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As coastal communities increasingly plan for climate change, there is a need to understand factors that influence whether planned actions get implemented. This study examines the implementation of coastal adaptation actions across Nova Scotia, Canada, the first province in the country to establish a regional policy framework to address adaptation by requiring municipalities to prepare Municipal Climate Change Action Plans (MCCAPs). Using the MCCAPs from 20 coastal communities, this study employs a mixed-methods approach that includes content analysis, surveys, and expert interviews to follow up on the actions identified as priorities in these plans. It finds that the MCCAPs successfully stimulated coastal adaptation throughout the province: within six years, nearly 75% of the 331 priority actions in these plans were implemented to some degree. Logistic regression models, supported by interviews with municipal representatives, indicate that political continuity and public participation throughout the planning process are significant determinants of successful implementation. [ABSTRACT FROM AUTHOR]

The economic impacts of pandemics can be enormous. However, lockdown and human mobility restrictions are effective policies for containing the spread of the disease. This study proposes a framework for assessing the economic impact of varying degrees of movement restrictions and examines the effectiveness of this framework in a case study examining COVID‐19 control measures in Japan. First, mobile network operators data and total employment statistics on a 500‐meter grid scale are used to determine the status of mobility restrictions and impacts on consumption in 30 industrial sectors. Next, the economic impacts are assessed using a spatial computable general equilibrium (CGE) model, proven to yield valuable insights into the total economic impacts of natural disasters. In sectors that implement telework and e‐commerce—wholesale/retail, finance/insurance, and communication sectors—estimates of production and GDP are obtained that are close to the actual figures. The current case study is limited to Japan, but similar analysis can be conducted by using the CGE model for each country and open mobility data. Thus, the framework has potential to serve as an effective tool for assessing trade‐offs between infection risks and economic impacts to inform policy‐making by combining with findings from epidemiology. [ABSTRACT FROM AUTHOR]

A resilient community is one that does not experience serious degradation in critical services when a hazard occurs and, in the event of degradation or failure, recovers to a similar or better level of service in a reasonable amount of time. The most efficient means of making a community resilient is to make its critical services and capital robust minimize damage/loss probability or the consequences from damage/loss through mitigation. If a community's critical services and capital are not robust, efforts must be put into recovery. Based on the measurable aspects of community capital, we have developed a simulation model called ResilUS that operationalizes community resilience across multiple, hierarchical scales in relation to a range of policy and decision variables associated with each scale. ResilUS is implemented using fragility curves to model loss and Markov chains to model recovery with respect to time. ResilUS was applied to the 1994 Northridge earthquake disaster in order to calibrate several output variables with empirical data. ResilUS represents a significant step forward for spatial decision support for disaster mitigation and recovery planning, in comparison to existing loss estimation models. KEYWORDS: resilience, recovery, modeling, disasters, Northridge earthquake, Introduction A resilient community is one that does not experience serious degradation in critical services when an earthquake or other disturbance occurs and, in the event of degradation or failure, [...]

An agent-based object-oriented model for household displacements is presented and used to analyze household decision-making after a hypothetical earthquake in the City of Vancouver, Canada. Temporary displacements and permanent relocation are accounted for. The model for households include considerations of socioeconomic demographics, social networks, and disaster preparedness. The analysis results indicate that nearly 70,000 persons are expected to be displaced by the earthquake. Of those, close to 19,000 will need public sheltering. In addition, nearly 40,000 persons are expected to relocate in the years following the earthquake. Among the displaced persons, occupants of multi-family pre-code and low-code buildings are over-represented. Among those needing public shelter or relocation, there is a disproportionately high number of renters and low-income households. The models in this paper can help the development of pre-disaster plans by suggesting optimal location of public shelters, and by identifying decisions that reduce the number of households relocating. [ABSTRACT FROM AUTHOR]

Input-output equations and linear programming may be used to assess the economic impact of power disruption during an earthquake. The study points out that lost productivity may become very high and that reallocation of scarce power across sectors could offset losses significantly. Moreover, heightened restoration with regards electricity transmission could offset production losses even further.