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.

Broadly-speaking, we think of “cost-effectiveness” as referring to how much of value is accomplished for a given amount of money. If two interventions are both proven and scalable to similar degrees, the more cost-effective one is a better investment because it allows the same donation to accomplish more of value. However, “value” means different things to different donors: to some, $200 to save a child’s life might be a great deal, while others may prefer $450 to repair a fistula.

We prefer to leave major judgment calls to our donors when practical. This means that rather adopt a single definition of value (such as Disability-Adjusted Life-Years), we hope to find the most cost-effective interventions for several different definitions of value. We can’t cover every possible notion of what’s worth funding, but we hope to be of use to as many donors as possible within the cause of developing-world health (our current focus – we will be moving on to economic empowerment later).

The following are several philosophical goals – i.e., definitions of what results make an intervention “valuable” – that we think will appeal to many donors.

1. DALYs averted. Although it isn’t our favorite measure of value, the Disability-Adjusted Life-Year is a widely used metric that considers all forms of mortality and morbidity. Some donors may feel most comfortable aiming to avert as many DALYs as possible for their donation.
2. Economic benefits. Health problems impose an economic burden, not just a moral one. There are sometimes attempts (such as the “benefit:cost ratio” used by the Copenhagen Consensus and some versions of the social return on investment metric) to combine economic and moral benefits into a single figure, measured in dollars.
3. Life-years saved – for those who put a lot of weight on being alive vs. not alive (and less weight on quality of life). Interventions that focus on infant mortality are likely to be cost-effective in terms of saving life-years.
4. Lives saved.
5. Adult lives saved. It is common to value adult lives more than children’s lives. In addition, adults are more likely to have dependents, making their deaths arguably more tragic (in a way that DALYs could capture in theory, but that DALY estimates generally don’t capture in practice).
6. Cases of extreme suffering prevented/rectified. This goal has several subcategories, for different conceptions of what constitutes extreme suffering. One that jumps to mind is fistula (and other deformities associated with ostracization).
7. People brought to a normal standard of health and potential productivity. In some ways the opposite of the cause immediately above, in that it focuses on helping those with high potential rather than helping those with high need. (There are different places one could draw the line for “normal health and potential productivity” – is it enough to prevent/cure someone’s blindness, or is it also important that they be adequately nourished and have reasonable job opportunities?)
8. Unwanted pregnancies averted / population growth slowed. Some donors might see births averted as a negative; others might feel that it is the key to better quality of life and sustainability.

Some of these metrics are highly well-defined and relatively easy to find or form cost-effectiveness estimates on. Others are far less so. We aren’t necessarily going to be conducting a separate search on interventions for each, but we think it’s productive to get as many appealing “goals” on the table as possible before beginning to narrow down the programs we’re focusing on. We hope that we won’t leave out programs whose potential effects are highly appealing to a large/important set of donors, even if they fail a “cost-effectiveness test” based on other metrics.

If you feel that we’re leaving out any important ones, please let us know. (We will also be consulting with our supporters and Advisory Board on this question.)

Business Week writes:

According to the World Health Organization, about half of the imaging equipment sent to developing countries goes unused because local technicians aren’t trained to operate it or lack the necessary spare parts.

(H/t Aman at THDBlog)

Is this possible?

(Note: I tried to find the original WHO source and all I could find was this article stating that “more than half of the medical equipment in developing countries is left unused or broken because it is too complicated or expensive to operate and repair,” which is substantially different.)