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Research papers, University of Canterbury Library

Natural hazard disasters often have large area-wide impacts, which can cause adverse stress-related mental health outcomes in exposed populations. As a result, increased treatment-seeking may be observed, which puts a strain on the limited public health care resources particularly in the aftermath of a disaster. It is therefore important for public health care planners to know whom to target, but also where and when to initiate intervention programs that promote emotional wellbeing and prevent the development of mental disorders after catastrophic events. A large body of literature assesses factors that predict and mitigate disaster-related mental disorders at various time periods, but the spatial component has rarely been investigated in disaster mental health research. This thesis uses spatial and spatio-temporal analysis techniques to examine when and where higher and lower than expected mood and anxiety symptom treatments occurred in the severely affected Christchurch urban area (New Zealand) after the 2010/11 Canterbury earthquakes. High-risk groups are identified and a possible relationship between exposure to the earthquakes and their physical impacts and mood and anxiety symptom treatments is assessed. The main research aim is to test the hypothesis that more severely affected Christchurch residents were more likely to show mood and anxiety symptoms when seeking treatment than less affected ones, in essence, testing for a dose-response relationship. The data consisted of mood and anxiety symptom treatment information from the New Zealand Ministry of Health’s administrative databases and demographic information from the National Health Index (NHI) register, when combined built a unique and rich source for identifying publically funded stress-related treatments for mood and anxiety symptoms in almost the whole population of the study area. The Christchurch urban area within the Christchurch City Council (CCC) boundary was the area of interest in which spatial variations in these treatments were assessed. Spatial and spatio-temporal analyses were done by applying retrospective space-time and spatial variation in temporal trends analysis using SaTScan™ software, and Bayesian hierarchical modelling techniques for disease mapping using WinBUGS software. The thesis identified an overall earthquake-exposure effect on mood and anxiety symptom treatments among Christchurch residents in the context of the earthquakes as they experienced stronger increases in the risk of being treated especially shortly after the catastrophic 2011 Christchurch earthquake compared to the rest of New Zealand. High-risk groups included females, elderly, children and those with a pre-existing mental illness with elderly and children especially at-risk in the context of the earthquakes. Looking at the spatio-temporal distribution of mood and anxiety symptom treatments in the Christchurch urban area, a high rates cluster ranging from the severely affected central city to the southeast was found post-disaster. Analysing residential exposure to various earthquake impacts found that living in closer proximity to more affected areas was identified as a risk factor for mood and anxiety symptom treatments, which largely confirms a dose-response relationship between level of affectedness and mood and anxiety symptom treatments. However, little changes in the spatial distribution of mood and anxiety symptom treatments occurred in the Christchurch urban area over time indicating that these results may have been biased by pre-existing spatial disparities. Additionally, the post-disaster mobility activity from severely affected eastern to the generally less affected western and northern parts of the city seemed to have played an important role as the strongest increases in treatment rates occurred in less affected northern areas of the city, whereas the severely affected eastern areas tended to show the lowest increases. An investigation into the different effects of mobility confirmed that within-city movers and temporary relocatees were generally more likely to receive care or treatment for mood or anxiety symptoms, but moving within the city was identified as a protective factor over time. In contrast, moving out of the city from minor, moderately or severely damaged plain areas of the city, which are generally less affluent than Port Hills areas, was identified as a risk factor in the second year post-disaster. Moreover, residents from less damaged plain areas of the city showed a decrease in the likelihood of receiving care or treatment for mood or anxiety symptoms compared to those from undamaged plain areas over time, which also contradicts a possible dose-response relationship. Finally, the effects of the social and physical environment, as well as community resilience on mood and anxiety symptom treatments among long-term stayers from Christchurch communities indicate an exacerbation of pre-existing mood and anxiety symptom treatment disparities in the city, whereas exposure to ‘felt’ earthquake intensities did not show a statistically significant effect. The findings of this thesis highlight the complex relationship between different levels of exposure to a severe natural disaster and adverse mental health outcomes in a severely affected region. It is one of the few studies that have access to area-wide health and impact information, are able to do a pre-disaster / post-disaster comparison and track their sample population to apply spatial and spatio-temporal analysis techniques for exposure assessment. Thus, this thesis enhances knowledge about the spatio-temporal distribution of adverse mental health outcomes in the context of a severe natural disaster and informs public health care planners, not only about high-risk groups, but also where and when to target health interventions. The results indicate that such programs should broadly target residents living in more affected areas as they are likely to face daily hardship by living in a disrupted environment and may have already been the most vulnerable ones before the disaster. Special attention should be focussed on women, elderly, children and people with pre-existing mental illnesses as they are most likely to receive care or treatment for stress-related mental health symptoms. Moreover, permanent relocatees from affected areas and temporarily relocatees shortly after the disaster may need special attention as they face additional stressors due to the relocation that may lead to the development of adverse mental health outcomes needing treatment.

Research papers, University of Canterbury Library

Sewerage systems convey sewage, or wastewater, from residential or commercial buildings through complex reticulation networks to treatment plants. During seismic events both transient ground motion and permanent ground deformation can induce physical damage to sewerage system components, limiting or impeding the operability of the whole system. The malfunction of municipal sewerage systems can result in the pollution of nearby waterways through discharge of untreated sewage, pose a public health threat by preventing the use of appropriate sanitation facilities, and cause serious inconvenience for rescuers and residents. Christchurch, the second largest city in New Zealand, was seriously affected by the Canterbury Earthquake Sequence (CES) in 2010-2011. The CES imposed widespread damage to the Christchurch sewerage system (CSS), causing a significant loss of functionality and serviceability to the system. The Christchurch City Council (CCC) relied heavily on temporary sewerage services for several months following the CES. The temporary services were supported by use of chemical and portable toilets to supplement the damaged wastewater system. The rebuild delivery agency -Stronger Christchurch Infrastructure Rebuild Team (SCIRT) was created to be responsible for repair of 85 % of the damaged horizontal infrastructure (i.e., water, wastewater, stormwater systems, and roads) in Christchurch. Numerous initiatives to create platforms/tools aiming to, on the one hand, support the understanding, management and mitigation of seismic risk for infrastructure prior to disasters, and on the other hand, to support the decision-making for post-disaster reconstruction and recovery, have been promoted worldwide. Despite this, the CES in New Zealand highlighted that none of the existing platforms/tools are either accessible and/or readable or usable by emergency managers and decision makers for restoring the CSS. Furthermore, the majority of existing tools have a sole focus on the engineering perspective, while the holistic process of formulating recovery decisions is based on system-wide approach, where a variety of factors in addition to technical considerations are involved. Lastly, there is a paucity of studies focused on the tools and frameworks for supporting decision-making specifically on sewerage system restoration after earthquakes. This thesis develops a decision support framework for sewerage pipe and system restoration after earthquakes, building on the experience and learning of the organisations involved in recovering the CSS following the CES in 2010-2011. The proposed decision support framework includes three modules: 1) Physical Damage Module (PDM); 2) Functional Impact Module (FIM); 3) Pipeline Restoration Module (PRM). The PDM provides seismic fragility matrices and functions for sewer gravity and pressure pipelines for predicting earthquake-induced physical damage, categorised by pipe materials and liquefaction zones. The FIM demonstrates a set of performance indicators that are categorised in five domains: structural, hydraulic, environmental, social and economic domains. These performance indicators are used to assess loss of wastewater system service and the induced functional impacts in three different phases: emergency response, short-term recovery and long-term restoration. Based on the knowledge of the physical and functional status-quo of the sewerage systems post-earthquake captured through the PDM and FIM, the PRM estimates restoration time of sewer networks by use of restoration models developed using a Random Forest technique and graphically represented in terms of restoration curves. The development of a decision support framework for sewer recovery after earthquakes enables decision makers to assess physical damage, evaluate functional impacts relating to hydraulic, environmental, structural, economic and social contexts, and to predict restoration time of sewerage systems. Furthermore, the decision support framework can be potentially employed to underpin system maintenance and upgrade by guiding system rehabilitation and to monitor system behaviours during business-as-usual time. In conjunction with expert judgement and best practices, this framework can be moreover applied to assist asset managers in targeting the inclusion of system resilience as part of asset maintenance programmes.