title: Judgment under uncertainty; a probabilistic evaluation framework for decision-making about sanitation systems in low-income countries.
abstract: This paper introduces the probabilistic evaluation framework, to enable transparent and objective decision-making in technology selection for sanitation solutions in low-income countries. The probabilistic framework recognizes the often poor quality of the available data for evaluations. Within this framework, the evaluations will be done based on the probabilities that the expected outcomes occur in practice, considering the uncertainties in evaluation parameters. Consequently, the outcome of evaluations will not be single point estimates; but there exists a range of possible outcomes. A first trial application of this framework for evaluation of sanitation options in the Nyalenda settlement in Kisumu, Kenya, showed how the range of values that an evaluation parameter may obtain in practice would influence the evaluation outcomes. In addition, as the probabilistic evaluation requires various site-specific data, sensitivity analysis was performed to determine the influence of each data set quality on the evaluation outcomes. Based on that, data collection activities could be (re)directed, in a trade-off between the required investments in those activities and the resolution of the decisions that are to be made.
authors: Sanitary Engineering Section, Water Management Department, Faculty of Civil Engineering and Geosciences, Delft University of Technology, Stevinweg 1, 2628 CN Delft, The Netherlands. Shirin.Malekpour@monash.edu
authors: Shirin
authors: S
authors: Malekpour
authors: Jeroen
authors: J
authors: Langeveld
authors: Sammy
authors: S
authors: Letema
authors: François
authors: F
authors: Clemens
authors: Jules B
authors: JB
authors: van Lier
mesh_terms: D003657:Decision Making; D003906:Developing Countries; D007600:Judgment; D007630:Kenya; D015233:Models, Statistical; D008962:Models, Theoretical; D012498:Sanitary Engineering / Q000379:methods*; D012680:Sensitivity and Specificity; D035501:Uncertainty