As discussed previously, we are looking for (program-based) interventions that are both proven and scalable. The Disease Control Priorities report lists many interventions that are “proven,” in the sense that one or more studies have been done indicating that the program has improved health outcomes in the region. However, showing that a program has worked once – or even several times – is far from showing that it will work again. Not only could the context, circumstances, and clients change, but the people running the program (and the scrutiny they’re under) most likely do change from a studied experiment to a less thoroughly tracked replication.

In examining the case for different interventions (see the list of interventions here), we have noted that some types of programs are inherently more “straightforward” than others, in the sense that a lower burden of proof is necessary to extrapolate from their past effects to their future effects. For example:

• Many programs focus on educating clients, and their success thus depends on sustained and difficult-to-track behavior change from locals. Even if a sanitation program has successfully reduced diarrhea incidence rates in one region, bringing it to a new region means dealing with a new group of people, who may respond completely differently to the same education techniques. Without thorough and ongoing monitoring and evaluation, we feel it is difficult to be confident that a program along these lines is continuing to work.
• Other programs, such as DOTS for tuberculosis, focus on improving medical care. They may depend on sustained behavior change from local medical professionals, but not from the population in general. The success of such programs will depend heavily on the existing health care infrastructure, qualifications of health professionals, and quality of training. We feel it is difficult to have confidence in such programs without continually tracking patient outcomes.
• Other programs, such as vaccinations, do not rely on sustained behavior change from anyone in the local population. A vaccination campaign in a given region can be carried out fairly infrequently (i.e., once a year) as long as the vaccines administered are legitimate and a large number of people can be gathered and treated. Both of these factors are relatively straightforward to track and report.

Below are all the interventions we’re aware of that fit in the last category: interventions that can be carried out relatively infrequently (i.e., every 6-12 months), and for which all necessary behavior change can be directly observed and reported by the people carrying them out. For each intervention, we briefly characterize what information would need to be reported in order to reasonably extrapolate from the intervention’s past, studied effects on health outcomes.

1. Intervention: vaccination campaigns. Information needed: number and age of people vaccinated; disease incidence/prevalence estimates for the region.
2. Intervention: Mass drug administration programs, including albendazole for treating helminths and ivermectin for treating onchocerciasis and lymphatic filariasis (more on these conditions in future posts). Information needed: number and age of people treated; disease incidence/prevalence estimates for the region.
3. Intervention: Vitamin supplementation programs, with nutrients that need be taken only infrequently (particularly vitamin A). Information needed: number and age of people treated; estimates of vitamin A deficiency prevalence for the region.
4. Intervention: Vitamin fortification programs, such as the iodization of salt. Information needed: amount and circulation of food fortified; estimates of iodine and other deficiency prevalence for the region.
5. Intervention: One-time surgery programs, along the lines of Interplast’s surgical team trips. Information needed: Condition treated for each client; completeness of surgery (before-and-after pictures would capture this information).

In labeling interventions “straightforward,” we are not claiming that they are easy to carry out or that they will always work. However, all else equal, we find them more promising for our purposes than other program-based interventions. This is largely because our experience to date with developing-world aid has shown that thorough, high-cost monitoring and evaluation (of the sort that could track sustained behavior change, for example) is relatively rare. We believe we are most likely to be able to confidently recommend interventions along the lines of those listed above, for which the necessary burden of monitoring and evaluation is lower.

In our analysis of bednet distribution programs, we considered the likelihood that a distributed bednet was ultimately used for its intended purpose: to protect against malaria.

The Malaria Matters blog recently posted links to numerous examples of nets used for other purposes:

Net stories include use for fishing in Zambia, as bridal veils in Zambia and other countries and trapping edible ants in Uganda. These problems arise when LLIN distribution programs focus on the wrong numbers. It is not enough to say how many hundreds of nets have been distributed in a community. The real concern is whether they are used correctly and for the intended purpose.

The post also notes that:

The three most popular reasons for using bednets to dry fish were: fish dry faster on these nets, they don’t stick and not surprisingly, these nets are cheaper.

On the one hand, it’s important for donors to know what their donations accomplish, and if donors’ aim is to prevent malaria, the above stories provide evidence of the types of problems that can occur with unmonitored aid. On the other hand, if people are buying nets and using them in other ways that improve their lives – even if it’s not malaria prevention – it’s not clear to me that that impact isn’t worth considering as well.

The Disease Control Priorities report has a summary section (pg 60-85) listing interventions, along with cost-effectiveness estimates (in disability-adjusted life-years per US$) and some other basic info (target population, required infrastructure, etc.) We’ve created an Excel version of the list that we will be referring to in future posts:

List of interventions from Disease Control Priorities projiect (XLS)

This list is incomplete, in the sense that it does not list all of the interventions (even the recommended interventions) in the report. We aren’t sure why this is (and neither is the only DCP author we’ve spoken to so far). We will be using our notes on the report to add all interventions in over time.

Most numbers below from this table (2000 data).

• Malaria kills about 1.1 million people per year in developing countries.
• ~65% are 4 years old or younger. (This particular figure appears to contradict the data from the Global Burden of Disease report pg 126-7, which implies a proportion closer to 90%).
• The burden of malaria goes far beyond mortality, as the vast majority of number of cases are not fatal. Cases per year are estimated at ~200 million, lasting an average of ~4 days each.
• Malaria both exacerbates and is exacerbated by malnutrition (see pgs 415-417 of the Disease Control Priorities report).
• Malaria can, but usually does not, lead to permanent non-fatal debilitation including partial paralysis, quadriparesis, hearing and visual impairment, behavioral difficulties, language deficits, and epilepsy. Estimates for the numbers of these conditions caused by malaria total 13,000-15,000 cases worldwide per year.

Broadly, I would say that fighting malaria will reduce infant mortality and lower the overall burden on the local economy, health care system, and day-to-day quality of life, though it will not have much direct effect on adult mortality/morbidity. It’s therefore most relevant to goals 1-4 of this list.

Using Global Burden of Disease data, I put together a quick look at mortality in lower- and middle-income countries (LMICs) by age group. This is particularly important when seeking interventions that focus on adult mortality, one of the goals from this list.

Burden of mortality in LMICs by age group

All the way on the right of the table is the proportion of deaths that different conditions cause in each age group. (Row 4 gives each age group’s mortality as a proportion of total LMIC mortality.) Yellow coloring means that the condition accounts for 5%-10% of all the mortality in that age group; orange means 10-20%; red, greater than 20%. My notes (chapter and page references are to the Disease Control Priorities report):

• More than 20% of all LMIC deaths happen before the age of five (also see the pie chart in our developing world summary). Of these deaths, a total of 75% come from one of the following:
  • Perinatal conditions account for more than 20%. Better maternal care, as well as micronutrient supplementation for expectant mothers, could substantially reduce this burden (Chapter 26).
  • Lower respiratory infections (including pneumonia and influenza) account for close to 20%, even though vaccines can be highly effective against these diseases (pg 485-6). Other vaccine-preventable diseases account for an additional 10%.
  • Diarrhea accounts for another 15% of these deaths. Even rudimentary medical care (such as the use of oral rehydration therapy) can prevent such deaths (pg 378).
  • Malaria accounts for another 10%.
• Mortality between the ages of 5 and 14 is far less common. The biggest causes are accidents (25%), childhood-cluster (generally vaccine-preventable) diseases (15%), respiratory infections (~10%), and HIV/AIDS (7%).
• People between 15 and 44 – relatively close to the age range I would call “adult” – are at much higher risk than children from tuberculosis (accounting for nearly 10% of deaths in this range), HIV/AIDS (~20%), and maternal mortality (~6% of all deaths in this range; ~15% of female deaths in this range). Cancer (~8%), cardiovascular disease (~10%), and accidents (~15%) are also major causes of death in this age range.
• People between 45 and 59 face similar mortality risks from tuberculosis and accidents; lower (but still high) mortality risks from HIV/AIDS; and higher mortality risks from cancer, cardiovascular disease, and pulmonary obstructive disease. These three conditions are also the predominant causes of death in people over 60.

We previously performed similar analysis here, with a slightly less detailed breakdown of conditions and more focus on the developing-vs.-developed world contrast.