Risk analysis of housing energy efficiency interventions under model uncertainty

Abstract

Mathematical models can be used to evaluate the health impacts of housing energy efficiency interventions. However by their nature, models are subject to uncertainty and variability, which are important to quantify if used to support policy decisions. Models that are used to assess the impacts on health of housing energy efficiency interventions are likely to be based on a pair of linked component models: a building physics model which calculates changes in exposures and whose outputs then feed into a health impact model. Current methods to propagate uncertainty in a series of models, where the outputs of one model are inputs to another, invariably use Monte Carlo (MC) numerical simulation. In this paper, two methods are used to quantify the uncertainty in the impact of draught proofing on childhood asthma: the MC simulation method and a semi-analytical method based on integral transforms. Both methods give close results but it is argued that the semi-analytical method has some advantages over the MC method, particularly in quantifying the uncertainties in the main outputs of the building physics model before propagating them to the health model.