Simple Analytics

Malaria analytics rely on simulation based analytics to link data from the past to decisions about the present and to guid policies about the future. An advantage of simulation-based analytics is that the same models and algorithms that were used to generate malaria intelligence through retrospective data analysis (see History of Exposure) are called on again to prospectively evaluate malaria policies. Simple analytics involves several steps:

1. Build a model

2. Calibrate the model using malaria intelligence

3. Construct a counter-factual baseline

4. Build a forecast

5. Compare policy scenarios

6. Develop advice