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To be truly able to inform policy, models must include a cost component and they must translate the detailed logistics of malaria interventions to both a cost and a measure of impact. This then allows for optimization algorithms to explore the best combination of malaria interventions under varied resource limitations. The group is exploring the development of frameworks that facilitate the usage of these algorithms by control programmes.

Atome figure 2
Predicted optimal intervention package under different budget constraints for a putative African population with a mean malaria true prevalence of 10%.