Designing the building space of a shopping street to use as a disaster evacuation shelter during the COVID-19 pandemic: A case study in Kobe, Japan.

This study considers the risk of a natural hazard-induced disaster occurring during a pandemic, such as the novel coronavirus (COVID-19) pandemic, and develops the idea of utilizing a shopping street with disaster-proof buildings as a temporary evacuation shelter by incorporating countermeasures against the spread of infectious diseases. Using a case study of a shopping street in Kobe, Japan, we estimate shelter capacity by considering the requirement of 6 m2 of space allotted for each person. The shelter can accommodate 1194 evacuees and provide them with food and drinks for one day, even in the worst case of lifeline disruption. This study proposes a method of designing shelter space, and demonstrates how non-homogeneous and noncontinuous spaces within shopping street buildings can be applied to prevent the spread of infection, through the classification of evacuee types and use of space and facilities designated for each type. The study further examines the liability issue of secondary infection at the shelter with reference to civic law and the roles of government in developing a distributed evacuation framework.

Successful Community Participation in Climate Change Adaptation Programs: on Whose Terms?

Community participation in climate change adaptation (CCA) programs has been advocated for long, but its implementation remains uncertain. There is also very little understanding and consensus on how and to what extent local communities can and should be involved in these projects. Arguably, both the concept and practice of community participation remain equivocal and contentious due to a lack of systematic effort to define the participatory framework in CCA. While the framework for community participation can be adopted from other planning and management discourses, yet they are typically expert-driven. The local communities hardly play a role in designing the framework. This study, therefore, took an alternative approach to define the meaning and implication of community participation from local communities' perspectives. To this end, we used the grounded theory qualitative research methods to survey 50 respondents across five rural communities in climate change impacted Northern Ghana. To evaluate the communities' meaningful participation in the adaptation projects, respondents suggested three critical parameters-First, community participation in a CCA project can be considered successful if the project contributes towards the livelihood security of the community. Second, the project outcome should be tangible. Third, the project should enhance the community's skills and training such that the community can run a similar project in the future without much dependence on external agencies. This study provides an alternative methodological insight on how to design and operationalize meaningful community participation in CCA that will have universal application irrespective of the geographical and socio-cultural boundaries.

Dynamic Stochastic Macroeconomic Model of Disaster Risk Reduction Investment in Developing Countries.

This research formulates a dynamic stochastic macroeconomic model that includes an optimization problem for the formation of stock of human capital, production capital, and household assets, and quantitatively examines economic impacts of disaster on developing countries. We further investigate the optimal policy of development of disaster risk reduction (DRR) capital by considering costs of DRR investment, and show that the effect of DRR investment on economic growth is like a single-peaked curve with respect to the DRR investment rate, which implies that overaccumulation could decelerate economic growth. Moreover, this study emphasizes an effect that DRR capital increases the shadow values of other types of capital and assets by reducing risks of destruction. Importantly, this effect emerges even in cases of process, in which disaster does not actually occur for a long period. We decompose the effects of DRR investments into two parts: "ex-ante risk reduction effect" (ARRE) and "ex-post damage mitigation effect" (PDME). Furthermore, we develop a method of measuring ARRE and PDME by applying the results of Monte Carlo simulation, and show that the scale of ARRE is nonnegligible using a case study of Pakistan. The results imply that types of models that cannot valuate ARRE underestimate the value of DRR investment.