is a conclusion reached by the majority of individual methodologically sound studies, as well as major systematic reviews of the available evidence (van Rooyen et al., Duvendack et al 2011, Banerjee 2013).

Further, while some may benefit from microcredit, there is significant evidence that for some it has potential for harm (van Rooyen et al 2012, Roodman 2012), in a similar manner perhaps to payday loans in the developing world, a 

 which GiveWell have drawn. While some recent studies do not find evidence of harm on income (Angelucci et al. 2013), even they do not find significant positive impact. Even if for many microcredit was a tool to escape poverty (which is far from clear) donors would rightly be concerned about funding an intervention which may actually cause harm to some. Further, some studies have found a decline in school attendance for those aged 16-19 in families who have had access to microcredit as family businesses expand and draw in labour supply from young adults; the long-term consequences of which are uncertain (Augsburg et al. 2014).

The evidence is more supportive of the ability of microcredit to promote the freedom of those in poverty, but it depends on the situation, and again, credit still has the ability to entrap some people through bad luck or bad judgement (Roodman 2012); moreover, in some areas there is evidence of overlending, with some either borrowing too much or borrowing from multiple borrowers (Planet Rating March 2013). A positive effect of microcredit which is related to freedom is that there is fairly strong evidence that microcredit leads to a decline in consumption on 'temptation goods' such as alcohol and tobacco (Banerjee 2013, Banerjee et al. 2013, Augsburg et al. 2014) for reasons that are unclear.

The effect of microcredit on female empowerment had been contested, with some studies finding positive, but non-uniform effects, and other systematic reviews finding they can neither support nor deny the notion that microcredit is pro-women (Duvendack et al 2011). However, the most recent RCTs from the past year have found no evidence of an increase in female empowerment (Augsburg et al. 2014, Tarozzi et al. 2013, Banerjee et al. 2013, Crepon et al. 2013), although we should note the difficulty of measuring such impacts (van Rooyen et al. 2012)

For the above reasons, we cannot recommend microcredit as a good choice for charitable giving. (Given the lack of any conclusive evidence of reliably positive impact, and evidence of some being harmed by microcredit, it is neither worthwhile nor possible to calculate a cost-effectiveness measure of microcredit in order to compare to other interventions). However, there are also other issues which cause us to recommend against microfinance as an avenue for charitable giving at this moment.

Firstly, there is a possibility that better research in the coming years could perhaps reveal which microfinance interventions are the most effective, and create opportunities for giving to microfinance which do have strong, measurable impacts. Indeed, GiveWell recommends the Small Enterprise Foundation as a standout 

, against a backdrop of strong misgivings over 

, suggesting that charities with a commitment to self-evaluation may in the future produce significant, measurable, and repeatable impacts. RCTs from the past year have shifted the balance of debate decisively towards the conclusion that current microfinance initiatives have at best limited effects in experimental studies, and perhaps the next generation of studies will diagnose the reasons for this and design more effective forms of microcredit. Relatedly, there may develop greater opportunities within microfinance in areas other than microcredit, such as microsavings, which has shown promise (Duvendack et al 2011, van Rooyen et al 2012)

Secondly, "microfinance activities and finance have absorbed a significant proportion of development resources, both in terms of finances and people" (Duvendack et al 2011), and have also seen the entrance of many commercial operations. This raises questions over whether there is room for more funding, and even in some areas whether additional funding would result in overlending and actually cause harm, 

Thirdly, GiveDirectly performs a similar role - the only difference being that the 'loan' is not repaid - and has strong 

Despite a strong narrative and intuitive appeal, we cannot recommend microfinance institutions as a recipient of effective-giving. The available evidence finds no statistically significant improvement on poverty-related outcomes or female empowerment (and indeed it may negatively affect some recipients), while the effect on most freedom-related outcomes is varied and inconclusive. Further, microfinance has received significant attention and resources while other less heralded interventions which have shown significant effects have received far less funding. Recent RCTs strongly support the conclusion that the impact of microcredit on poverty is limited at best, and more high-quality research from academia and microfinance institutions is necessary to reveal the effects and pathways more clearly, as well as to inform best practice.

Angelucci, M., D. Karlan, and J. Zinman (2013). Win some lose some? Evidence from a randomized microcredit program placement experiment by Compartamos Banco. Working Paper.

Attanasio, O., B. Augsburg, R. D. Haas, E. Fitzsimons, and H. Harmgart (2013). Group lending or individual lending? Evidence from a randomised field experiment in Mongolia. EBRD Working Paper No. 136.

Augsburg, B., De Haas, R., Harmgart, H., Mehgir, C., (2014). Microfinance at the margin: experimental evidence from Bosnia and Herzegovina. Working Paper.

Banerjee, A. (2013). Microcredit under the microscope: What have we learned in the past two decades, and what do we need to know? Annual Reviews of Economics 5, 487{519.

Banerjee, A., E. Duflo, R. Glennerster, and C. Kinnan (2013). The miracle of microfinance? Evidence from a randomized evaluation. MIT Department of Economics.

Crépon, B., F. Devoto, E. Duflo, and W. Pariente (2013). Estimating the impact of microcredit on those who take it up: Evidence from a randomized experiment in Morocco. Working Paper.

Duvendack, M., Palmer0Jones, R., Copestake, J., Hooper L., Loke Y. and Rao, N., (2011), 'What is the evidence of the impact of microfinance on the well-being of poor people?', August 2011, London: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London

Matin, I., Hulme, D., Rutherford., S (1999). Financial services for the poor and poorest: deepening understanding to improve provision. Finance and development research programme working paper series no. 9. Manchester: IDPM, University of Manchester Pitt, M., Khandker, S., (1998) The impact of group-based credit programmes on poor households in Bangladesh: does the gender of participants matter? Journal of Political Economy, 106 (5): 958-996.

Roodman, D., (2012). Due Diligence: An impertinent inquiry into microfinance. Centre for Global Development

Steel, W. F., Aryeetey, E., Hettige, H. and Nissanke M. (1997), 'Informal Financial Markets Under Liberalization in Four African Counties', World Development, vol. 25, no. 5, pp. 817-830, Elsevier Science Ltd.

Stewart, R., van Rooyen, C., Korth, M., Chereni, A., Rebelo Da Silva, N., de Wet, T., (2012) Do micro credit, microsavings and microleasing serves as effective financial inclusion interventions enabling poor people, and especially women, to engage in meaningful economic opportunities in low and middle income countries. A systematic review of the evidence. London: EPPI-Centre, Social Science Research Unit, Institute of Education, University of London

Tarozzi, A., Desai, J., Johnson, K., (2013), On the impact of microcredit: evidence from a randomized intervention in rurar Ethiopia. Working Paper

Jessica Costello

Measuring benefits

By investing in the most effective charities, we can extend people's lives. We can improve the quality of their lives. Sometimes we can do both. But how do we measure and compare the potential benefits that charities provide, to ensure we are indeed investing in the most effective ones? We use metrics known as Health-Adjusted Life Years (HALYs), which involve the trade-off between duration and quality of health in a single numerical unit. [1] There are two types: Quality-Adjusted Life Years (QALYs) and Disability-Adjusted Life Years (DALYs). These measure health gain and loss, respectively,[2] and as such, may very broadly be considered inverse metrics.[3] Quality-adjusted life years (QALYs) have been used in the assessment of health interventions for three decades[4] as an aid to resource allocation.[5] Although the measure is well-established, the assumptions underlying it are ever debated.[6]

Individuals move through health states over time; these consist of varying levels of functioning within a set of health domains, which may include mobility, cognition, pain, emotional functioning, self-care, and so on.[7] The domains considered are contingent on the instrument used to measure the health state, such as the EuroQol five dimensions (EQ5D) or the Health Utilities Index.[8] Each health state is assigned a certain value (or utility) which is determined by assessing the preferences of a group of individuals for being in any one state (using methods like the standard gamble or time trade-off). A value of zero represents death, while a value of one represents full health. It follows that any state in between (of less than perfect health, e.g. living in a wheelchair) is also assigned a value in between.[4]

A QALY score is obtained by multiplying (or weighting) the amount of time spent in a health state by the utility score assigned to that health state.[4] For example, it takes one additional year of perfect health (utility score of one) to obtain one QALY. It also takes four additional years in a health state valued at 0.25 to obtain one QALY. Again, if the quality of an individual's life is improved by 0.25 over four years, a QALY is gained.

The QALY framework provided a basis for the development of the disability-adjusted life year (DALY) in the early 1990s.[4] The DALY tends to be used in the developing world, and has been widely adopted by the 

. Members of Giving What We Can also use DALYs, and have been involved in designing recent adjustments to the metric.[9] The DALY is primarily a measure of disease burden, and thus relates to an entire disease (rather than a health state, as with the QALY). This burden may be a reduction in full health (such as suffering from malaria, for instance), or even premature death. The DALY thus represents a loss of functioning, and can be thought of as one life year in full health lost.[2]

To determine the number of years lost due to a disease, a weight factor that reflects the severity of the disease on a scale from zero (perfect health) to one (death) is assigned. This is the inverse to the QALY.

When calculating the number of years lost due to premature death, the life expectancy of the afflicted individual would need to be known. As this is not possible, a typical life expectancy is predetermined. Giving What We Can uses a life expectancy of 60 years, which is the typical life-expectancy at birth for the developing countries in which our charities operate.

When calculating the number of years lost due to disability, the severity of the disease state is presented as a percentage of the burden of premature death. For instance, a year of blindness would be considered 60% as burdensome as a year lost.[10]

As with the valuation of health states for QALYs, these weightings may be determined from preference-based studies, or expert valuations. However, controversy exists around the use of these methods to decide that, for instance, a year of blindness should be counted as 60% as burdensome as a year lost, whereas a year of being severely underweight due to malnutrition would be considered 5.3% as burdensome. The DALY metric also allows for optional age weighting and discounting features, which are based on moral assumptions, and as such, are also liable to being debated. The Disability-Adjusted Life Years series by Holden from GiveWell describes these controversies in detail.[10]

QALYs and DALYs face criticisms, which stem from the theoretical assumptions and subjectivity underlying them. Albeit used in different settings, both are measures that combine mortality with morbidity in single numerical units. Some argue that mortality and morbidity are different dimensions that cannot be combined, whereas others advocate the necessity of such criteria to enable resource allocation in a consistent manner, across health states and diseases.[1] As such, the use of QALYs and DALYs, although relatively widespread, remains controversial, and alternative measures continue to be developed.

[1] Robberstad B. QALYs vs DALYs vs LYs gained: What are the differences, and what difference do they make for health care priority setting? Norsk Epidemiologi 2005; 15 (2): 183-191 [2] World Health Organization. The Global Burden of Disease concept. 

http://www.who.int/quantifying_ehimpacts/publications/en/9241546204chap3.pdf

 [Accessed December 2013] [3] Gold MR. et al. HALYS AND QALYS AND DALYS, OH MY: Similarities and Differences in Summary Measures of Population Health. Annu Rev Public Health 2002; 23: 115-134 [4] Sassi F. Calculating QALYs, comparing QALY and DALY calculations. Health Policy Plan. 2006 Sep;21(5):402-8. Epub 2006 Jul 28. [5] National Institute for Health and Care Excellence. Measuring effectiveness and cost effectiveness: the QALY. 

http://www.nice.org.uk/newsroom/features/measuringeffectivenessandcosteffectivenesstheqaly.jsp

 [Accessed December 2013] [6] Seventh Framework Programme. European Assessment Of The Validity Of The Qaly Outcome Measure: The Qaly Controversy: Key Results From The Experiment Conducted By The Echoutcome Project, January 2013 

http://www.reglinkassociates.com/Articles/echoutcome0113.pdf

 [Accessed December 2013] [7] Chatterji S. et al. Global Programme on Evidence for Health Policy Discussion Paper No. 45: The conceptual basis for measuring and reporting on health. 2002. 

http://www.who.int/healthinfo/paper45.pdf

 [Accessed December 2013] [8] Whitehead SJ. et al. Health outcomes in economic evaluation: the QALY and utilities. Br Med Bull 2010; 96 (1): 5-21. doi: 10.1093/bmb/ldq033 [9] GWWC members Nick Beckstead, Nir Eyal, Toby Ord, and Thomas Pogge were amongst philosophers asked to advise on ethical aspects of the DALY measure at the recent Critical Ethical Choices for DALYs meeting, convened by the World Health Organisation and World Bank in preparation for publication of the 2010 Global Burden of Disease Report.} [10] Holden. The GiveWell Blog. Series: Disability-Adjusted Life Years. 

http://blog.givewell.org/2008/08/07/disability-adjusted-life-years-introduction/

Andreas Mogensen

Why we (still) don’t recommend GiveDirectly

 This article hasn't been updated recently. We're keeping it up for the historic record of the debate, and because people still seem to refer to the arguments. Giving What We Can no longer actively conducts charity evaluation. We recommend you 

read GiveWell's latest research on GiveDirectly

 is a charity founded in 2008 that provides unconditional cash transfers to households in extreme poverty. GiveDirectly is currently among 

's top recommended charities, but doesn't feature on our own list of recommended charities. In this post, I'll explain why we haven't changed our mind about GiveDirectly since we last addressed the issue in late 2012. In particular, I'll discuss the results of a recent randomized control trial (RCT) from November 2013, which some have taken to answer skepticism about unconditional cash transfers[1]. While generally positive, the results of this RCT also provide evidence that transfers are less cost-effective than was indicated by estimates made by GiveWell when we last commented on their recommendation. It goes without saying that we have great admiration for GiveWell's work, and much of our own research is heavily indebted to theirs[2]. However, on this point we continue to respectfully disagree.

At present, GiveDirectly operates in Kenya and Uganda. Transfers are targeted at the very poorest, and GiveDirectly employs a detailed selection procedure to identify the worst-off households. Within villages, these are selected based on homes of mud and thatch that lack metal roofs[3]. Marginal donations to GiveDirectly go toward cash grants, as operating costs are independently funded by large donors. Transfer costs absorb approx. 10% of donations, meaning that roughly 90% of the amount given ultimately reaches recipients[4]. Cash transfers are a well-studied intervention-type, beginning with highly encouraging results obtained in a randomized trial of the Mexican Progresa programme[5]. Within the field of cash transfers, GiveDirectly's programme has two distinctive features.

Firstly, transfers are unconditional: recipients are not obligated to spend their transfer in any way, and receipt of further instalments is not dependent on meeting goals associated with, say, children's education or health (as in the Progresa programme). Secondly, relative to other cash transfer programmes, the amounts transferred are large. Households receive approx. $1,000 (in instalments) over the course of a year[6]. By way of comparison, this represents approx. 55% of median household income[7]. The same amount of money could be used to supply long-lasting insecticide-treated nets to more than 160 people[8] and provide deworming treatment to more than 1,000 children[9]. Although cash transfers are well-studied, there is relatively little direct evidence on the impact of large, unconditional transfers of this kind. However, there does exist a recent, well-designed, pre-registered RCT that examines short-term impacts from GiveDirectly's own programme. Results from this trial were reported in a policy brief by Johannes Haushofer and Jeremy Shapiro released in November of 2013[10].

GiveDirectly appeared on GiveWell's list of top recommended charities in the winter of 2012, ranked above Schistosomiasis Control Initiative (SCI) and below Against Malaria Foundation (AMF). At the time, GWWC Vice President William MacAskill offered a broad range of considerations explaining our skepticism about GiveWell's recommendation and our continuing decision to preferentially recommend health charities[11]. Will noted a number of general considerations that should lead us to assign low prior confidence to the idea that cash transfers are more cost-effective than the best health programmes. In addition, he pointed to the paucity of evidence on the impact of large, unconditional transfers and expressed surprise at what he regarded as a lack of concern for cost-effectiveness underlying GiveWell's recommendation.

At the end of 2013, GiveDirectly maintained its status among GiveWell's top-recommended charities. GiveWell no longer explicitly ranks its charities, though senior staff members' personal donation-decisions suggest they regard GiveDirectly as the best option for giving[12]. GWWC has maintained its position on GiveDirectly. Maintaining our position requires some explanation in light of the results reported by Haushofer and Shapiro, which go some way to addressing Will's earlier concern about paucity of evidence. Ultimately, disagreement between GiveWell and GWWC on GiveDirectly reflects more fundamental methodological divisions. GWWC places greater weight on explicit estimates of charity cost-effectiveness, which GiveWell regards with more skepticism[13]. Consequently, GiveWell's recommendations lend greater weight to assessments of organizational virtues, such as transparency, self-monitoring and evaluation, etc. Our own recommendations weight organizational virtues to the extent that they provide reason to believe that an organization can reliably deliver an intervention whose cost-effectiveness can be pre-established with reasonable certainty. GiveWell's own cost-effectiveness estimates suggest that GiveDirectly's wealth transfers are less effective than deworming[14]. What we believe about GiveDirectly depends, ultimately, on the weight we give to cost-effectiveness estimates of this kind. Our recommendations lend them more weight than GiveWell's. There is thus a deeper controversy, which we can't hope to resolve here. Instead, I'll confine my discussion to explaining why the results reported by Haushofer and Shapiro haven't changed our minds.

A randomized control trial of wealth transfers

Haushofer and Shapiro conducted a randomized control trial in the Rarieda district of western Kenya in 2011-2012. Whereas our information about charity cost-effectiveness typically relies on evidence regarding the cost-effectiveness of the type of programme being carried out, Haushofer and Shapiro directly assess GiveDirectly's own work, albeit with one qualification. GiveDirectly's transfers are typically worth approx. $1,000. However, only about a quarter of households received transfers of this size, with the remainder receiving approx. $300. The aim here was to assess the impact of transfer size on key variables (described below). However, the overall results of the study are often reported in a manner that averages across both groups and doesn't easily allow us to look within treatment conditions[15]. Haushofer and Shapiro looked at 8 key variables: total assets; total consumption; food security; agricultural and business income; health; education; psychological well-being; and female empowerment. Overall, the results were encouraging, with recipients of larger transfers showing greater improvements. However, some key variables showed no significant positive impact.

Recipients chose toinvest a significant fraction of their transfer, in livestock, furniture, and home improvements. The total value of their asset holdings increased by USD PPP 279 on average, representing a 58% increase over the control group. Relative to controls, recipients of transfers were 23 percentage points more likely to own an iron roof (16% vs 39%); Haushofer and Shapiro estimate a 7-14% return on investment (ROI) for iron roof purchases, as this obviates the need to make periodic, costly repairs of thatched roofs.

Cash transfers increased all categories of consumption, except for temptation goods, such as alcohol and tobacco, with a 19% increase in food consumption relative to controls. Food security increased significantly in transfer recipients, reducing the likelihood that respondents had gone to bed hungry in the previous week by 7 percentage points and the number of days children had gone without food by 42%.

Revenues from agriculture and business increased, though there was no significant increase in profits. Transfers did not significantly increase indices of health and education. Transfer recipients reported subjective well-being greater than that of controls by 1/5th of a standard deviation, though measures of the stress hormone cortisol were not significantly lower than in controls. Female empowerment increased significantly, as measured by attitudes toward women and reports of spousal abuse.

Some variables show 'spill-over' effects, estimated by comparing non-recipient households within villages where some households received transfers with households in villages where no households received transfers. Psychological well-being and female empowerment showed positive spill-over effects. Positive spill-over effects on psychological well-being are especially welcome in this context, as one worry regarding wealth transfers is that they might create resentment among non-recipients. There was some evidence for a negative spill-over effect on consumption, but this was only statistically significantly at a 10% level. Haushofer and Shapiro found that transfers had no impact on the general village-level economy.

The study comes with some limitations. With the exception of cortisol levels, all data is self-reported. This may raise the worry that positive results are driven by recipients' desire to report encouraging results that please experimenters - especially given that measures of cortisol did not accord with self-reported gains in well-being. We're not especially inclined to discount the results on this basis, however, because self-reported results also show no significant impact for a number of key variables, including business profits, health, and education. As Haushofer has noted, the mixed nature of the results provides evidence for internal validity[16]. The more significant limitation is the inability of this study to assess long-term impacts. It is far from implausible that significant positive impacts on business profits, health, and education emerge over longer time-scales.

We have never seriously doubted that cash transfers could make improvements in the lives of poor people in the developing world. The only question concerns whether the size of these benefits are comparable to those attained by our recommended charities. In this respect, GiveWell have done a fantastic job in describing models that allow us to compare the cost-effectiveness of deworming and wealth transfers. One such model was described in late 2012[17], and the most recent came out at the end of 2013[18].

The key thing we'll note here is that the estimate produced in 2012 relied on assumptions about cash transfers that appear to have been too optimistic in light of results reported by Haushofer and Shapiro. Therefore, we don't regard these results as providing sufficient reason for us to revise the position we had at that time. Updated in light of other evidence from 2013 indicating lower effectiveness of deworming[19], GiveWell's own estimates continue to indicate that deworming is more effective than cash transfers by roughly the same factor.

Deworming and wealth transfers can be compared by thinking of deworming as an investment that pays off in terms of greater future earnings; the present value of these earnings can be compared with that of investments made by recipients of cash-transfers, primarily in terms of purchases of metal roofs. The case for deworming as a source of greater income in adulthood rests principally on two studies. Based on a retrospective survey from hookworm eradication in the American South, Hoyt Bleakley (2007)[20] predicted that deworming during childhood should raise incomes by over 20% in adulthood in Sub-Saharan Africa; Sarah Baird and colleagues (2011)[21] subsequently obtained evidence from deworming programmes in Kenya that confirm this prediction[22].

Comparing deworming and wealth transfers in this way depends on a number of key assumptions such as the discount rate, the external validity of the results reported by Baird et al., the return on investment for cash transfers, etc. for which different staff members have offered different estimates. The estimates made by GiveWell in late 2012 turned out to be optimistic in two respects.

The first concerns the return-on-investment, though here only some estimates may be thought too high. ROI was originally estimated at 10%, 25%, 5%, or 54%, depending on the person surveyed. As noted, Haushofer and Shapiro estimated a 7-14% ROI for investment in roofs. Business investments showed no significant evidence of increasing profits and thus provide no evidence of additional returns on investment. However, the latter point may simply reflect the short-term nature of the study.

The more significant overestimate concerned the proportion of transfers invested, estimated in 2012 at 75%. Haushofer and Shapiro report that recipients invested $PPP 278 on average, with recipients of larger transfers investing more than recipients of modest transfers by $PPP 253. This suggests that recipients within each group invested approx. 30% of the amount received. Of the $PPP 278 invested on average, $PPP 85 went to livestock, $PPP 53 on durable goods such as furniture and agriculture appliances, and $PPP 10.22 was saved. This may suggest that less than half of invested funds went into purchasing iron roofs.

Although the results obtained by Haushofer and Shapiro may be thought to significantly help the case for large, unconditional cash transfers - and certainly address earlier concerns about paucity of evidence - they are less positive in other respects, particularly when compared with estimates available when we last addressed the value of cash transfers. Ultimately, we don't feel that these results have tipped the balance in favour of GiveDirectly.

[1] See the discussion of these results in The Economist: 

http://www.economist.com/news/international/21588385-giving-money-directly-poor-people-works-surprisingly-well-it-cannot-deal

 [2] We'd also like to thank GiveWell for comments on a previous draft of this post, which helped to clarify a number of important points for us. [3] 

http://www.givedirectly.org/howitworks.php#

http://www.givedirectly.org/financials.php

 [5] Banerjee & Duflo Poor Economics, pp. 78-81 [6] 

 [7] For median household income figures see: 

http://www.gallup.com/poll/166211/worldwide-median-household-income-000.aspx#2

 [8] Assuming a cost of approx. $6 per net distributed. 

http://www.givewell.org/international/top-charities/AMF#Costperlifesaved

 [9] Assuming a cost of less than $1 per child dewormed. 

http://www.givewell.org/international/top-charities/schistosomiasis-control-initiative

http://web.mit.edu/joha/www/publications/Haushofer_Shapiro_Policy_Brief_UCT_2013.10.22.pdf

https://www.givingwhatwecan.org/blog/2012-11-30/givewell%E2%80%99s-recommendation-of-givedirectly

http://blog.givewell.org/2013/12/12/staff-members-personal-donations/

http://blog.givewell.org/2011/08/18/why-we-cant-take-expected-value-estimates-literally-even-when-theyre-unbiased/

http://www.givewell.org/international/top-charities/give-directly#Whatdoyougetforyourdollar

 [15] Overall, households in the treatment group were randomized according to three conditions: the gender of the person receiving the transfer on behalf of the household; the size of the transfer ($300 vs $1,100); and, finally, for smaller transfers, whether these were made as a lump-sum or in monthly instalments.

http://blogs.worldbank.org/impactevaluations/some-thoughts-give-directly-impact-evaluation

http://blog.givewell.org/2012/12/19/cost-effectiveness-of-nets-vs-deworming-vs-cash-transfers/

 [19] Sadly, further discussion of this issue is beyond the scope of this post. We hope to further review the status of deworming charities within the recent future. [20] 

http://qje.oxfordjournals.org/content/122/1/73.short

http://www.povertyactionlab.org/publication/worms-work-long-run-impacts-child-health-gains

 [22] There is also evidence that freedom from childhood malaria considerably increases adult earnings: see references in Banerjee and Duflo, p.45

Katie Hamilton

The Economic Burden of Neglected Tropical Diseases: What Trachoma Can Teach Us

This blog, the final in a 3-part series written by Costello Medical Consulting, focuses on the estimated economic burden of trachoma. This neglected tropical disease (NTD), caused by repeated bacterial infection of the eye, is estimated to leave one person blind every 15 minutes. International work highlighting the importance of tackling this infectious disease has led to adoption of a simple yet effective control strategy, which reduces the prevalence of trachoma by treating those affected and reducing transmission by improving sanitation. Here, we discuss the potential of this intervention tactic to not only decrease the prevalence of trachoma, but to also provide benefits that help reduce the global burden of other NTDs.

Trachoma is one of the top ten most common blinding diseases [1] and the leading cause of preventable blindness worldwide [2]. One person is left with severe sight loss every four minutes due to the damage caused by trachoma infection; four people are blinded by the disease every hour [3]. Endemic in more than 50 countries worldwide [1], trachoma has been classified by the World Health Organisation (WHO) as one of 17 neglected tropical diseases (NTDs). Its cause is infection of the eye surface by the bacteria 

 [1]. Recurrent infection leads to painful in-turning of the eyelashes (trichiasis), which, if left untreated, scratch and subsequently scar the eyeball, resulting in the cornea becoming opaque and, ultimately, blindness [1,4]. The bacteria are readily transmitted through infected discharge – therefore the disease can be spread through shared items such as towels, as well as by eye-seeking flies [4]. People that live in crowded conditions and with poor sanitation are particularly susceptible to the spread of trachoma [5]. This means that the disease burden, in terms of human suffering and reduced quality of life for those infected, their families and wider communities, is shouldered by some of the world’s poorest populations [2].

In addition to prevalence and impact on quality of life, the burden of a disease can also be measured in terms of monetary losses, referred to as economic burden of a disease. Estimating the economic burden of different diseases is useful when resources and funding for health interventions are limited, as it allows the cost-effectiveness of proposed control strategies to be evaluated in monetary terms.

To understand the economic burden of NTDs, we searched the key sources of health-related publications, including PubMed, the WHO and Cochrane websites, using a combination of disease-related and economy-related search terms. Disease-related search terms included all of the 17 NTDs, as defined by the WHO [6], and economy-related search terms such as ‘burden’, ‘cost’ and ‘employment’. Diseases with inexpensive treatments that affect the largest populations were prioritised. In total, we found 282 articles reporting on the economic burden of NTDs in developing countries, which we then divided by disease area. The 12 resulting articles on trachoma were used as basis for this review.

A number of studies presented estimates of the occurrence of trachoma at various scales - individual countries, continents and worldwide. One study estimated that, globally, trachoma is the cause of blindness in 1.3 million people and trichiasis in a further 8.2 million [1]. It is thought that 110 million people live in areas where trachoma is endemic [2], including Pakistan, Senegal, Nepal and Fiji [3], and are therefore at risk of contracting the disease. Within these endemic areas, 4.6 million people already suffer with late-stage-trachoma and will require surgery to prevent blindness. Worryingly, a further 210 million people currently live in areas where trachoma is suspected, but not confirmed [2].

Some of these studies converted the disease prevalence into health burden, measured in disability-adjusted or handicap-adjusted life years (DALYs, which are a measure of healthy life-years lost due to disability and mortality; or HALYs, which are a measure of years lived in a handicapped state and mortality); others used the prevalence data to calculate the economic burden of trachoma. The global estimate of the health burden of trachoma was 80 million HALYs [7]; the estimated economic burden was $2.9 billion [8]. The geographic distribution of trachoma infection is very patchy, with 80% of the global burden concentrated in only 14 countries [2], and 97% of the burden of Latin America and the Caribbean found in Brazil alone [9]. Perhaps unsurprisingly, NTDs have been shown to have particularly high prevalence in conflict and post-conflict countries, for example trachoma in Sudan, Mali and Niger [10].

Generally, estimates of the burden of trachoma vary considerably between different reports [1], most likely due to the fact that prevalence figures are not consistent between studies; and there seems to be no standard conversion method to generate estimates of human or economic burden. Accurate estimates of disease burden are therefore difficult to generate. However, even if not completely accurate, estimating the disease burden is undoubtedly useful, as it allows assessment of the cost-effectiveness of disease control or elimination strategies and provides decision makers with additional information to help prioritise healthcare interventions.

An innovative strategy which targets trachoma from both a medical and a socioeconomic angle [11], ‘The SAFE Strategy’ (

nvironmental change), is endorsed by the World Health Foundation [3]. The potential of SAFE has been demonstrated in Morocco, where the prevalence of trachoma has been reduced by 75% since its implementation in the late 1990s, and complete elimination of the disease has been achieved in some provinces [11]. This is by no means an isolated case - a further 9 countries, including Ghana, Vietnam and The Gambia, have reported meeting their targets towards the elimination of blinding trachoma [3]. The total cost of implementing the SAFE strategy in all remaining known endemic countries is estimated to be $430-$748 million [3], which is less than a third of the estimated overall economic burden of trachoma.

An alliance of interested parties, led by the WHO, has set the target of the 

 elimination of trachoma for 2020 (GET2020). Pfizer, a major pharmaceutical company, has committed to help. They have donated over 225 million doses of azithromycin (an antibiotic) to date [12], allowing the treatment to cure or prevent trachoma for 48.8 million people [13]. However a 2012 review suggested that lack of funding may still be a barrier to achieving the GET2020 goal [14]. Interestingly, the authors of this review estimated that diverting just 10% of the funding allocated to the treatment of the ‘Big Three’ diseases (tuberculosis, HIV and malaria) to NTDs would allow the achievement of the GET2020 goal [14].

As the occurrence of NTDs is so often linked to the living conditions in poor rural communities, it is likely that any healthcare interventions introduced will contribute to the decrease of more than one disease simultaneously. For example, it has been suggested that the framework set up to provide treatment for onchocerciasis (another NTD, which also causes blindness) can also be used to distribute azithromycin, or any other drug [11]. Therefore, if NTDs are considered individually, the effectiveness calculated for interventions may well be underestimated. In many cases, it will be more appropriate to consider the reduction of the burden of 

 diseases when calculating the cost-effectiveness of a single intervention strategy.

Overall, it is clear that NTDs, such as trachoma, cause immense human suffering and remain a serious impediment to poverty reduction and overall socioeconomic development [15]. Our research into trachoma, as well as onchocerciasis and cysticercosis [16, 17], has shown that these NTDs each impose a significant economic as well as health burden on affected communities. Although there has been much progress in tackling this global problem by introducing control measures, such as SAFE, continued strategic investment is necessary if the targets for the reduction and eradication of these diseases are to be met.

By Katie Hamilton and Julia Bardos, working pro bono on behalf of 

, with a wider team at Costello Medical Consulting

1. Burton M and Mabey D. The Global Burden of Trachoma: A Review. PLoS Negl Trop Dis. 2009;3(10):e460 2. International Trachoma Initiative: Trachoma Overview. 

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