@article{31460,
  keywords = {Water sanitation hygiene (WaSH), WaSH poverty index, Object oriented Bayesian Network, Planning, Kenya},
  author = {Giné-Garriga R and Requejo D and Molina J L and Pérez-Foguet A},
  title = {A novel planning approach for the water, sanitation and hygiene (WaSH) sector: The use of object-oriented bayesian networks.},
  abstract = {<p>Conventional approaches to design and plan water, sanitation, and hygiene (WaSH) interventions are not suitable for capturing the increasing complexity of the context in which these services are delivered. Multidimensional tools are needed to unravel the links between access to basic services and the socio-economic drivers of poverty. This paper applies an object-oriented Bayesian network to reflect the main issues that determine access to WaSH services. A national Program in Kenya has been analyzed as initial case study. The main findings suggest that the proposed approach is able to accommodate local conditions and to represent an accurate reflection of the complexities of WaSH issues, incorporating the uncertainty intrinsic to service delivery processes. Results indicate those areas in which policy makers should prioritize efforts and resources. Similarly, the study shows the effects of sector interventions, as well as the foreseen impact of various scenarios related to the national Program.</p>
},
  year = {2018},
  journal = {Environmental modelling & software},
  volume = {103},
  pages = {1-15},
  issn = {13648152},
  url = {https://upcommons.upc.edu/bitstream/handle/2117/115984/novel_planning_preprint.pdf},
  doi = {10.1016/j.envsoft.2018.01.021},
  language = {eng},
}