Indoor air pollution affects forecasts of under-5 mortality related to respiratory infection and adult (30+) mortality related to respiratory disease.  IFs uses the percentage of people using solid fuels as their primary source of energy (ENSOLFUEL) as a proxy for indoor air pollution.

The full model calculation is:

ENSOLFUEL = ratio of electricity use to total primary energy demand, in percentage

GDPPCP = gross domestic product per capita at purchasing power parity in thousand constant 2005 dollars

INFRAELECACC(national, that is, not urban or rural but total) = percent of total population with access to electricity in percentage

• multiplicative shift factor: ENSOLFUELShift; never converges
• multiplier: ensolfuelm
• targeting parameters: ensolfuelsetar, ensolfueltrgtyr, ensolfuelsetar, ensolfuelseyrtar
• hold switch: ensolflhldsw, fixes value of ENSOLFUEL at initial year value
• cross-sectional data, GLM regression, R-squared = 0.81

The distal driver formulation for ENSOLFUEL uses the following formula, which relies also on EDYRSAG25 and average years of formal education for adults over 25.

We use a multiplicative shift factor to match initialization data in the first year, and keep it constant in our forecast. Following work done through the WHO Desai and others (2004), IFs adjusts in the full formulation (not the distal one) the percentage of population exposed to indoor smoke from solid fuels by a ventilation coefficient ( ensfvent ) that ranges from 0 to 1. A coefficient of 0 indicates no exposure to pollutants from solid fuel use, whereas a coefficient of 1 indicates full exposure: 

Since in the case of indoor air pollution there are only 2 categories–exposed or not exposed, in which case RR = 1 - the mortality effect can then be simplified to:

Where P is the percentage of population exposed to indoor smoke from solid fuel, adjusted for ventilation; and RR is the relative risk for the exposed population ^[1] .  The table below lists RRs used in IFs.