Policymakers who work in the public health sector may rely on the help of quantitative models to support their choice of control strategy against a particular infectious disease. While policymakers have a large number of decision support models to choose from, hardly any of these tools are used to design an intervention strategy that can work well across multiple diseases. This is in part because of the need for large amounts of precise, detailed data and the presence of many unknown or confounding factors, which complicates attempts to make single-disease models, let alone multi-disease models. Is this highly data-intensive and detailed predictive approach necessary to make a good decision about how limited health resources should be allocated against multiple threats? Could the inclusion of multiple pathogens into a single decision support tool change the recommendation of an “optimal” intervention? In the following thesis, a novel multi-disease model is created. Rather than attempting to make a predictive tool to try and foresee a deeply uncertain future, this multi-disease model uses an exploratory approach to systematically evaluate the impacts of uncertain parameters. Many objective optimization techniques are used to find robust intervention strategies that work well for decision-makers who are interested in increasing the impact of their limited resources.

Humanitarians and global health actors come to the aid of many people every year, with the aim of preventing disease, increasing wellbeing, and providing (medical) aid to those suffering from disease. One of the contexts in which they operate is that of an epidemic. An epidemic is dynamic by nature and provides a complex and evolving environment in which medical aid needs to be provided. A key aspect in a response to an epidemic is logistics – specifically the allocation of resources such as personnel and medical supplies. These resources are often limited, calling for a targeted and strategic response. There is a variety of studies tackling the problem of resource allocation in the context of an epidemic, which include sequential decisions as the epidemic evolves, as well as the choice between several locations to which resources can be sent. However, these studies often assume decision-makers have complete information on the situation at hand and can make “perfect” choices. In reality, due to the large number of actors involved in a response, poor (telecommunication) infrastructure, and the fact that an epidemic is a moving target due to its dynamic nature, decision-makers often have to deal with incomplete and uncertain information on the number of patients and the way the epidemic is evolving.

Site selection is a critical factor in the ability to provide safe and healthy environment for refugees. At the outset of an emergency, limited resource and time create large planning uncertainties and current refugee sites’ assessments based on field visit are no longer adequate. The selection of unsuitable locations triggers a number of issues such as environmental degradation, competition for scarce resources and, exploitation of water sources. These can be reduced through a rational refugee allocation decision process. The question that arises is, can the refugee allocation process be supported by a structured decision-making (SDM) approach and more specifically, by a portfolio decision analysis (PDA) model? Focusing on water security criteria, this study presents the initial phases of the SDM-approach intended to ensure a more sustainable allocation of newly-arrived refugees among new and/or existing hosing sites. To this end, a procedural tool for supporting WASH (Water, Sanitation and Hygiene) officers in the site assessment is proposed. This was obtained based on 15 semi-structured interviews and questionnaires carried out in a global stakeholder environment, in order to make the SDM framework applicable to other settings.
The generic procedural tool was tested in a case-study in south-western Uganda by applying a portfolio decision analysis model. Local and global data were combined with stakeholder preferences to predict the performance of diverse sets of alternatives. The latter were generated according to different combinations of numbers of refugees, hosting locations and percentage of water extracted from surface water, groundwater and rain water. To identify efficient portfolios, we used the Robust Portfolio Modelling - Decisions software. Results showed that overlooked solutions outperforms over the current allocation strategy. In specific, the scatter of newly arrived refugees showed the highest scores on availability of water, socio-economic costs and host communities' advantages. The proposed framework provides also options for the optimal repartition of the future water extraction among available water sources, aiming to avoid their depletion while preserving sustainable costs of the water services.

This research emerged from the need to improve the Netherlands’ contribution to international water and sanitation service delivery. Over the previous two decades these serviced were not found to be sufficient sustainable according to the Dutch Ministry of Foreign Affairs (2013). This thesis researches how development aid organisations can contribute to sustainable WASH services by looking to the strategic planning process.
In this research an adaptive planning approach is designed to contribute to long-term sustainable WASH services. It is a systematic step-wise pro-active approach where planners need to think beforehand of ways a plan might fail and design adaptation actions to guard against such failure. An adaptive planning approach has been adapted for sustainable WASH services and consist of three systematic steps:(1) defining the impact and critical assumptions of the WASH programme, (2) defining relevant uncertainties by using contextual scenarios, and (3) defining adaptation actions and the timing of the actions.
The content and the applicability of the adaptive planning approach for long-term sustainable WASH has been examined during this research in the context of Bangladesh. To examine the approach a single case study is used. In this research multiple research methods have been applied to improve the reliability and validity of the findings, but also to capture different perspectives on this topic. First by means of an adaptive planning workshop in the Netherlands with WASH experts from the Dutch NGO Simavi and sequential by means of a field-research in Bangladesh, including interviews with local project stakeholders and field-trips.
It can be concluded that WASH experts in the Netherlands and the project stakeholders in Bangladesh reacted differently on the three systematic steps of the adaptive planning approach for sustainable WASH. The indirectly involved project stakeholders - WASH experts - found it easy to question project assumptions and to identify critical assumptions for the project failure but could not propose specific adaptation actions. The directly involved project stakeholder - local project stakeholders in Bangladesh - found it more difficult to criticize and reassess project assumptions, but they defined feasible adaptation actions.
It can be argued that ‘misrepresentation’ of critical assumptions of the project created hazard to all sequential steps of the adaptive planning approach for long-term sustainable WASH services.
Purposely defining scenarios of success and gloss over the potential for failure, conflicts with the pro-active adaptive planning approach to define adaptation actions at the begin of the project. Therefore, it is questionable whether all systematic steps of the approach serve the interest of all project stakeholders. This makes that the adaptive planning approach, as it is designed now, does not contribute to long-term sustainable WASH services in environments where project incentives are on benefits and not on robustness.
Based on the findings of this research, it can be recommended that different components of the adaptive planning approach for long-term sustainable WASH services should be practices by different involved parties.

Climate change and urbanization put increasing stress on urban water management (UWM). Prolonged periods of drought in densely populated areas threaten the quantity and quality of freshwater sources. Closing the water cycle by wastewater reuse can alleviate pressure on these freshwater sources. However, a closed water system requires a different institutional environment. A comprehensive and specific institutional analysis framework can provide guidance to stakeholders in the regional water system. A literature review has concluded that academia has not yet provided such framework (van Es, 2017a). This research proposes an institutional analysis framework by combining two widely used frameworks in institutional analysis: the four-layer model of Williamson (1998) and the Institutional Analysis and Development (IAD) framework of Ostrom (2011). The aim of the institutional analysis framework is twofold: 1) to find the critical issues that can be expected in closing the regional water cycle and 2) to provide recommendations on coordination of the action situations in which the critical issues are addressed. The framework is applied to the case of closing the water cycle in the service area of water authority Delfland in the western part of the Netherlands. This research shows that the proposed institutional analysis framework is highly useful in finding and coordinating crucial issues in closing the water cycle. An empirical operation of the four-layer model of Williamson (1998) provided a deep and structured understanding of the expected issues by relevant stakeholders. It also provided insight into the attitude and main drivers of stakeholders on a closed water cycle. The IAD framework of Ostrom (2011) helped to specify the most critical action situations. Further research can contribute to the field of institutional analysis by conducting more case studies with the proposed Williamson-Ostrom framework and execute the case study in a theoretical way instead of an empirical way.