Air pollution and health - IFs

Health analysis systems typically can help us either (1) to understand better where broad, long-term patterns of human development appear to be taking us with respect to global health, or (2) to consider opportunities for intervention and achievement of alternative health futures, enhancing the foundation for decisions and actions that improve health.

Broad structural models with deep distal drivers such as technological and income advance (e.g., that of the Global Burden of Disease or GBD) assist in the first purpose by relating those distal development drivers to longer-term pattern change in health.  Distal driver formulations tend to produce forecasts of constantly decreasing death rates.  Yet we know, for instance, that some more proximate factors driving mortality, such as smoking, obesity, and road traffic accidents, tend to increase in developing societies with income and education, before at least smoking and road traffic deaths (and perhaps also obesity) typically decline. The inclusion of such proximate drivers thus opens the door to the second, allowing for consideration of interventions in the pursuit of alternate health futures.  A hybrid and integrated model form like that of IFs can help with both purposes and provide a richer overall picture of alternative health futures.

The integrated nature of the IFs modeling system further allows us to think about feedback loops between health outcomes and larger development variables such as economic progress and population structure.