Canterbury, New Zealand, was struck by two major earthquakes in 2010 and 2011. Using a dyadic and developmental perspective, the current thesis first aimed to determine how the experience of earthquake-related stressors (including loss of material resources, trauma exposure, and ongoing earthquake-related stressors) and stress (posttraumatic stress symptoms) impacted individuals’ intimate relationship quality (Part 1). Data were collected from a sample of 99 couples at four time points over a period of approximately 15 months, with Time 1 completed 14 months after the 2010 earthquake (eight months post the 2011 earthquake). Data were analysed using moderated growth curve modelling in an Actor-Partner Interdependence Model framework. In line with expectations, posttraumatic stress symptoms were the strongest predictors of relationship quality. More specifically, individuals’ (actor) posttraumatic stress symptoms and their partner’s posttraumatic stress symptoms had an adverse effect on their relationship quality at Time 1. Demonstrating the importance of taking a developmental perspective, the effect of partner posttraumatic stress symptoms changed over time. Although higher partner posttraumatic stress symptoms were associated with worse relationship quality in individuals (actors) at Time 1, this was no longer the case at Time 4. Differences were also found between men and women’s actor posttraumatic stress symptom slopes across time. Using the same data and analyses, Part 2 built on these findings by investigating the role of a possible posttrauma resource available within the relationship – support exchanges. Overall, results showed that individuals were protected from any adverse effects that posttraumatic stress symptoms had on relationship quality if they had more frequent support exchanges in the relationship, however, differences between men and women and slopes across time were found. Although not the case initially, individuals’ relationship quality was worse in the longer-term if their partner reported receiving lower support from them when they were experiencing high posttraumatic stress symptoms. Results also suggested that although women coped better (as evidenced through slightly better relationship quality) with higher symptoms and lower support than men initially, these efforts diminished over time. Furthermore, men appeared to be less able to cope (i.e., had worse relationship quality) with their partner’s stress when they were not receiving frequent support. Contrary to expectations, negative exchanges in the relationship did not exacerbate any adverse effects that posttraumatic stress symptoms (experienced by either individuals or their partner) had on an individuals’ relationship quality. The theoretical and practical implications and applications of these findings are discussed.
Geospatial liquefaction models aim to predict liquefaction using data that is free and readily-available. This data includes (i) common ground-motion intensity measures; and (ii) geospatial parameters (e.g., among many, distance to rivers, distance to coast, and Vs30 estimated from topography) which are used to infer characteristics of the subsurface without in-situ testing. Since their recent inception, such models have been used to predict geohazard impacts throughout New Zealand (e.g., in conjunction with regional ground-motion simulations). While past studies have demonstrated that geospatial liquefaction-models show great promise, the resolution and accuracy of the geospatial data underlying these models is notably poor. As an example, mapped rivers and coastlines often plot hundreds of meters from their actual locations. This stems from the fact that geospatial models aim to rapidly predict liquefaction anywhere in the world and thus utilize the lowest common denominator of available geospatial data, even though higher quality data is often available (e.g., in New Zealand). Accordingly, this study investigates whether the performance of geospatial models can be improved using higher-quality input data. This analysis is performed using (i) 15,101 liquefaction case studies compiled from the 2010-2016 Canterbury Earthquakes; and (ii) geospatial data readily available in New Zealand. In particular, we utilize alternative, higher-quality data to estimate: locations of rivers and streams; location of coastline; depth to ground water; Vs30; and PGV. Most notably, a region-specific Vs30 model improves performance (Figs. 3-4), while other data variants generally have little-to-no effect, even when the “standard” and “high-quality” values differ significantly (Fig. 2). This finding is consistent with the greater sensitivity of geospatial models to Vs30, relative to any other input (Fig. 5), and has implications for modeling in locales worldwide where high quality geospatial data is available.
This study sought to investigate employee burnout within a post-disaster context by exploring teachers’ burnout perceptions and workplace attitudes in the aftermath of the 2010-2011 Christchurch earthquakes. The study hypothesised that burnout dimensions (emotional exhaustion and cynicism) would be related with the extent to which individuals and schools were impacted by the earthquakes, and with the quality of school support for staff and students (i.e., personal disaster impact, school disaster impact and school responsiveness to the disaster), with perceptions of role conflict and role overload, and with turnover intentions. Additionally, a Teacher Burnout Model was proposed whereby emotional exhaustion and cynicism were hypothesised to mediate the relationships between the independent variables (i.e., the disaster-related and role-related variables) and turnover intentions. 125 primary, intermediate and secondary school teachers from the city of Christchurch completed an online survey. Results revealed that high role overload, high role conflict, high school disaster impact, and schools’ ineffective disaster coping responses, were associated with increased levels of emotional exhaustion and cynicism. Although greater impact of earthquakes on teachers’ personal lives was related to higher levels of emotional exhaustion, results revealed a non-significant relationship between personal disaster impact and cynicism. In the Teacher Burnout Model, the relationships between both role stress variables and turnover intentions were mediated by perceptions of emotional exhaustion. This study contributes novel findings to the burnout literature, and provides implications for schools and organisations operating within a disaster context.
Despite over a century of study, the relationship between lunar cycles and earthquakes remains controversial and difficult to quantitatively investigate. Perhaps as a consequence, major earthquakes around the globe are frequently followed by 'prediction' claims, using lunar cycles, that generate media furore and pressure scientists to provide resolute answers. The 2010-2011 Canterbury earthquakes in New Zealand were no exception; significant media attention was given to lunarderived earthquake predictions by non-scientists, even though the predictions were merely 'opinions' and were not based on any statistically robust temporal or causal relationships. This thesis provides a framework for studying lunisolar earthquake temporal relationships by developing replicable statistical methodology based on peer reviewed literature. Notable in the methodology is a high accuracy ephemeris, called ECLPSE, designed specifically by the author for use on earthquake catalogs, and a model for performing phase angle analysis. The statistical tests were carried out on two 'declustered' seismic catalogs, one containing the aftershocks from the Mw7.1 earthquake in Canterbury, and the other containing Australian seismicity from the past two decades. Australia is an intraplate setting far removed from active plate boundaries and Canterbury is proximal to a plate boundary, thus allowing for comparison based on tectonic regime and corresponding tectonic loading rate. No strong, conclusive, statistical correlations were found at any level of the earthquake catalogs, looking at large events, onshore events, offshore events, and the fault type of some events. This was concluded using Schuster's test of significance with α=5% and analysis of standard deviations. A few weak correlations, with p-5-10% of rejecting the null hypothesis, and anomalous standard deviations were found, but these are difficult to interpret. The results invalidate the statistical robustness of 'earthquake predictions' using lunisolar parameters in this instance. An ambitious researcher could improve on the quality of the results and on the range of parameters analyzed. The conclusions of the thesis raise more questions than answers, but the thesis provides an adaptable methodology that can be used to further investigation the problem.
School travel is a major aspect of a young person’s everyday activity. The relationship between the built environment that youth experience on their way to and from school, influences a number of factors including their development, health and wellbeing. This is especially important in low income areas where the built environment is often poorer, but the need for it to be high quality and accessible is greater. This study focusses on the community of Aranui, a relatively low income suburb in Christchurch, New Zealand. It pays particular attention to Haeata Community Campus, a state school of just under 800 pupils from year one through to year thirteen (ages 5-18). The campus opened in 2017 following the closure of four local schools (three primary and one secondary), as part of the New Zealand Government’s Education Renewal scheme following the Christchurch earthquakes of 2010/11. Dedicated effort toward understanding the local built environment, and subsequent travel patterns has been argued to be insufficiently considered. The key focus of this research was to understand the importance of the local environment in encouraging active school travel. The present study combines geospatial analysis, quantitative survey software Maptionnaire, and statistical models to explore the features of the local environment that influence school travel behaviour. Key findings suggest that distance to school and parental control are the most significant predictors of active transport in the study sample. Almost 75% of students live within two kilometres of the school, yet less than 40% utilise active transport. Parental control may be the key contributing factor to the disproportionate private vehicle use. However, active school travel is acknowledged as a complex process that is the product of many individual, household, and local environment factors. To see increased active transport uptake, the local environment needs to be of greater quality. Meaning that the built environment should be improved to be youth friendly, with greater walkability and safe, accessible cycling infrastructure.
One of the great challenges facing human systems today is how to prepare for, manage, and adapt successfully to the profound and rapid changes wreaked by disasters. Wellington, New Zealand, is a capital city at significant risk of devastating earthquake and tsunami, potentially requiring mass evacuations with little or short notice. Subsequent hardship and suffering due to widespread property damage and infrastructure failure could cause large areas of the Wellington Region to become uninhabitable for weeks to months. Previous research has shown that positive health and well-being are associated with disaster-resilient outcomes. Preventing adverse outcomes before disaster strikes, through developing strengths-based skill sets in health-protective attitudes and behaviours, is increasingly advocated in disaster research, practise, and management. This study hypothesised that well-being constructs involving an affective heuristic play vital roles in pathways to resilience as proximal determinants of health-protective behaviours. Specifically, this study examined the importance of health-related quality of life and subjective well-being in motivating evacuation preparedness, measured in a community sample (n=695) drawn from the general adult population of Wellington’s isolated eastern suburbs. Using a quantitative epidemiological approach, the study measured the prevalence of key quality of life indicators (physical and mental health, emotional well-being or “Sense of Coherence”, spiritual well-being, social well-being, and life satisfaction) using validated psychometric scales; analysed the strengths of association between these indicators and the level of evacuation preparedness at categorical and continuous levels of measurement; and tested the predictive power of the model to explain the variance in evacuation preparedness activity. This is the first study known to examine multi-dimensional positive health and global well-being as resilient processes for engaging in evacuation preparedness behaviour. A cross-sectional study design and quantitative survey were used to collect self-report data on the study variables; a postal questionnaire was fielded between November 2008 and March 2009 to a sampling frame developed through multi-stage cluster randomisation. The survey response rate was 28.5%, yielding a margin of error of +/- 3.8% with 95% confidence and 80% statistical power to detect a true correlation coefficient of 0.11 or greater. In addition to the primary study variables, data were collected on demographic and ancillary variables relating to contextual factors in the physical environment (risk perception of physical and personal vulnerability to disaster) and the social environment (through the construct of self-determination), and other measures of disaster preparedness. These data are reserved for future analyses. Results of correlational and regression analyses for the primary study variables show that Wellingtonians are highly individualistic in how their well-being influences their preparedness, and a majority are taking inadequate action to build their resilience to future disaster from earthquake- or tsunami-triggered evacuation. At a population level, the conceptual multi-dimensional model of health-related quality of life and global well-being tested in this study shows a positive association with evacuation preparedness at statistically significant levels. However, it must be emphasised that the strength of this relationship is weak, accounting for only 5-7% of the variability in evacuation preparedness. No single dimension of health-related quality of life or well-being stands out as a strong predictor of preparedness. The strongest associations for preparedness are in a positive direction for spiritual well-being, emotional well-being, and life satisfaction; all involve a sense of existential meaningfulness. Spiritual well-being is the only quality of life variable making a statistically significant unique contribution to explaining the variance observed in the regression models. Physical health status is weakly associated with preparedness in a negative direction at a continuous level of measurement. No association was found at statistically significant levels for mental health status and social well-being. These findings indicate that engaging in evacuation preparedness is a very complex, holistic, yet individualised decision-making process, and likely involves highly subjective considerations for what is personally relevant. Gender is not a factor. Those 18-24 years of age are least likely to prepare and evacuation preparedness increases with age. Multidimensional health and global well-being are important constructs to consider in disaster resilience for both pre-event and post-event timeframes. This work indicates a need for promoting self-management of risk and building resilience by incorporating a sense of personal meaning and importance into preparedness actions, and for future research into further understanding preparedness motivations.
Geological research in the immediate aftermath of the 2016 Kaikōura Earthquake, New Zealand, was necessary due to the importance and perishability of field data. It also reflects a real desire on the part of researchers to contribute not only to immediate scientific understanding but also to the societal recovery effort by enhancing knowledge of the event for the benefit of affected communities, civil defence organizations and regional and national decision makers. This commitment to outreach and engagement is consistent with the recent IAPG statement of Geoethics. More immediately, it was informed by experience of the 2010-2011 Canterbury Earthquake sequence. After that earlier disaster, intense interactions between researchers and various response agencies as well as local communities informed the development and dissemination of a set of ethical guidelines for researchers immediately following the Mw7.8 14 November 2016 Kaikōura Earthquake. In this presentation, I argue that ethical engagement of this kind is the key to gathering high quality research data immediately after the event. Creating trusting and mutually respectful, mutually beneficial relationships is also vital to ongoing engagement to facilitate further “in depth” research in collaboration with communities.
INTRODUCTION: Connections between environmental factors and mental health issues have been postulated in many different countries around the world. Previously undertaken research has shown many possible connections between these fields, especially in relation to air quality and extreme weather events. However, research on this subject is lacking in New Zealand, which is difficult to analyse as an overall nation due to its many micro-climates and regional differences.OBJECTIVES: The aim of this study and subsequent analysis is to explore the associations between environmental factors and poor mental health outcomes in New Zealand by region and predict the number of people with mental health-related illnesses corresponding to the environmental influence.METHODS: Data are collected from various public-available sources, e.g., Stats NZ and Coronial services of New Zealand, which comprised four environmental factors of our interest and two mental health indicators data ranging from 2016 up until 2020. The four environmental factors are air pollution, earthquakes, rainfall and temperature. Two mental health indicators include the number of people seen by District Health Boards (DHBs) for mental health reasons and the statistics on suicide deaths. The initial analysis is carried out on which regions were most affected by the chosen environmental factors. Further analysis using Auto-Regressive Integrated Moving Average(ARIMA) creates a model based on time series of environmental data to generate estimation for the next two years and mental health projected from the ridge regression.RESULTS: In our initial analysis, the environmental data was graphed along with mental health outcomes in regional charts to identify possible associations. Different regions of New Zealand demonstrate quite different relationships between the environmental data and mental health outcomes. The result of later analysis predicts that the suicide rate and DHB mental health visits may increase in Wellington, drop-in Hawke's Bay and slightly increase in Canterbury for the year 2021 and 2022 with different environmental factors considered.CONCLUSION: It is evident that the relationship between environmental and mental health factors is regional and not national due to the many micro-climates that exist around the nation. However, it was observed that not all factors displayed a good relationship between the regions. We conclude that our hypotheses were partially correct, in that increased air pollution was found to correlate to increased mental health-related DHB visits. Rainfall was also highly correlated to some mental health outcomes. Higher levels of rainfall reduced DHB visits and suicide rates in some areas of the country.
In 2010 and 2011 Christchurch, New Zealand experienced a series of earthquakes that caused extensive damage across the city, but primarily to the Central Business District (CBD) and eastern suburbs. A major feature of the observed damage was extensive and severe soil liquefaction and associated ground damage, affecting buildings and infrastructure. The behaviour of soil during earthquake loading is a complex phenomena that can be most comprehensively analysed through advanced numerical simulations to aid engineers in the design of important buildings and critical facilities. These numerical simulations are highly dependent on the capabilities of the constitutive soil model to replicate the salient features of sand behaviour during cyclic loading, including liquefaction and cyclic mobility, such as the Stress-Density model. For robust analyses advanced soil models require extensive testing to derive engineering parameters under varying loading conditions for calibration. Prior to this research project little testing on Christchurch sands had been completed, and none from natural samples containing important features such as fabric and structure of the sand that may be influenced by the unique stress-history of the deposit. This research programme is focussed on the characterisation of Christchurch sands, as typically found in the CBD, to facilitate advanced soil modelling in both res earch and engineering practice - to simulate earthquake loading on proposed foundation design solutions including expensive ground improvement treatments. This has involved the use of a new Gel Push (GP) sampler to obtain undisturbed samples from below the ground-water table. Due to the variable nature of fluvial deposition, samples with a wide range of soil gradations, and accordingly soil index properties, were obtained from the sampling sites. The quality of the samples is comprehensively examined using available data from the ground investigation and laboratory testing. A meta-quality assessment was considered whereby a each method of evaluation contributed to the final quality index assigned to the specimen. The sampling sites were characterised with available geotechnical field-based test data, primarily the Cone Penetrometer Test (CPT), supported by borehole sampling and shear-wave velocity testing. This characterisation provides a geo- logical context to the sampling sites and samples obtained for element testing. It also facilitated the evaluation of sample quality. The sampling sites were evaluated for liquefaction hazard using the industry standard empirical procedures, and showed good correlation to observations made following the 22 February 2011 earthquake. However, the empirical method over-predicted liquefaction occurrence during the preceding 4 September 2010 event, and under-predicted for the subsequent 13 June 2011 event. The reasons for these discrepancies are discussed. The response of the GP samples to monotonic and cyclic loading was measured in the laboratory through triaxial testing at the University of Canterbury geomechanics laboratory. The undisturbed samples were compared to reconstituted specimens formed in the lab in an attempt to quantify the effect of fabric and structure in the Christchurch sands. Further testing of moist tamped re- constituted specimens (MT) was conducted to define important state parameters and state-dependent properties including the Critical State Line (CSL), and the stress-strain curve for varying state index. To account for the wide-ranging soil gradations, selected representative specimens were used to define four distinct CSL. The input parameters for the Stress-Density Model (S-D) were derived from a suite of tests performed on each representative soil, and with reference to available GP sample data. The results of testing were scrutinised by comparing the data against expected trends. The influence of fabric and structure of the GP samples was observed to result in similar cyclic strength curves at 5 % Double Amplitude (DA) strain criteria, however on close inspection of the test data, clear differences emerged. The natural samples exhibited higher compressibility during initial loading cycles, but thereafter typically exhibited steady growth of plastic strain and excess pore water pressure towards and beyond the strain criteria and initial liquefaction, and no flow was observed. By contrast the reconstituted specimens exhibited a stiffer response during initial loading cycles, but exponential growth in strains and associated excess pore water pressure beyond phase-transformation, and particularly after initial liquefaction where large strains were mobilised in subsequent cycles. These behavioural differences were not well characterised by the cyclic strength curve at 5 % DA strain level, which showed a similar strength for both GP samples and MT specimens. A preliminary calibration of the S-D model for a range of soil gradations is derived from the suite of laboratory test data. Issues encountered include the influence of natural structure on the peak-strength–state index relationship, resulting in much higher peak strengths than typically observed for sands in the literature. For the S-D model this resulted in excessive stiffness to be modelled during cyclic mobility, when the state index becomes large momentarily, causing strain development to halt. This behaviour prevented modelling the observed re- sponse of silty sands to large strains, synonymous with “liquefaction”. Efforts to reduce this effect within the current formulation are proposed as well as future research to address this issue.
After a disaster, cities experience profound social and environmental upheaval. Current research on disasters describes this social disruption along with collective community action to provide support. Pre-existing social capital is recognised as fundamental to this observed support. This research examines the relationship between sense of place for neighbourhood, social connectedness and resilience. Canterbury residents experienced considerable and continued disruption following a large and protracted sequence of earthquakes starting in September 2010. A major aftershock on 22 February 2011 caused significant loss of life, destruction of buildings and infrastructure. Following this earthquake some suburbs of Christchurch showed strong collective action. This research examines the features of the built environment that helped to form this cooperative support. Data were collected through semi-structured interviews with 20 key informants followed by 38 participants from four case study suburbs. The objectives were to describe the community response of suburbs, to identify the key features of the built environment and the role of social infrastructure in fostering social connectedness. The last objective was to contribute to future planning for community resilience. The findings from this research indicated that social capital and community competence are significant resources to be called upon after a disaster. Features of the local environment facilitated the formation of neighbourhood connections that enabled participants to cope, manage and to collectively solve problems. These features also strengthened a sense of belonging and attachment to the home territory. Propinquity was important; the bumping and gathering places such as schools, small local shops and parks provided the common ground for meaningful pre-existing local interaction. Well-defined geography, intimate street typology, access to quality natural space and social infrastructure helped to build the local social connections and develop a sense of place. Resourceful individuals and groups were also a factor, and many are drawn to live near the inner city or more natural places. The features are the same well understood attributes that contribute to health and wellbeing. The policy and planning framework needs to consider broader social outcomes, including resilience in new and existing urban developments. The socio-political structures that provide access to secure and stable housing and local education should also be recognised and incorporated into local planning for resilience and the everyday.
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.
