One of the most important health risk factors in the developing world, especially for women and children under 5 is the use of solid fuels for cooking (and heating) indoors (ENSOLFUEL).  It is a major cause of respiratory diseases.  In IFs it affects mortality rates via the mechanism that the model uses to modify cause-specific mortality from the distal driver formulation by using information concerning actual risk level in a country.  The core of that approach is to compare the risk-specific population attributable fraction (PAF) of total morality as calculated from the distal drivers with the PAF calculated from the actual level of the risk in the country. 

The figure below shows the approach for indoor air pollution from the use of solid fuels.  The two key variables in the distal driver formulation at any point in time (ignoring the technology factor that adds dynamics over time) are GDP per capita at purchasing power parity and years of adult education.  They are used in a cross-sectionally estimated function to calculate indoor air pollution (linked to solid fuel use) that then produces the associated implicit PAF.  IFs uses an alternative and more risk-factor specific formulation to forecast values of solid fuel use over time.  The PAF associated with this explicit representation of ENSOLFUEL is compared with the PAF from the implicit calculation and the comparison alters the actual mortality pattern. 

To calculate ENSOLFUEL the explicit formulation also uses GDP per capita, as in the distal formulation, but augments it with access to electricity.  For the actual equation, see the topic on equations for solid fuel use in the infrastructure documentation.  A multiplicative parameter ( ensolfuelm ) can be used to change solid fuel use in scenario analysis.  Another parameter ( ensolhldsw ) can be used to hold the rate of solid fuel use at the level of the first year, an approach useful for counterfactual scenario analysis.

Major factors affecting the health impact of indoor solid fuel use are the efficiency and ventilation of the stoves.  The model provides a coefficient ( ensfvent ) for scenario analysis concerning those factors.

Much analysis on this health issue will want to use control of solid fuel use, partly through the use of a multiplier ( ensolfuelm ).  There is also targeting of solid fuel use and the model provides two different kinds of targeting parameters, absolute and relative.  The absolute (or universal) targeting allows the setting of a year ( ensolfueltrgtyr ) by which solid fuel use would be eliminated; it is available country by country.  The relative targeting approach, available only globally across all countries, allows the setting of a value based on the typical rate of solid fuel use at different levels of GDP per capita (estimated cross-sectionally).  A target rate ( ensolfuelsetar ) would normally be no higher than the typical rate at the country’s level of GDP per capita and could be, for instance, one standard error lower than the typical rate.  An associated parameter ( ensolfuelseyrtar ) identifies the number of years over which a country would move to the target level.  If a country already meets or exceeds a relative target, it will not move (adversely) toward it.  Moreover, only the absolute or relative target should be used in analysis, not both together–an attempt to use both together will result in neither being used.