Individual responses to natural disasters are highly variable. The psychological and behavioural response trajectories of those who manage to cope well with adverse life events are in need of further investigation. Increased alcohol use is often observed in communities exposed to mass traumas, particularly among those exposed to severe levels of trauma, with males drinking more than females. The current study examined patterns of alcohol use and motivations for drinking among a sample of psychologically resilient individuals with varying levels of exposure to the Canterbury earthquakes (N = 91) using structured and semi-structured interviews and self-report measures. As hypothesised, there was a significant increase in alcohol consumption since the earthquakes began, and males reported significantly higher levels of pre-earthquake and current alcohol consumption than females. Contrary to expectations, there was no association between traumatic exposure severity and alcohol consumption. While participants reported anxiety-based coping motives for drinking at levels comparable to those reported by other studies, depression-based coping motives were significantly lower, providing partial support for the hypothesis that participants would report coping motives for drinking at levels comparable to those found by other researchers. No gender differences in drinking motives were found. As expected, current alcohol consumption was positively correlated with anxiety and depression-based coping motives for drinking. Psychological resilience was not significantly associated with alcohol use, however resilience was negatively associated with depression-based coping motives for drinking. These findings have inter-generational and international implications for post-traumatic intervention.
Access to clean and safe drinking water is a fundamental human requirement. However, in many areas of the world natural water sources have been impacted by a variety of biological and chemical contaminants. The ingestion of these contaminants may cause acute or chronic health problems. To prevent such illnesses, many technologies have been developed to treat, disinfect and supply safe drinking water quality. However, despite these advancements, water supply distribution systems can adversely affect the drinking water quality before it is delivered to consumers. The primary aim of this research was to investigate the effect that water distribution systems may have on household drinking water quality in Christchurch, New Zealand and Addis Ababa, Ethiopia. Water samples were collected from the source water and household taps in both cities. The samples were then tested for various physical, chemical and biological water quality parameters. The data collected was also used to determine if water samples complied with national drinking water quality standards in both countries. Independent samples t-test statistical analyses were also performed to determine if water quality measured in the samples collected from the source and household taps was significantly different. Water quality did not vary considerably between the source and tap water samples collected in Christchurch City. No bacteria were detected in any sample. However, the pH and total iron concentrations measured in source and tap water samples were found to be significantly different. The lower pH values measured in tap water samples suggests that corrosion may be taking place in the distribution system. No water samples transgressed the Drinking Water Standards for New Zealand (DWSNZ) MAVs. Monitoring data collected by the Christchurch City Council (CCC) was also used for comparison. A number of pH, turbidity and total iron concentration measurements collected by the CCC in 2011 were found to exceed the guideline values. This is likely due to structural damage to the source wells and pump-stations that occurred during the 2011 earthquake events. Overall, it was concluded that the distribution system does not adversely affect the quality of Christchurch City’s household drinking water. The water quality measured in samples collected from the source (LTP) and household taps in Addis Ababa was found to vary considerably. The water collected from the source complied with the Ethiopian (WHO) drinking water quality standards. However, tap water samples were often found to have degraded water quality for the physical and chemical parameters tested. This was especially the case after supply interruption and reinstatement events. Bacteria were also often detected in household tap water samples. The results from this study indicate that water supply disruptions may result in degraded water quality. This may be due to a drop in pipeline pressure and the intrusion of contaminants through the leaky and cross-connected pipes in the distribution network. This adversely affects the drinking water quality in Addis Ababa.
The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours). The potential for a gastroenteritis outbreak in a post-earthquake environment may increase because of compromised infrastructure services, contaminated liquefaction (lateral spreading and surface ejecta), and the presence of gastroenteritis agents in the drinking water network. A population in a post-earthquake environment might be seriously affected by gastroenteritis because it has a short incubation period (about 10 hours). The aim of this multidisciplinary research was to retrospectively analyse the gastroenteritis prevalence following the February 22, 2011 earthquake in Christchurch. The first focus was to assess whether earthquake-induced infrastructure damage, liquefaction, and gastroenteritis agents spatially explained the recorded gastroenteritis cases over the period of 35 days following the February 22, 2011 earthquake in Christchurch. The gastroenteritis agents considered in this study were Escherichia coli found in the drinking water supply (MPN/100mL) and Non-Compliant Free Associated Chlorine (FAC-NC) (less than <0.02mg/L). The second focus was the protocols that averted a gastroenteritis outbreak at three Emergency Centres (ECs): Burnside High School Emergency Centre (BEC); Cowles Stadium Emergency Centre (CEC); and Linwood High School Emergency Centre (LEC). Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach. Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC. Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols and indirect themes included type of EC building (school or a sports stadium), and EC staff. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss. This research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally Using a mixed-method approach, gastroenteritis point prevalence and the considered factors were quantitatively analysed. A damage profile was created by amalgamating different types of damage for the considered factors for each Census Area Unit (CAU) in Christchurch. The damage profile enabled the application of a variety of statistical methods which included Moran’s I , Hot Spot (HS) analysis, Spearman’s Rho, and Besag–York–Mollié Model using a range of software. The qualitative analysis involved interviewing 30 EC staff members. The data was evaluated by adopting the Grounded Theory (GT) approach. Spatial analysis of considered factors showed that highly damaged CAUs were statistically clustered as demonstrated by Moran’s I statistic and hot spot analysis. Further modelling showed that gastroenteritis point prevalence clustering could not be fully explained by infrastructure damage alone, and other factors influenced the recorded gastroenteritis point prevalence. However, the results of this research suggest that there was a tenuous, indirect relationship between recorded gastroenteritis point prevalence and the considered factors: earthquake-induced infrastructure damage, liquefaction and FAC-NC. Two ECs were opened as part of the post-earthquake response in areas with severe infrastructure damage and liquefaction (BEC and CEC). The third EC (CEC) provided important lessons that were learnt from the previous September 4, 2010 earthquake, and implemented after the February 22, 2011 earthquake. The ECs were selected to represent the Christchurch area, and were situated where potential for gastroenteritis was high. BEC represented the western side of Christchurch; whilst, CEC and LEC represented the eastern side, where the potential for gastroenteritis was high according to the outputs of the quantitative spatial modelling. Qualitative analysis from the interviews at the ECs revealed that evacuees were arriving at the ECs with gastroenteritis-like symptoms. Participants believed that those symptoms did not originate at the ECs. Two types of interwoven themes identified: direct and indirect. The direct themes were preventive protocols that included prolific use of hand sanitisers; surveillance; and the services offered. Indirect themes included the EC layout, type of EC building (school or a sports stadium), and EC staff. Indirect themes governed the quality and sustainability of the direct themes implemented, which in turn averted gastroenteritis outbreaks at the ECs. The main limitations of the research were Modifiable Areal Units (MAUP), data detection, and memory loss. It was concluded that gastroenteritis point prevalence following the February 22, 2011 earthquake could not be solely explained by earthquake-induced infrastructure damage, liquefaction, and gastroenteritis causative agents alone. However, this research provides a practical method that can be adapted to assess gastroenteritis risk in a post-earthquake environment. Creating a damage profile for each CAU and using spatial data analysis can isolate vulnerable areas, and qualitative data analysis provides localised information. Thus, this mixed method approach can be used in other disaster contexts to study gastroenteritis prevalence, and can serve as an appendage to the existing framework for assessing infectious diseases. Furthermore, the lessons learnt from qualitative analysis can inform the current infectious disease management plans, designed for a post-disaster response in New Zealand and internationally.
On 14 November 2016, the Mw 7.8 Kaikōura earthquake caused widespread damage along the east coast of the South Island, New Zealand. Kaikōura town itself was isolated from the rest of the country by landslides blocking off major roads. While impacts from the Kaikōura earthquake on large, urban population centres have been generally well documented, this thesis aims to fill gaps in academic knowledge regarding small rural towns. This thesis investigates what, where and when critical infrastructure and lifeline service disruption occurred following the 2016 Kaikōura earthquake in a selection of small towns, and how the communities in these areas adapted to disruption. Following a robust review of literature and news media, four small rural towns were selected from North Canterbury (Culverden & Waiau) and Marlborough (Seddon & Ward) in the South Island, New Zealand. Semi-structured interview sessions with a special focus on these towns were held with infrastructure managers, emergency response and recovery officials, and organisation leaders with experience or expertise in the 2016 Kaikōura earthquake. Findings were supplemented with emergency management situation reports to produce hazard maps and infrastructure exposure maps. A more detailed analysis was conducted for Waiau involving interdependence analyses and a level of service timeline for select lifeline services. The earthquake impacted roads by blocking them with landslides, debris and surface rupture. Bridges where shaken off their abutments, breaking infrastructure links such as fibre landlines as they went. Water supplies and other forms of infrastructure relied heavily on the level of service of roads, as rough rural terrain left few alternatives. Adapting to an artificial loss of road service, some Waiau locals created their own detour around a road cordon in order to get home to family and farms. Performance of dwellings was tied to socioeconomic factors as much as proximity to the epicentre. Farmers who lost water access pulled out fences to allow stock to drink from rivers. Socioeconomic differences between farmland and township residents also contributed to resilience variations between the towns assessed in this study. Understanding how small rural towns respond and adapt to disaster allows emergency management officials and policy to be well informed and flexible with planning for multiple size classes of towns.
