In this study, we extend the spatial weight matrix defined by Getis and Aldstadt (2004) to a more general case. The modified spatial weight matrix performs better than the original spatial weight matrix since the modified spatial weight matrix adjusts weights of observations based on the distance from other observations. Both the simulation study and the application to the ecological process of invasion of non-native invasive plants (NNIPs) provide evidences for the better performance of the modified spatial weight matrix. We also develop procedures that can be used to quantify the invasion stages of NNIPs. The resultant map of invasion stage on county-level provides a useful and meaningful tool for policy makers; especially, it can be used to optimize allocation of management resources. The result of simultaneous autoregressive model shows that not only the biotic and abiotic factors but also human activities play an important role in the establishment and spread of multiflora rose in the Upper Midwest. It also shows the tendency of the establishment and spread of multiflora rose (Rosa Multiflora, Thunb. ex Murr.) in the Upper Midwest.

Abstract: Road traffic accidents claim more than 1,500 lives each year in Canada and affect society adversely, so transport authorities must reduce their impact. This is a major concern in Quebec, where the traffic-accident risks increase year by year proportionally to provincial population growth. In reality, the occurrence of traffic crashes is rarely random in space-time; they tend to cluster in specific areas such as intersections, ramps, and work zones. Moreover, weather stands out as an environmental risk factor that affects the crash rate. Therefore, traffic-safety engineers need to accurately identify the location and time of traffic accidents. The occurrence of such accidents actually is determined by some important factors, including traffic volume, weather conditions, and geometric design. This study aimed at identifying hotspot locations based on a historical crash data set and spatiotemporal patterns of traffic accidents with a view to improving road safety. This thesis proposes two new methods for identifying hotspot locations on a road network. The first method could be used to identify and rank hotspot locations in cases in which the value of traffic volume is available, while the second method is useful in cases in which the value of traffic volume is not. These methods were examined with three years of traffic-accident data (2011–2013) in Sherbrooke. The first method proposes a two-step integrated approach for identifying traffic-accident hotspots on a road network. The first step included a spatial-analysis method called network kernel-density estimation. The second step involved a network-screening method using the critical crash rate, which is described in the Highway Safety Manual. Once the traffic-accident density had been estimated using the network kernel-density estimation method, the selected potential hotspot locations were then tested with the critical-crash-rate method. The second method offers an integrated approach to analyzing spatial and temporal (spatiotemporal) patterns of traffic accidents and organizes them according to their level of significance. The spatiotemporal seasonal patterns of traffic accidents were analyzed using the kernel-density estimation; it was then applied as the attribute for a significance test using the local Moran’s I index value. The results of the first method demonstrated that over 90% of hotspot locations in Sherbrooke were located at intersections and in a downtown area with significant conflicts between road users. It also showed that signalized intersections were more dangerous than unsignalized ones; over half (58%) of the hotspot locations were located at four-leg signalized intersections. The results of the second method show that crash patterns varied according to season and during certain time periods. Total seasonal patterns revealed denser trends and patterns during the summer, fall, and winter, then a steady trend and pattern during the spring. Our findings also illustrated that crash patterns that applied accident severity were denser than the results that only involved the observed crash counts. The results clearly show that the proposed methods could assist transport authorities in quickly identifying the most hazardous sites in a road network, prioritizing hotspot locations in a decreasing order more efficiently, and assessing the relationship between traffic accidents and seasons. / Les accidents de la route sont responsables de plus de 1500 décès par année au Canada et ont des effets néfastes sur la société. Aux yeux des autorités en transport, il devient impératif d’en réduire les impacts. Il s’agit d’une préoccupation majeure au Québec depuis que les risques d’accidents augmentent chaque année au rythme de la population. En réalité, les accidents routiers se produisent rarement de façon aléatoire dans l’espace-temps. Ils surviennent généralement à des endroits spécifiques notamment aux intersections, dans les bretelles d’accès, sur les chantiers routiers, etc. De plus, les conditions climatiques associées aux saisons constituent l’un des facteurs environnementaux à risque affectant les taux d’accidents. Par conséquent, il devient impératif pour les ingénieurs en sécurité routière de localiser ces accidents de façon plus précise dans le temps (moment) et dans l’espace (endroit). Cependant, les accidents routiers sont influencés par d’importants facteurs comme le volume de circulation, les conditions climatiques, la géométrie de la route, etc. Le but de cette étude consiste donc à identifier les points chauds au moyen d’un historique des données d’accidents et de leurs répartitions spatiotemporelles en vue d’améliorer la sécurité routière. Cette thèse propose deux nouvelles méthodes permettant d’identifier les points chauds à l’intérieur d’un réseau routier. La première méthode peut être utilisée afin d’identifier et de prioriser les points chauds dans les cas où les données sur le volume de circulation sont disponibles alors que la deuxième méthode est utile dans les cas où ces informations sont absentes. Ces méthodes ont été conçues en utilisant des données d’accidents sur trois ans (2011-2013) survenus à Sherbrooke. La première méthode propose une approche intégrée en deux étapes afin d’identifier les points chauds au sein du réseau routier. La première étape s’appuie sur une méthode d’analyse spatiale connue sous le nom d’estimation par noyau. La deuxième étape repose sur une méthode de balayage du réseau routier en utilisant les taux critiques d’accidents, une démarche éprouvée et décrite dans le manuel de sécurité routière. Lorsque la densité des accidents routiers a été calculée au moyen de l’estimation par noyau, les points chauds potentiels sont ensuite testés à l’aide des taux critiques. La seconde méthode propose une approche intégrée destinée à analyser les distributions spatiales et temporelles des accidents et à les classer selon leur niveau de signification. La répartition des accidents selon les saisons a été analysée à l’aide de l’estimation par noyau, puis ces valeurs ont été assignées comme attributs dans le test de signification de Moran. Les résultats de la première méthode démontrent que plus de 90 % des points chauds à Sherbrooke sont concentrés aux intersections et au centre-ville où les conflits entre les usagers de la route sont élevés. Ils révèlent aussi que les intersections contrôlées sont plus à risque par comparaison aux intersections non contrôlées et que plus de la moitié des points chauds (58 %) sont situés aux intersections à quatre branches (en croix). Les résultats de la deuxième méthode montrent que les distributions d’accidents varient selon les saisons et à certains moments de l’année. Les répartitions saisonnières montrent des tendances à la densification durant l’été, l’automne et l’hiver alors que les distributions sont plus dispersées au cours du printemps. Nos observations indiquent aussi que les répartitions ayant considéré la sévérité des accidents sont plus denses que les résultats ayant recours au simple cumul des accidents. Les résultats démontrent clairement que les méthodes proposées peuvent: premièrement, aider les autorités en transport en identifiant rapidement les sites les plus à risque à l’intérieur du réseau routier; deuxièmement, prioriser les points chauds en ordre décroissant plus efficacement et de manière significative; troisièmement, estimer l’interrelation entre les accidents routiers et les saisons.

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.