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Research papers, University of Canterbury Library

This paper presents the preliminary conclusions of the first stage of Wellington Case Study project (Regulating For Resilience in an Earthquake Vulnerable City) being undertaken by the Disaster Law Research Group at the University of Canterbury Law School. This research aims to map the current regulatory environment around improving the seismic resilience of the urban built environment. This work provides the basis for the second stage of the project which will map the regulatory tools onto the reality of the current building stock in Wellington. Using a socio-legal methodology, the current research examines the regulatory framework around seismic resilience for existing buildings in New Zealand, with a particularly focus on multi-storey in the Wellington CBD. The work focusses both on the operation and impact of the formal seismic regulatory tools open to public regulators (under the amended Building Act) as other non-seismic regulatory tools. As well as examining the formal regulatory frame, the work also provides an assessment of the interactions between other non-building acts (such as Health and Safety at Work Act 2015) on the requirements of seismic resilience. Other soft-law developments (particularly around informal building standards) are also examined. The final output of this work will presents this regulatory map in a clear and easily accessible manner and provide an assessment of the suitability of this at times confusing and patchy legal environment as Wellington moves towards becoming a resilient city. The final conclusion of this work will be used to specifically examine the ability of Wellington to make this transition under the current regulatory environment as phase two of the Wellington Case Study project.

Videos, UC QuakeStudies

A video of a presentation by Professor David Johnston during the fourth plenary of the 2016 People in Disasters Conference. Johnston is a Senior Scientist at GNS Science and Director of the Joint Centre for Disaster Research in the School of Psychology at Massey University. The presentation is titled, "Understanding Immediate Human Behaviour to the 2010-2011 Canterbury Earthquake Sequence, Implications for injury prevention and risk communication".The abstract for the presentation reads as follows: The 2010 and 2011 Canterbury earthquake sequences have given us a unique opportunity to better understand human behaviour during and immediately after an earthquake. On 4 September 2010, a magnitude 7.1 earthquake occurred near Darfield in the Canterbury region of New Zealand. There were no deaths, but several thousand people sustained injuries and sought medical assistance. Less than 6 months later, a magnitude 6.2 earthquake occurred under Christchurch City at 12:51 p.m. on 22 February 2011. A total of 182 people were killed in the first 24 hours and over 7,000 people injured overall. To reduce earthquake casualties in future events, it is important to understand how people behaved during and immediately after the shaking, and how their behaviour exposed them to risk of death or injury. Most previous studies have relied on an analysis of medical records and/or reflective interviews and questionnaire studies. In Canterbury we were able to combine a range of methods to explore earthquake shaking behaviours and the causes of injuries. In New Zealand, the Accident Compensation Corporation (a national health payment scheme run by the government) allowed researchers to access injury data from over 9,500 people from the Darfield (4 September 2010) and Christchurch (22 February 2011 ) earthquakes. The total injury burden was analysed for demography, context of injury, causes of injury, and injury type. From the injury data inferences into human behaviour were derived. We were able to classify the injury context as direct (immediate shaking of the primary earthquake or aftershocks causing unavoidable injuries), and secondary (cause of injury after shaking ceased). A second study examined people's immediate responses to earthquakes in Christchurch New Zealand and compared responses to the 2011 earthquake in Hitachi, Japan. A further study has developed a systematic process and coding scheme to analyse earthquake video footage of human behaviour during strong earthquake shaking. From these studies a number of recommendations for injury prevention and risk communication can be made. In general, improved building codes, strengthening buildings, and securing fittings will reduce future earthquake deaths and injuries. However, the high rate of injuries incurred from undertaking an inappropriate action (e.g. moving around) during or immediately after an earthquake suggests that further education is needed to promote appropriate actions during and after earthquakes. In New Zealand - as in US and worldwide - public education efforts such as the 'Shakeout' exercise are trying to address the behavioural aspects of injury prevention.

Research papers, The University of Auckland Library

Background: Up to 6 years after the 2011 Christchurch earthquakes, approximately one-third of parents in the Christchurch region reported difficulties managing the continuously high levels of distress their children were experiencing. In response, an app named Kākano was co-designed with parents to help them better support their children’s mental health. Objective: The objective of this study was to evaluate the acceptability, feasibility, and effectiveness of Kākano, a mobile parenting app to increase parental confidence in supporting children struggling with their mental health. Methods: A cluster-randomized delayed access controlled trial was carried out in the Christchurch region between July 2019 and January 2020. Parents were recruited through schools and block randomized to receive immediate or delayed access to Kākano. Participants were given access to the Kākano app for 4 weeks and encouraged to use it weekly. Web-based pre- and postintervention measurements were undertaken. Results: A total of 231 participants enrolled in the Kākano trial, with 205 (88.7%) participants completing baseline measures and being randomized (101 in the intervention group and 104 in the delayed access control group). Of these, 41 (20%) provided full outcome data, of which 19 (18.2%) were for delayed access and 21 (20.8%) were for the immediate Kākano intervention. Among those retained in the trial, there was a significant difference in the mean change between groups favoring Kākano in the brief parenting assessment (F1,39=7, P=.012) but not in the Short Warwick-Edinburgh Mental Well-being Scale (F1,39=2.9, P=.099), parenting self-efficacy (F1,39=0.1, P=.805), family cohesion (F1,39=0.4, P=.538), or parenting sense of confidence (F1,40=0.6, P=.457). Waitlisted participants who completed the app after the waitlist period showed similar trends for the outcome measures with significant changes in the brief assessment of parenting and the Short Warwick-Edinburgh Mental Well-being Scale. No relationship between the level of app usage and outcome was found. Although the app was designed with parents, the low rate of completion of the trial was disappointing. Conclusions: Kākano is an app co-designed with parents to help manage their children’s mental health. There was a high rate of attrition, as is often seen in digital health interventions. However, for those who did complete the intervention, there was some indication of improved parental well-being and self-assessed parenting. Preliminary indications from this trial show that Kākano has promising acceptability, feasibility, and effectiveness, but further investigation is warranted. Trial Registration: Australia New Zealand Clinical Trials Registry ACTRN12619001040156; https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377824&isReview=true

Research papers, The University of Auckland Library

The supply of water following disasters has always been of significant concern to communities. Failure of water systems not only causes difficulties for residents and critical users but may also affect other hard and soft infrastructure and services. The dependency of communities and other infrastructure on the availability of safe and reliable water places even more emphasis on the resilience of water supply systems. This thesis makes two major contributions. First, it proposes a framework for measuring the multifaceted resilience of water systems, focusing on the significance of the characteristics of different communities for the resilience of water supply systems. The proposed framework, known as the CARE framework, consists of eight principal activities: (1) developing a conceptual framework; (2) selecting appropriate indicators; (3) refining the indicators based on data availability; (4) correlation analysis; (5) scaling the indicators; (6) weighting the variables; (7) measuring the indicators; and (8) aggregating the indicators. This framework allows researchers to develop appropriate indicators in each dimension of resilience (i.e., technical, organisational, social, and economic), and enables decision makers to more easily participate in the process and follow the procedure for composite indicator development. Second, it identifies the significant technical, social, organisational and economic factors, and the relevant indicators for measuring these factors. The factors and indicators were gathered through a comprehensive literature review. They were then verified and ranked through a series of interviews with water supply and resilience specialists, social scientists and economists. Vulnerability, redundancy and criticality were identified as the most significant technical factors affecting water supply system robustness, and consequently resilience. These factors were tested for a scenario earthquake of Mw 7.6 in Pukerua Bay in New Zealand. Four social factors and seven indicators were identified in this study. The social factors are individual demands and capacities, individual involvement in the community, violence level in the community, and trust. The indicators are the Giving Index, homicide rate, assault rate, inverse trust in army, inverse trust in police, mean years of school, and perception of crime. These indicators were tested in Chile and New Zealand, which experienced earthquakes in 2010 and 2011 respectively. The social factors were also tested in Vanuatu following TC Pam, which hit the country in March 2015. Interestingly, the organisational dimension contributed the largest number of factors and indicators for measuring water supply resilience to disasters. The study identified six organisational factors and 17 indicators that can affect water supply resilience to disasters. The factors are: disaster precaution; predisaster planning; data availability, data accessibility and information sharing; staff, parts, and equipment availability; pre-disaster maintenance; and governance. The identified factors and their indicators were tested for the case of Christchurch, New Zealand, to understand how organisational capacity affected water supply resilience following the earthquake in February 2011. Governance and availability of critical staff following the earthquake were the strongest organisational factors for the Christchurch City Council, while the lack of early warning systems and emergency response planning were identified as areas that needed to be addressed. Economic capacity and quick access to finance were found to be the main economic factors influencing the resilience of water systems. Quick access to finance is most important in the early stages following a disaster for response and restoration, but its importance declines over time. In contrast, the economic capacity of the disaster struck area and the water sector play a vital role in the subsequent reconstruction phase rather than in the response and restoration period. Indicators for these factors were tested for the case of the February 2011 earthquake in Christchurch, New Zealand. Finally, a new approach to measuring water supply resilience is proposed. This approach measures the resilience of the water supply system based on actual water demand following an earthquake. The demand-based method calculates resilience based on the difference between water demand and system capacity by measuring actual water shortage (i.e., the difference between water availability and demand) following an earthquake.