Although unsafe water and sanitation is a killer via its contribution to undernutrition of children in particular, it creates its own mortality risk especially via diarrheal disease. The variables of importance in IFs are access to safe water (WATSAFE) and safe sanitation (SANITATION).  In IFs they affect 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 safe water and sanitation.  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 unsafe water and sanitation that then produces the associated implicit PAF.  IFs uses alternative and more risk-factor specific formulations to forecast values of safe access to water and sanitation over time.  The PAF associated with this explicit representation of WATSAFE and SANITATION (in combination) is compared with the PAF from the implicit calculation and the comparison alters the actual mortality pattern. 

To calculate WATSAFE and SANITATION (separately) the explicit formulation also uses both average years of adult education and GDP per capita, as in the distal formulation, but augments those with the spending of a country on health as a portion of GDP (which appears to serve reasonably well as a proxy for more general attention to the environment) and portion of the citizenry living on less than $1.25 per day.  For the actual equations, see the topic on outdoor urban air pollution equations in the infrastructure documentation.

Both access to safe water and to safe sanitation have ladders of access quality ranging from none to household connections.  Parameters affecting them must thus take into account those ladders and the specific level(s) the parameter affects. Multiplicative parameters ( watsafem and sanitationm ) can be used to change access at any level on the two ladders (the model normalizes access across levels to assure summation to 100 percent.   Another parameter pair ( watsafehldsw and sanithldsw ) can be used to hold the level of access at that of the first year, an approach useful for counterfactual scenario analysis.

Other parameters control targeting, both universal and relative.  With respect to absolute targeting, watsafetrgtval and watersafetrgtyr control those with no access to safe water (the proportion and the number of years to reach the target, respectively).  Similarly, sanitationtrgtval and sanitationtrgtyr control those with access to household connections.  The relative targeting approach, available only globally across all countries, allows the setting of a value based on the typical rate of access at different levels of GDP per capita (estimated cross-sectionally).  A target level ( watsafenoconsetar, sanithhconsetar, sanitnoconsetar ) would normally be no better (which could mean no higher or no lower) than the typical level at the country’s level of GDP per capita and could be, for instance, one standard error better (higher or lower depending on the variable being targeted)  than the typical level.  An associated parameter ( watsafenoconseyrtar, sanithhconseyrtar, sanitnoconseyrtar ) 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.  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.