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Mosquito-zapping lasers, refrigerators for vaccines, and disease modeling: these are the three impressive technologies featured in a TED talk by Nathan Myhrvold. On the first two technologies, I responded in a piece “When engineering met public health” in the Huffington Post. What I didn’t get a chance to talk about was the importance of his third technology – disease modeling:

“One of the problems that you have if you're trying to eradicate malaria or reduce it is you don't know what's the most effective thing to do. Okay, we heard about bed nets earlier. You spend a certain amount per bed net. Or you could spray. You can give drug administration. There's all these different interventions but they have different kinds of effectiveness. How can you tell? So we've created, using our supercomputer, the world's best computer model of malaria, which we'll show you now…”

“By doing these kinds of simulations, we want to eradicate or control malaria thousands of times in software before we actually have to do it in real life; to be able to simulate both the economic trade-offs -- how many bed nets versus how much spraying? -- or the social trade-offs -- what happens if unrest breaks out?

Without a doubt, this software may well be a more powerful technology than a laser zapper or a vaccine refrigerator. Myhrvold notes that the disease modeling software developed by Global Good now informs eradication strategies for polio, HIV/AIDS, tuberculosis and malaria.

We can’t be more supportive of this work, an issue we’ve supported in our CGD Working Group on Value for Money in Global Health. In the Planning Allocation chapters in our More Health for the Money report, we recommend the Global Fund “optimize investments for greatest health impact.” True, the Global Fund is beginning to move in this direction, with its greater focus on targeting programs and grant-funded interventions to key populations. But the Global Fund can do much more by requiring that its recipients systematically consider intervention effectiveness, costs, environment, and other factors into a model, however simple or complex, to maximize health impact.

Detractors will say that these models are too hard, the data aren’t available, and recipients don’t have the technical capacity. But the data requirements for these models are not onerous or burdensome, nor do they need to involve Myhrvold’s supercomputers. Dr Tim Hallett, a reader at Imperial College London, found that impact could increase by 20%, simply by redirecting the same resources to the populations at greatest risk of infection and transmission. Simpler modeling tools producing “good-enough” decisions on how to allocate national resources are needed and are being developed by various groups – and the Global Fund should tap into these activities.

In the meantime, the Global Fund can encourage applicants to talk with networks and organizations such as Myhrvold’s and Hallett’s as well as the various disease modeling consortia (see here, here, and here) to make sure that proposed plans are good value for money. That can start a conversation where ultimately more lives will be saved and more people will benefit. When done appropriately, countries using more information and data can better target their interventions to the right populations and ultimately control, if not eliminate, their epidemics.

 

Victoria Fan is a research fellow and health economist at the Center for Global Development. She thanks Amanda Glassman, Jenny Ottenhoff, Justin Sandefur, and Huffington Post for their inputs. You can follow Victoria Fan on Twitter at @FanVictoria.