Overheating in buildings is predicted to increase as a result of a warming climate and urbanisation in most cities. With regards to responding to this challenge, decision makers ranging from_ design teams, local authorities, building users, national programs and market innovators; and during the different stages of a building’s service life, want to know a few pertinent matters: What space characteristics and buildings are at a higher risk and by how much?; What are the tradeoffs between alternative design and/or user-based actions?; What are the likely or possible consequences of their decisions?; What is the impact of climate change to indoor overheating?; among other decision support questions. However, such decision appraisal information still remains buried and dispersed in existing simulation models, and empirical studies, and not yet been clearly articulated in any existing study or model. Especially decision support information articulated in a way that gives each decision maker maximum capacity to anticipate and respond to thermal discomfort in different spaces and through the lifetime of a building. There is a need for an integrated and systematic means of building adaptation decision-support, which provides analytical leverage to these listed decision makers. A means that: 1) assimilates a range of indoor thermal comfort's causal and solution space processes; 2) reveals and enhances the exploration of the space and time-dependent patterns created by the dynamics of the indoor overheating phenomenon through time; and one that 3) imparts insight into decision strategy and its synthesis across multiple decision makers. This study recognises the lack of an overarching framework attending to the listed concerns. Therefore, the key aim of this thesis is to develop and test a building adaptation decision-support framework, which extends the scope of existing frameworks and indoor overheating risk models to facilitate trans-sectional evaluations that reveal temporal decision strategies. The generic framework frames a multi-method analysis aiming to underpin decision appraisal for different spaces over a 50 to 100-year time horizon. It constitutes an underlying architecture that engages the dimensions of decision support information generation, information structuring, its exploration and dissemination, to ease in drawing decision strategy flexibly and transparently. The multi-method framework brings together: 1) Systems thinking methods to a) facilitate the systematic exposure of the elements that shape indoor overheating risk, and b) reveal the processes that shape multi-stakeholder decision-making response over time; 2) The use of normative, predictive and exploratory building scenarios to a) examine the overheating phenomenon over time, and b) as a lens through which to explore the micro-dynamics brought about by aspects of heterogeneity and uncertainty; and 3) The application of both computational and optimization techniques to appraise potential routes towards indoor thermal comfort over an extended time scale by a) tracking shifts in frequency, intensity and distribution of indoor overheating vulnerability by causal elements over time and space; and b) tracking shifting optima of the heat mitigation solution space, with respect to time, climate futures, heterogeneity of spaces, and due to thermal comfort assumptions. The framework’s potential has been demonstrated through its application to office buildings in Nairobi.

In vitro fertilization (IVF) is used to help infertile couples achieve a live birth. Clinical studies have suggested that multiple, consecutive cycles of IVF can increase live birth rate significantly. Others have documented improved live birth rates from the use of new laboratory techniques for preimplantation genetic screening (PGS). This genetic screening technique seeks to determine the ploidy of the embryo prior to implantation into the woman. To date, no study has examined the cost-effectiveness of using IVF in conjunction with PGS compared to that of IVF alone for 3 consecutive cycles in achieving a live birth. This study compared the incremental cost-effectiveness ratios (ICER) from each intervention arm based on the clinical probabilities for each outcome and this study was grounded in the protection motivation theory. Costs were obtained from secondary sources, such as the literature and government databases. The model was constructed using a decision-analytical approach that allowed for z test statistical analysis of the outcomes, where the ICER is the dependent variable and the independent variables are the 2 interventions. The robustness of the model was tested through univariate and probabilistic sensitivity analysis and stratified by age groups. The results showed that PGS with IVF was cost-effective for women aged under 40 and women aged 40-42, but not for women over 42. Based on a willingness-to-pay threshold of $100,000, IVF with PGS was the most cost-effective strategy in all age groups. The positive social change implication of this study is such that understanding the costs associated with a new technology to achieve a live birth is significant for society to help guide clinical treatment of these patients.