Tesis sobre el tema "Spatial disease"

The understanding of human mobility and the development of qualitative models as well as quantitative theories for it is of key importance to the research of human infectious disease dynamics on large geographical scales. In our globalized world, mobility and traffic have reached a complexity and volume of unprecedented degree. Long range human mobility is now responsible for the rapid geographical spread of emergent infectious diseases. Multiscale human mobility networks exhibit two prominent features: (1) Networks exhibit a strong heterogeneity, the distribution of weights, traffic fluxes and populations sizes of communities range over many orders of magnitude. (2) Although the interaction magnitude in terms of traffic intensities decreases with distance, the observed power-laws indicate that long range interactions play a significant role in spatial disease dynamics. We will review how the topological features of traffic networks can be incorporated in models for disease dynamics and show, that the way topology is translated into dynamics can have a profound impact on the overall disease dynamics. We will also introduce a class of spatially extended models in which the impact and interplay of both spatial heterogeneity as well as long range spatial interactions can be investigated in a systematic fashion. Our analysis of multiscale human mobility networks is based on a proxy network of dispersing US dollar bills, which we incorporated in a model to produce real-time epidemic forecasts that projected the spatial spread of the recent outbreak of Influenza A(H1N1).

The understanding of human mobility and the development of qualitative models as well as quantitative theories for it is of key importance to the research of human infectious disease dynamics on large geographical scales. In our globalized world, mobility and traffic have reached a complexity and volume of unprecedented degree. Long range human mobility is now responsible for the rapid geographical spread of emergent infectious diseases. Multiscale human mobility networks exhibit two prominent features: (1) Networks exhibit a strong heterogeneity, the distribution of weights, traffic fluxes and populations sizes of communities range over many orders of magnitude. (2) Although the interaction magnitude in terms of traffic intensities decreases with distance, the observed power-laws indicate that long range interactions play a significant role in spatial disease dynamics. We will review how the topological features of traffic networks can be incorporated in models for disease dynamics and show, that the way topology is translated into dynamics can have a profound impact on the overall disease dynamics. We will also introduce a class of spatially extended models in which the impact and interplay of both spatial heterogeneity as well as long range spatial interactions can be investigated in a systematic fashion. Our analysis of multiscale human mobility networks is based on a proxy network of dispersing US dollar bills, which we incorporated in a model to produce real-time epidemic forecasts that projected the spatial spread of the recent outbreak of Influenza A(H1N1).

This thesis is concerned with providing further statistical development in the area of space-time modelling with particular application to disease data. We briefly consider the non-Bayesian approaches of empirical mode decomposition and generalised linear modelling for analysing space-time data, but our main focus is on the increasingly popular Bayesian hierarchical approach and topics surrounding that. We begin by introducing the hierarchical Poisson regression model of Mugglin et al. [36] and a data set provided by NHS Direct which will be used to illustrate our results through-out the remainder of the thesis. We provide details of how a Bayesian analysis can be performed using Markov chain Monte Carlo (MCMC) via the software LinBUGS then go on to consider two particular issues associated with such analyses. Firstly, a problem with the efficiency of MCMC for the Poisson regression model is likely to be due to the presence of non-standard conditional distributions. We develop and test the 'improved auxiliary mixture sampling' method which introduces auxiliary variables to the conditional distribution in such a way that it becomes multivariate Normal and an efficient block Gibbs sampling scheme can be used to simulate from it. Secondly, since MCMC allows modelling of such complexity, inputs such as priors can only be elicited in a casual way thereby increasing the need to check how sensitive our output is to changes to the prior. We therefore develop and test the 'marginal sensitivity' method which, using only one MCMC output sample, quantifies how sensitive the marginal posterior distributions are to changes to prior parameters

The objective of this thesis is to analyze how existing data can address Chagas disease transmission risk in South America given data availability. A literature review was conducted to determine prominent variables that models use to assist with Chagas disease mitigation efforts, followed by a Web search to collect publicly available spatial data pertaining to these variables. The data were then used to create maps of data availability and in an agent-based model to identify which variables are most associated with disease transmission risk. Data availability varied widely across South America, and model results indicate that datasets related to household size and spatial housing arrangement are most important to Chagas disease infection in urban areas. Governments can use this information to better direct their resources to collect data and control the spread of triatomine vectors and Chagas disease more effectively, and potentially identify more cost-effective strategies for vector elimination.

El programa d'eradicació de la malaltia d'Aujeszky va començar a Espanya l'any 1995, però no va ser fins el 2003, quan a causa de les garanties suplementàries establertes en els intercanvis intracomunitaris de l'espècie porcina amb relació a la malaltia d'Aujeszky, que aquest programa es va reforçar i es varen establir les bases del programa coordinat de lluita, control i eradicació de la malaltia. L'objectiu d'aquest estudi és realitzar una anàlisi espacial de l'eradicació de la malaltia d'Aujeszky a Catalunya (Espanya) des del 2003 fins el 2007. L'estudi s'ha dividit en quatre períodes, en base a les diferents etapes establertes al programa d'eradicació a Catalunya.
A la primera part de l'estudi, varem analitzar si la distribució espacial de la malaltia d'Aujeszky a Catalunya ha estat homogènia o hi han hagut zones d'alt risc (conglomerats) durant les diferents etapes del programa d'eradicació. Per fer-ho, en cada període varem realitzar diferents anàlisis espacials amb el programa SaTScan v6.1 basats en el model de Bernoulli. En els quatre períodes d'estudi, varem identificar conglomerats de granges positives de truges (cicle obert i cicle tancat) i/o de granges positives d'engreixos, tant a l'oest com al centre com a l'est de Catalunya. Com que el risc d'infecció va disminuir més ràpidament fora dels conglomerats que dintre, els valors del ràtio de prevalença d'aquests conglomerats augmenten al llarg del temps. Per analitzar l'evolució de la malaltia, varem estudiar si hi havia àrees en les que la proporció de granges que s'havien reinfectat o que havien eliminat la infecció era més gran. Aquestes anàlisis van demostrar que hi havia zones en les que la proporció de granges que havien eliminat la infecció era més alta, i per tant que l'eradicació de la malaltia té també un component espacial.
En els quatre períodes d'estudi, també es van detectar àrees en les que la proporció de granges reinfectades havia estat més alta. El risc relatiu d'aquests conglomerats era més gran que el dels conglomerats descrits abans. D'altra banda, existeix una associació geogràfica entre els conglomerats de granges de mares positives, granges d'engreix positives i granges de mares reinfectades. Aquesta associació podria ser deguda a la transmissió a nivell local del virus d'Aujeszky. Ja que la densitat de granges a una zona podria ser un factor relacionat amb aquesta transmissió local, varem analitzar aquesta variable en conglomerats d'eradicació i de reinfeccions. La densitat mitjana de granges de porc als conglomerats d'eradicació és de 0.4 granges per quilòmetre quadrat (mitjana de 0.28 i desviació estàndard de 0.33) i de 1.51 (mitjana de 0.7 i desviació estàndard de 1.61) als conglomerats on més granges de truges s'han reinfectat (valor de p<0.05).
En base a aquests resultats, a la segona part de l'estudi varem analitzar el paper que podien exercir factors geogràfics en la transmissió a nivell local del virus i en la persistència de la malaltia d'Aujeszky a determinades zones. Per fer-ho, varem usar un model jeràrquic bayesià, en el que varem incloure diferents variables geogràfiques que podien estar implicades en la transmissió a nivell local del virus; com són la distància a l'escorxador més proper, distància a la carretera més pròxima, nombre d'animals d'engreix positius pròxims a la granja (radi de 750 metres) i nombre de truges positives pròximes a la granja (radi de 750 metres). Al model també varem incloure una altra variable no geogràfica: tipus de granja (cicle obert o cicle tancat). L'ús d'aquests models jeràrquics bayesians permet d'incorporar un terme que té en compte la dependència espacial (autocorrelació) existent a les dades. La dependència espacial va ser inclosa al model mitjançant una distribució normal condicionalment autoregressiva (CAR) basada en un nombre de veïns. Aquests veïns van ser definits com aquelles granges localitzades en un radi de 500 metres de cada granja de truges.
De les quatre variables geogràfiques incloses al model, només la presència d'animals d'engreix positius presents a la proximitat d'una granja de truges incrementava la probabilitat d'infecció pel virus d'Aujeszky. Al primer període, per cada 1000 porcs d'engreix al voltant de cada granja de mares, l'odds (raó de probabilitats) de cada granja d'ésser positiva s'incrementava per un factor entre 1.005 i 1.36. En el període 2.2, tenir porcs d'engreix al voltant augmentava la raó de probabilitats d'infecció per un valor d'entre 1.84 i 3.22. En el període 2.1 i en el període 3, cap de les variables va influir de forma significativa en la probabilitat de ser una granja positiva. El tipus de granja (cicle obert o cicle tancat) tampoc es va relacionar amb la probabilitat de ser una granja positiva en cap dels períodes de l'estudi. El patró geogràfic dels residus (observats versus predits) del model binomial jeràrquic bayesià va ser molt similar al dels observats, en tots els períodes de l'estudi. Aquest resultat evidencia que la transmissió a nivell local del virus d'Aujeszky probablement no hagi estat el principal factor relacionat amb la persistència del virus en granges de truges. Altres factors, específics de cada granja, probablement han tingut una relació més alta en la probabilitat d'infecció que les variables geogràfiques incloses en aquesta anàlisi.
El programa de erradicación de la enfermedad de Aujeszky comenzó en España en 1995, pero no fue hasta el 2003, cuando debido a las garantías suplementarias establecidas en los intercambios intracomunitarios de la especie porcina en relación a la enfermedad de Aujeszky, que dicho programa se reforzó y se establecieron las bases del programa coordinado de lucha, control y erradicación de la enfermedad. El objetivo de este estudio es realizar un análisis espacial de la erradicación de la enfermedad de Aujeszky en Cataluña (España) desde el 2003 hasta el 2007. El estudio se ha dividido en cuatro periodos, en base a las diferentes etapas establecidas en el programa de erradicación en Cataluña.
En la primera parte del estudio, analizamos si la distribución espacial de la enfermedad de Aujeszky en Cataluña ha sido homogénea o han existido zonas de alto riesgo (conglomerados) durante las distintas etapas del programa de erradicación. Para ello, en cada periodo realizamos diferentes análisis espaciales con el programa SaTScan® v6.1 basados en el modelo de Bernoulli. En los cuatro periodos de estudio, identificamos conglomerados de granjas positivas de cerdas (ciclo abierto y ciclo cerrado) y/o de granjas positivas de engordes, tanto en la parte oeste como en el centro y este de Cataluña. Debido a que el riesgo de infección disminuyó más rápido fuera de los conglomerados que dentro, los valores del ratio de prevalencia de estos conglomerados aumentaron a lo largo del tiempo. Para analizar la evolución de la enfermedad, estudiamos si había áreas en las que la proporción de granjas que se habían reinfectado
o que habían eliminado la infección era mayor. Estos análisis demostraron que había zonas en las que la proporción de granjas que habían eliminado la infección era más alta, y por lo tanto que la erradicación de la enfermedad tiene también un componente espacial.
En los cuatro periodos de estudio, también se detectaron áreas en las que la proporción de granjas reinfectadas fue más alta. El riesgo relativo de estos conglomerados era mayor que el de los otros análisis de conglomerados. Por otro lado, existía una asociación geográfica entre los conglomerados de granjas de madres positivas, granjas de engorde positivas y granjas de madres reinfectadas. Esta asociación podría ser debida a la transmisión a nivel local del virus de Aujeszky. Ya que la densidad de granjas en una zona podría ser un factor relacionado con esta transmisión local, analizamos esta variable en conglomerados de erradicación y de reinfecciones. La densidad media de granjas de porcino en los conglomerados de erradicación fue de 0.4 granjas por kilómetro cuadrado (mediana de 0.28 y desviación estándar de 0.33) y de 1.51 (mediana de 0.7 y desviación estándar de 1.61) en los conglomerados donde más granjas de cerdas se habían reinfectado (valor de p<0.05).
En base a estos resultados, en la segunda parte del estudio analizamos el papel que podían desempeñar factores geográficos en la transmisión a nivel local del virus y en la persistencia de la enfermedad de Aujeszky en determinadas zonas. Para ello, usamos un modelo jerárquico bayesiano y en él incluimos diferentes variables geográficas que podían estar implicadas en la transmisión a nivel local del virus; como son la distancia al matadero más cercano, distancia a la carretera más próxima, número de animals de engorde positivos próximos a la granja (radio de 750 metros) y número de cerdas positivas próximas a la granja (radio de 750 metros). En el modelo también incluimos otra variable no geográfica: tipo de granja (ciclo abierto o ciclo cerrado). El uso de estos modelos jerárquicos bayesianos permite incorporar un término que tiene en cuenta la dependencia espacial (autocorrelación) existente en los datos. La dependencia espacial fue incluida en el modelo mediante una distribución normal condicionalmente autoregresiva (CAR) basada en un número de vecinos. Dichos vecinos fueron definidos como aquellas granjas localizadas en un radio de 500 metros de cada granja de cerdas.
De las cuatro variables geográficas incluidas en el modelo, sólo la presencia de animales de engorde positivos presentes en la proximidad de una granja de cerdas incrementaba la probabilidad de infección por el virus de Aujeszky. En el primer periodo, por cada 1000 cerdos de engorde en la vecindad de cada granja de madres, el odds (razón de probabilidades) de ser positiva de cada granja se incrementaba por un factor entre 1.005 y 1.36. En el periodo 2.2, tener cerdos de engorde en la vecindad aumentaba la razón de probabilidades de infección por un valor entre 1.84 y 3.22. En el periodo 2.1 y en el periodo 3, ninguna de las variables influyó de forma significativa en la probabilidad de ser una granja positiva. El tipo de granja (ciclo abierto o ciclo cerrado) tampoco se relacionó con la probabilidad de ser una granja positiva en ninguno de los periodos del estudio. El patrón geográfico de los residuos (observados versus predichos) del modelo binomial jerárquico bayesiano fue muy similar al de los observados, en todos los periodos del estudio. Este resultado evidencia que la transmisión a nivel local del virus de Aujeszky probablemente no haya sido el principal factor relacionado con la persistencia del virus en granjas de cerdas. Otros factores, específicos de cada granja, probablemente tengan una relación más alta en la probabilidad de infección que las variables geográficas incluidas en este análisis.
Aujeszky's disease (AD) eradication programme started in Spain in 1995, but it was not until 2003, due to the additional guarantees in intra-community trade relating to Aujeszky's, that AD eradication programme was adapted and ensured. The aim of this study is to conduct a spatial analysis of the Aujeszky's disease (AD) eradication programme in Catalonia, Spain, from 2003 to 2007. The study has been divided in four periods, based on the phases designed in the AD eradication programme in Catalonia.
In the first part of the study, we explore for high risk areas (clusters) in order to test whether the spatial distribution of AD in the region during the consecutive eradication periods was homogeneously distributed over the territory or clustered in space. Different purely spatial analyses, based on the Bernoulli model, were run with SaTScan® v6.1 in each period. Clusters of positive sow farms (farrow to weaning and farrow to finish) and/or fattening farms were identified in the four study periods in the western, central and north eastern part of the region. The prevalence ratio values of these clusters increased throughout the study period due to the fact that the risk of disease decreased faster outside the clusters than inside the clusters. In order to study the evolution of the disease, we explored for areas where more negative sow farms became infected and areas where more sow farms eliminated the infection. These analyses demonstrated areas with significantly higher proportions of sow farms that became negative, which indicates that the eradication of the disease has a spatial component. Clusters of negative sow farms that were infected again (reinfections) were also detected in the four study periods. The relative risk values of these clusters were much higher compared to the other cluster analyses. There was a geographical association between the clusters of positive sow farms, positive fattening farms and re-infected sow farms. This association could be attributable to the local spread of Aujeszky´s disease virus. Pig farm density could be a factor influencing the local spread of infection and was therefore evaluated for clusters of re-infected sow farms and clusters of sow farms that eliminated the infection. The mean density of pig farms was 0.40 farms per square Km (median of 0.28 and standard deviation of 0.33) in clusters of sow farms that became negative and 1.51 (median of 0.70 and standard deviation of 1.61) in clusters where more sow farms became positive (p-value<0.05).
Based on these results, in the second part of the study, we tested the role of geographical factors that could be implicated in local spread and persistence of AD in certain areas. Several geographic variables describing the possible risk factors associated to neighbourhood transmission: Distance to the nearest slaughterhouse, distance to conventional roads, mean number of AD serological positive sows and serological positive fattening pigs in the neighbourhood (750 meters radius) of each sow farm were included in a hierarchical Bayesian binomial model. A non geographic variable; type of farm (farrow to weaning versus farrow to finish) was also included. The use of Bayesian models allowed us to take into account the spatial dependence (autocorrelation) among the data; included in the model as a random effect. Spatial dependence was parameterised with a conditional autoregressive distribution (CAR) based on a set of neighbours. The set of neighbours was defined as those farms located in a 500 meters buffer radius around each sow farm.
From the four geographical variables included in the model, only positive fattening animals in the neighbourhood of sow farms increased the probability of being AD positive. In the first period, 1,000 positive fattening pigs in the neighbourhood (750 meters buffer radius) increase the odds of each sow farm being AD positive by a factor between 1.005 and 1.36. In period 2.2, having positive fattening animals in the neighbourhood increased the likelihood of each sow farm to be AD positive between
1.84 and 3.22. In period 2.1 and period 3, none of the variables had a positive relation with the probability of being positive. The type of farm (farrow to weaning or farrow to finish) also did not influence the probability of being AD positive in any period. The geographical pattern of the residuals of the hierarchical bayesian binomial model (observed versus predicted) was very similar to the observed infection in sow farms in all the eradication periods, showing that neighbourhood transmission might not be the main factor related to the eradication of Aujeszky-s disease in sow farms. Other herd¬specific risk factors might be much more related to the probability of AD infection than the geographical variables included in this study.

During 2007 the UK experienced outbreaks of three notifiable exotic livestock diseases; Foot and Mouth Disease (FMD), Highly Pathogenic Avian Influenza (HPAI) and bluetongue. Large epidemics of any of these diseases would have a serious impact on animal welfare, farming, food production and the economy. In light of this, understanding holdings which are most likely to acquire and spread infection and being able to identify areas at higher risk of an epidemic is valuable when preparing for and managing an epidemic. This thesis uses a spatial epidemiological framework and the detailed disease and demographic data from the 2001 Great Britain (GB) FMD epidemic to develop static models of the risk of FMD susceptibility and transmission. These models are used to develop maps of FMD risk. These methods are then applied to the outbreak of FMD in 2007. The inputs for this analysis comprised a set of data relating to the farms diagnosed with FMD and farms culled as part of the disease control measures. The cleaning of these data is described and data which were estimated relating to dates of infection and putative sources of infection are evaluated. The distribution of farm holdings and animals is taken from the June 2000 GB agricultural census, off-fields of farms in the agricultural census are recorded in other datasets and these have been identified and linked to census holdings. A model of holding level susceptibility is developed using both farm level variables and measures of animal numbers in the locality of the holding as well as the distance to the nearest farm infected before the ban on animal movements (seeds). The overall fit of the model was very good with an area under the Receiver Operator Characteristic (ROC) curve of 0.91. A further model was developed to describe the risk of FMD transmission. However, due to incompleteness of transmission data, this was a model of the risk of finding a subsequent Infected Premises (IP) within 3km of an IP. Risk factors were a combination of holding level variables and locality measures as well as data relevant to the infection, such as infectious period and the species initially infected. The area under the ROC curve for this model was 0.71, which is regarded as an acceptable fit. Geographical barriers to FMD transmission were investigated using a case-control methodology, linear barriers comprising rivers and railways had a significant protective effect with respect to disease transmission (odds ratio = 0.54, 95% CIs = 0.30,0.96, p=0.038). Modelled values for the transmission and susceptibility models were transformed to a raster surface in ESRI ArcMap for both the disease as it was seeded in the 2001 epidemic and a non-specific background risk surface independent of the distribution of seeds. A risk map generated for the outbreak of FMD in Surrey in August 2007 suggested that there was little risk of a large outbreak in Surrey. Potential disease introductions through livestock movements from Surrey into Scotland were identified and these suggested that if the disease were introduced into Scotland there was great danger of substantial local spread. These methods described in this thesis have been used to map risk of FMD and subsequently applied to inform the risk presented by a different outbreak of FMD. The study underlines the value of detailed data both disease and demographic, for epidemic management. Similar methods could and should be applied to other infectious diseases threats of livestock such as HPAI and bluetongue.

The purpose of this project was to develop a reliable and valid battery for the assessment of spatial orientation skills (SOS) in persons with Alzheimer's disease (AD). The battery, comprised of 13 subtests, was administered to 97 normal control subjects, 25 subjects with early AD and 10 with late AD. The test-retest reliability of the battery was based on the test results of 33 normal control subjects and 25 early AD subjects. Inter-rater reliability was determined using four trained raters who evaluated 27 normal control subjects and the same 25 early AD subjects. Content validity was established using a panel of six experts and construct validity was determined by comparing the performance of the normal control and early AD groups. To establish criterion validity, the Global Deterioration Scale (GDS) was used as the criterion. For the AD group, eight subtests demonstrated acceptable test-retest and inter-rater reliability coefficients (ICC $ ge$.70). For the control group, three subtests had acceptable test-retest coefficients and four had acceptable inter-rater coefficients. The internal consistency of the battery was acceptable as shown by overall Cronbach's alpha of.86 for AD subjects and.72 for control subjects, and was further analyzed using factor analysis which yielded five factors. Logistic regression provided evidence for good construct validity. Scores on the SOS subtests were able to differentiate the three groups of subjects established on the basis of the GDS scores (GDS 1 and 2, GDS 3 and 4, and GDS 5). A preliminary shortened version of the battery was developed using six subtests which demonstrated high test-retest and inter-rater reliability. The performance of subjects with AD on the battery is discussed with respect to its implications for the theoretical basis and clinical assessment of spatial orientation in AD.

Septoria tritici is one of the most serious foliar diseases of winter wheat across England and Wales, causing considerable reduction in yield quality and production. There are increasing pressures to control such a disease using disease forecasting systems sociated with various meteorological factors.

This thesis focuses on the spread of organisms in both ecological and epidemiological contexts. In most of the studies presented, displacement is modeled with a spatial kernel function, which is characterized by scale and shape. These are measured by the net squared displacement (or kernel variance) and kurtosis, respectively. If organisms disperse by the assumptions of a random walk or correlated random walk, a Gaussian shaped kernel is expected. Empirical studies often report deviations from this, and commonly leptokurtic distributions are found, often as a result of heterogeneity in the dispersal process. In the studies presented in two of the included papers, the importance of the kernel shape is tested, by using a family of kernels where the shape and scale can be separated effectively. Both studies utilize spectral density approaches for modeling the spatial environment. It is concluded that the shape is not important when studying the population distribution in a habitat/matrix context. The shape is however important when looking at the invasion of organisms in a patchy environment, when the arrangement of patches deviates from randomly distributed. The introduced method for generating patch distribution is also compared to empirical distributions of patches (farms and old trees). Here it is concluded that the assumptions used for modeling of the spatial environment are consistent with the observed patterns. These assumptions include fractal properties such that the same aggregational patterns are found at different scales. In a series of papers, movements of animals are considered as vectors for between-herd disease spread. The studies are based on data found in databases held by the Swedish Board of Agricultural (SJV), consisting of reported movements, as well as farm location and characteristics. The first study focuses on the distance related probability of contacts between herds. In the following papers, the analysis is expanded to include production type and herd size. Movement data of pigs (and cattle in Paper I) are analyzed with Bayesian models, implemented with Markov Chain Monte Carlo (MCMC). This is a flexible approach that allows for parameter estimations of complex models, and at the same time includes parameter uncertainty. In Paper IV, the effects of the included factors are investigated. It is shown that all three factors (herd size, production type structure and distance related probability of contacts) are expected to influence disease spread dynamics, however the production type structure is found to be the most important factor. This emphasizes the value of keeping such information in central databases. The models presented can be used as support for risk analysis and disease tracing. However, data reliability is always a problem, and implementation may be improved with better quality data. The thesis also shows that utilizing spatial kernels for description of the spatial spread of organisms is an appropriate approach. However, these kernels must be flexible and flawed assumptions about the shape may lead to erroneous conclusions. Hence, the joint distribution of kernel shape and scale should be estimated. The flexibility of Bayesian analysis, implemented with MCMC techniques, is a good approach for this, and further allows for implementation of more complex models where other factors may be included.

The Mongolian gerbil is extensively used to model transient cerebral ischemia, a type of stroke that can occur with anoxia and cardiac arrest. A global ischemic insult in the gerbil produces damage to hippocampal CA1 pyramidal cells comparable to that observed in humans. A limited number of models are available to evaluate the behavioral consequences of cerebral ischemia in the gerbil. The goal of the present experiments was to evaluate the impact of transient cerebral ischemia on object and spatial recognition memory as these tasks have not been previously utilized with the gerbil model. Following ischemic insult (5-min bilateral carotid occlusion) or sham procedure, gerbils were tested in a familiar environment with novel objects. A familiarization phase followed by separate test phases for presentations of a novel object or object location were conducted. Exploratory behavior for the novel object or object location was evaluated using an automated tracking system. Results indicated that both ischemic and sham subjects were able to recognize the novel object when placed in the environment. However, when confronted with a familiar object, placed in a novel location, neither group exhibited a significant increase in exploratory behavior. A second experiment was conducted to further investigate the spatial recognition task. Subjects were habituated to the apparatus in addition to the experimental objects. Under this experimental condition, both groups exhibited significant exploratory behavior for the object placed in the novel location. The ischemic and control groups differed from each other during habituation with ischemic subject showing significantly higher activity levels. It is possible that differences between the groups remain but that these recognition findings are a result of extended habituation to the experimental objects. Further investigation of this matter is needed to determine the effect of prior object exposure on exploratory behavior in the spatial recognition task.

Thesis (Ph.D)--Industrial and Systems Engineering, Georgia Institute of Technology, 2009.
Committee Chair: Lu, Jye-Chyi; Committee Co-Chair: Kvam, Paul; Committee Member: Mei, Yajun; Committee Member: Serban, Nicoleta; Committee Member: Vidakovic, Brani. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Barmah Forest virus (BFV) disease is one of the most widespread mosquito-borne diseases in Australia. The number of outbreaks and the incidence rate of BFV in Australia have attracted growing concerns about the spatio-temporal complexity and underlying risk factors of BFV disease. A large number of notifications has been recorded continuously in Queensland since 1992. Yet, little is known about the spatial and temporal characteristics of the disease. I aim to use notification data to better understand the effects of climatic, demographic, socio-economic and ecological risk factors on the spatial epidemiology of BFV disease transmission, develop predictive risk models and forecast future disease risks under climate change scenarios. Computerised data files of daily notifications of BFV disease and climatic variables in Queensland during 1992-2008 were obtained from Queensland Health and Australian Bureau of Meteorology, respectively. Projections on climate data for years 2025, 2050 and 2100 were obtained from Council of Scientific Industrial Research Organisation. Data on socio-economic, demographic and ecological factors were also obtained from relevant government departments as follows: 1) socio-economic and demographic data from Australian Bureau of Statistics; 2) wetlands data from Department of Environment and Resource Management and 3) tidal readings from Queensland Department of Transport and Main roads. Disease notifications were geocoded and spatial and temporal patterns of disease were investigated using geostatistics. Visualisation of BFV disease incidence rates through mapping reveals the presence of substantial spatio-temporal variation at statistical local areas (SLA) over time. Results reveal high incidence rates of BFV disease along coastal areas compared to the whole area of Queensland. A Mantel-Haenszel Chi-square analysis for trend reveals a statistically significant relationship between BFV disease incidence rates and age groups (ƒÓ2 = 7587, p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. A cluster analysis was used to detect the hot spots/clusters of BFV disease at a SLA level. Most likely spatial and space-time clusters are detected at the same locations across coastal Queensland (p<0.05). The study demonstrates heterogeneity of disease risk at a SLA level and reveals the spatial and temporal clustering of BFV disease in Queensland. Discriminant analysis was employed to establish a link between wetland classes, climate zones and BFV disease. This is because the importance of wetlands in the transmission of BFV disease remains unclear. The multivariable discriminant modelling analyses demonstrate that wetland types of saline 1, riverine and saline tidal influence were the most significant risk factors for BFV disease in all climate and buffer zones, while lacustrine, palustrine, estuarine and saline 2 and saline 3 wetlands were less important. The model accuracies were 76%, 98% and 100% for BFV risk in subtropical, tropical and temperate climate zones, respectively. This study demonstrates that BFV disease risk varied with wetland class and climate zone. The study suggests that wetlands may act as potential breeding habitats for BFV vectors. Multivariable spatial regression models were applied to assess the impact of spatial climatic, socio-economic and tidal factors on the BFV disease in Queensland. Spatial regression models were developed to account for spatial effects. Spatial regression models generated superior estimates over a traditional regression model. In the spatial regression models, BFV disease incidence shows an inverse relationship with minimum temperature, low tide and distance to coast, and positive relationship with rainfall in coastal areas whereas in whole Queensland the disease shows an inverse relationship with minimum temperature and high tide and positive relationship with rainfall. This study determines the most significant spatial risk factors for BFV disease across Queensland. Empirical models were developed to forecast the future risk of BFV disease outbreaks in coastal Queensland using existing climatic, socio-economic and tidal conditions under climate change scenarios. Logistic regression models were developed using BFV disease outbreak data for the existing period (2000-2008). The most parsimonious model had high sensitivity, specificity and accuracy and this model was used to estimate and forecast BFV disease outbreaks for years 2025, 2050 and 2100 under climate change scenarios for Australia. Important contributions arising from this research are that: (i) it is innovative to identify high-risk coastal areas by creating buffers based on grid-centroid and the use of fine-grained spatial units, i.e., mesh blocks; (ii) a spatial regression method was used to account for spatial dependence and heterogeneity of data in the study area; (iii) it determined a range of potential spatial risk factors for BFV disease; and (iv) it predicted the future risk of BFV disease outbreaks under climate change scenarios in Queensland, Australia. In conclusion, the thesis demonstrates that the distribution of BFV disease exhibits a distinct spatial and temporal variation. Such variation is influenced by a range of spatial risk factors including climatic, demographic, socio-economic, ecological and tidal variables. The thesis demonstrates that spatial regression method can be applied to better understand the transmission dynamics of BFV disease and its risk factors. The research findings show that disease notification data can be integrated with multi-factorial risk factor data to develop build-up models and forecast future potential disease risks under climate change scenarios. This thesis may have implications in BFV disease control and prevention programs in Queensland.

This thesis contributes to Bayesian spatial and spatiotemporal methodology by investigating techniques for spatial imputation and joint disease modelling, and identifies high-risk individual profiles and geographic areas for type II diabetes mellitus (DMII) outcomes. DMII and related chronic conditions including hypertension, coronary arterial disease, congestive heart failure and chronic obstructive pulmonary disease are examples of ambulatory care sensitive conditions for which hospitalisation for complications is potentially avoidable with quality primary care. Bayesian spatial and spatiotemporal studies are useful for identifying small areas that would benefit from additional services to detect and manage these conditions early, thus avoiding costly sequelae.

The recent increased availability of geographically linked individual level health outcome data and improvements in exposure mapping techniques, which furnish point exposure estimates, motivate the development of spatial statistical methodology that takes full advantage of individual level data. Kernel density estimation is a powerful tool for mapping the risk of a health outcome that uses individual level data. Development of kernel density methodology has provided a global significance test for regions of elevated relative risk and a test for the spatial association between a health outcome and environmental exposure. Comparisons with some existing spatial statistical techniques highlight the strengths of the kernel density based methods. Moreover, simulation exercises indicate that the kernel density test for spatial association is a more powerful testing procedure than the most popular standard test proposed by Stone. Kernel density estimation and the global significance test for regions of elevated relative risk are illustrated for congenital malformations around a landfill site and sex ratios in Cardiff and the Vale of Glamorgan. The application of these methodologies revealed that both birth outcomes had a statistically significant heterogeneous spatial pattern over the relevant study regions even after adjustment for known confounders. Good quality, high resolution environmental exposure data was unavailable and prevented a direct application of the kernel density test for spatial association with a health outcome. However, the test can be applied to any two relative risk/density surfaces and was used to compare the spatial patterns of chromosomal and non-chromosomal anomalies in the region of the Nant y Gwyddon landfill site. It was concluded that the spatial patterns for the two sets of anomalies were different. The test was also used to assess the quality of the adjustment for confounders when producing expected risk surfaces and the adjustment was found to be adequate.

Boston University. University Professors Program Senior theses.
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2031-01-02

Spatial data is often aggregated into small area. It is challenging to analyse these data. Two new statistical techniques were developed to tackle these challenges. Bayesian meta-analysis models were used to unveil geographic disparities in cancer using the Australian Cancer Atlas. More flexible Bayesian Empirical Likelihood models were used to analyse more complex data including COVID19 deaths. Both methods provided new insights into the analysis of spatial data.

This doctoral thesis investigates the relationships between disorders of behavioural monitoring (including “productive” behaviours and unawareness of neuropsychological deficits) and unilateral spatial neglect in right-brain-damaged patients. One main monitoring disorder is recurrent perseveration, namely a “productive” motor symptom frequently found in target cancellation tasks: we demonstrate, in two specific tasks (Experiments 1 and 2), that the disposition of the stimuli and the type of target modulate its severity. Neglect patients showing perseveration in visuo-motor exploratory tests perseverate also in drawing tasks. No correlation between omission and perseveration errors is found, supporting the functional independence of the two deficits. In the context of a two-component hypothesis, perseveration (the first component) is a specific disorder that manifests in a variety of tasks, particularly those requiring serial graphic production; unilateral spatial neglect (the second component) may trigger and facilitate the production of perseveration errors. Moreover results indicate that patients with perseveration are not disproportionately impaired in tasks assessing executive, visuo-spatial short-term memory, and attentional functions, suggesting the specificity of the monitoring disorder associated with spatial neglect. Lesion analysis indicates damage to the right insula as a relevant neural correlate of perseverative behaviour. Experiment 3 shows that perseverating patients produce a majority of substitution errors during a word reading task, suggesting that also this type of paralexic neglect error can be considered a “productive” manifestation. The clinical, experimental and neural features of another monitoring deficit and “positive” manifestation referring to the personal space, “somatoparaphrenia”, are reviewed: somatoparaphrenia is a symptom usually associated with right-sided hemispheric lesions, most often characterized by a delusion of disownership of contralesional body parts. Possible pathological factors may include a deranged representation of the body concerned with ownership, mainly right-hemisphere-based, and deficits of multisensory integration. Finally, Experiment 4 investigates anosognosia for unilateral spatial neglect by a quantitative assessment. Results indicate that unawareness for spatial attentional and representational deficits is not a pervasive disorder, and that some tasks can evoke different degrees of awareness. In addition, the scores assigned by neglect patients to their performance in spatial tasks are not modulated by the different conditions of the estimation tasks. In conclusion, we demonstrate that: 1) “productive”, as “defective”, manifestations of unilateral spatial neglect are multifarious; 2) these “positive” phenomena are independent of general executive deficits and of the severity of the spatial neglect syndrome; 3) the neural bases of motor productive disorders included the right insula; 4) neglect patients are not globally anosognosic about their spatial defective performances.

Since its initial identification in 1975, Lyme disease has become a public health concern in the U.S.  Increased concern is sparked by the rapid rate at which the disease is emerging into new areas.  One area of disease emergence is the state of Virginia which has been experiencing exponentially increasing rates of the disease.  This research studies Virginia\'s landscape-level habitats to explore demographic and environmental variables related to the spread of Lyme disease.

The land cover data came from the National Land Cover Database (2006), demographic data came from the U.S. census (2010), and Lyme disease case data came from the Virginia Department of Health (2006-2010).  Key variables examined in this statewide study include the percentages of landscape types measured inside each census tract, measures of forest fragmentation, and measures of land cover interspersion inside state census tracts

Analysis was carried out using a spatial Poisson regression model.  Of the original 15 variables, 10 were significantly correlated to Lyme disease.  The six that were positively correlated with disease incidence include percent herbaceous land, percent water, two edge contrast measurements of herbaceous-forest land, median age, and average income.  The four that were negatively correlated were percent developed, population density, and two edge contrast measurements of developed-herbaceous land.

Overall results indicate that specific environmental and demographic variables are associated with increased disease incidence as Lyme disease emerges in Virginia.  Results from this study could help create a predictive statewide map for Lyme disease incidence and aid in disease awareness and resource allocation.
Master of Science

Positron emission tomography (PET) produces images of functional processes of the body in-vivo. The analysis of PET data for research purposes traditionally involves kinetic modeling of the concentration of the radiotracer over time within a region of interest (ROI) in the body to derive parameters related to the uptake/binding of the radiotracer in that region. PET imaging is commonly used to study Parkinson's disease (PD), where loss of motor function is caused by the progressive death of neurons in the brain that produce the neurotransmitter dopamine. In PD, both the kinetic and the spatial distribution of the tracer change due to the disease: the posterior parts of the striatum (in particular in the putamen) are affected before the anterior parts. The purpose of this dissertation is to develop a novel analysis method for PET data that uses the spatial characteristics of the radiotracer's distribution within anatomically-defined ROIs to extract additional information about pathological states. The proposed analysis method is based on mathematical 3D shape descriptors that are invariant to translation, scaling, and rotation, called 3D moment invariants (3DMIs). The variable of interest in this case is not only the radiotracer's uptake rate constant or binding potential, but also the 3D spatial shape and distribution of the radioactivity within the ROI. This dissertation shows that 3DMIs were able to successfully quantify differences in the spatial distribution of PET radiotracer images between healthy controls and PD subjects. 3DMI values were found to correlate with a clinical measure of disease severity in all anatomical regions studied here (putamen, caudate and ventral striatum), as opposed to kinetic parameters which only showed significant correlation to clinically-assessed PD severity in the putamen. Levodopa-induced changes in spatial patterns of dopamine release (as measured using 3DMIs) were found to be significantly correlated with PD severity in all ROIs studied here. These findings suggest that quantitative studies of a radiotracer's spatial distribution can be complementary to kinetic modeling in extracting information about pathological states from PET data and have the potential to contribute novel information in PET neuroimaging studies.

Apple scab is the most important disease of apples in most of the world. The disease, caused by Venturia inaequalis, is controlled by numerous fungicide applications, regardless of the presence of inoculum in the orchard. Better timing of fungicide applications could be achieved if the airborne ascospore concentration (AAC) was considered in decision making. AAC can be measured in real time using spore traps. In this project, the relationship between AAC and lesions development was studied under controlled and natural conditions for five cultivars: Empire, McIntosh, Jonagold, Royal Gala, and Spartan. Potted trees were exposed to different airborne ascospore inoculum and the corresponding AAC were measured using spore traps. The spatial distribution of ascospores was studied in a commercial apple orchard plot. The potential ascospore dose (PAD) and the AAC were measured in 40 quadrats in the spring of 1999. (Abstract shortened by UMI.)

Recent trends in emerging and re-emerging human infectious disease indicate that zoonotic diseases are on the rise (e.g., SARS, Swine Flu, Bird flu, Ebola, and Lyme disease), creating large economic and social costs. The increasingly dominant role that humans are playing in changing the environment is thought to be a leading cause for this increasing emergence. In this dissertation, I investigated the effects of landscape level changes on a specific host parasite system: red colobus (Procolobus rufomitratus) and gastrointestinal nematode parasites within Kibale National Park, Uganda landscape. I first quantified the variation in forest recovery in the region and their effects on the resident primate community. Next, I explored the link between forest structure and red colobus movement patterns by 1) developing a new measure of habitat use (STBBD), quantifying the predilection of an animal to revisit habitat patches, and 2) testing between several hypotheses to explain red colobus movement patterns. Finally, I developed a spatially-explicit epidemiological model using the insights developed in forest structure and red colobus movement patterns. This model was used to assess the disease-related consequences of habitat fragmentation, quantifying the relative effects of the extent of habitat and its spatial configuration. My epidemiological model illustrate that by taking advantage of advances in spatial data analysis it is possible to expand the range of questions that can be addressed, developing a more spatially explicit understanding of infectious disease. I also argue that by including specific landscapes and host behaviours, these approaches increase the relevance of the results for disease management, allowing managers and researches to take a more proactive role and assess the effects of planned or predicted landscape changes on host-parasite dynamics.
Les tendances récentes dans les maladies infectieuses humaines émergentes et réémergentes indiquent que les maladies zoonotiques sont à la hausse (par exemple, le SRAS, la grippe porcine, la grippe aviaire, le virus Ebola et la maladie de Lyme), générant d'importants coûts économiques et sociaux. Le rôle de plus en plus dominant que les humains jouent dans la transformation de l'environnement est considéré comme une des principales causes de cette émergence. Dans cette thèse, j'ai étudié les effets des changements au niveau du paysage sur un système hôte-parasite spécifique : le colobe roux (Procolobus rufomitratus) et les nématodes gastro-intestinaux dans le parc national de Kibale, en Ouganda. J'ai d'abord quantifié la variation de la reconstitution de la forêt dans la région et leurs effets sur la communauté des primates. Par la suite, j'ai exploré le lien entre la structure de la forêt et les habitudes de déplacement des colobes roux par 1) l'élaboration d'une nouvelle mesure de l' utilisation de l'habitat (ST-BBD), la quantification de la prédilection d'un animal de revisiter des parcelles d'habitat, et 2 ) des tests avec plusieurs hypothèses afin d'expliquer les habitudes de déplacement des colobes roux. Enfin, j'ai développé un modèle épidémiologique spatialement explicite en utilisant les idées développées dans la structure de la forêt et l'utilisation du territoire des colobes roux. Ce modèle a été utilisé pour évaluer les conséquences des maladies liées à la perte d'habitat, en quantifiant les effets relatifs de la fragmentation et de l'ampleur de la perte. Mes modèles épidémiologiques montrent que, en prenant avantage de l'amélioration des techniques d'analyse spatiale, il est possible d'élargir l'éventail de questions qui peuvent être abordées, en développant une compréhension plus spatialement explicite des maladies infectieuses. Je soutiens également que, en sélectionnant spécifiquement des paysages et des comportements de l'hôte, ces approches augmentent la pertinence des résultats à la gestion de la maladie, permettant aux gestionnaires et aux chercheurs de jouer un rôle plus proactif et d'évaluer les effets des changements prévus ou planifiés du paysage sur la dynamique hôte-parasite.

Space constitutes one of the core framing structures of experience in the natural environment. Therefore, communicating spatial information with verbal means, such as locative relations between objects, is vital for numerous everyday activities and constitutes a core part of human linguistic communication. The present project aimed to 1) develop psychometrically sound measures assessing spatial language abilities, including naming static and dynamic spatial relations, memory for route- and survey-based descriptions, and comprehension of descriptions of locative relations under different spatial reference frames; 2) identify the trajectories of these spatial language abilities across the adult-lifespan and contrast them against trajectories of various (non-verbal) visuospatial and (non-spatial) verbal abilities; and 3) investigate spatial language abilities in individuals who are at an early stage of Alzheimer’s disease (AD), for the first time. Across a series of studies involving 160 adults aged between 18 and 85, we found comparable age-related declines in spatial language and visuospatial abilities, although their onset and magnitude depended on the type of subability examined. By contrast, verbal abilities remained well-preserved with increasing age. Moreover, performance in spatial language measures was found to discriminate mild AD patients and age-, education-, and gender-matched controls to a very high degree. The results of the present work have several theoretical and practical implications, as they 1) establish the test-retest reliability, and the concurrent, construct and discriminative validity of the newly-developed spatial language measures; 2) reveal a number of divergent and convergent domain-specific cognitive changes across the adult-lifespan; 3) extend the large existing literature on the detrimental (a)typical ageing effects on visuospatial cognition by demonstrating that spatial processing is also compromised when assessed through language; and 4) suggest that language- and perception-based representations of space are underpinned by comparable cognitive operations and supported by overlapping neural networks that are particularly sensitive to ageing effects.

In the last ten years, there has been significant progress towards the prevention, control and elimination of podoconiosis as a health problem. There are however gaps in our understanding of the epidemiology and geography of podoconiosis that hinder the planning and scale-up of intervention activities. Therefore, this PhD project aimed to define the current geographical distribution and disease burden of podoconiosis in Ethiopia and investigate underlying risk factors. This thesis adopted two main approaches to understanding distribution: first, historical data were compiled and analysed; second, a nationwide mapping survey was conducted. These data were contextualised through a systematic review of the literature on neglected tropical diseases (NTDs) in Ethiopia. The data were also used to develop elimination targets and endemicity classifications in a Delphi exercise involving a range of international NTD experts.

Lung cancer is the leading cause of cancer death in the United States, but a large fraction of cases is preventable. We use a spatial smoothing algorithm to identify a geographic pattern of high lung cancer mortality, primarily in the Southeast, which we call a lung cancer belt. Disease belts are an effective mode for conveying patterns of high incidence or mortality; formally defining this lung cancer belt may encourage increased public dialogue and more focused research. Public health officials could complement existing population lung cancer data with this information to help inform resource allocation decisions.

This thesis addresses three interrelated challenges of disease mapping and contributes a new approach for improving visualization of disease burdens to enhance disease surveillance systems. First, it determines an appropriate threshold choice (smoothing parameter) for the adaptive kernel density estimation (KDE) in disease mapping. The results show that the appropriate threshold value depends on the characteristics of data, and bandwidth selector algorithms can be used to guide such decisions about mapping parameters. Similar approaches are recommended for map-makers who are faced with decisions about choosing threshold values for their own data. This can facilitate threshold selection. Second, the study evaluates the relative performance of the adaptive KDE and spatial empirical Bayes for disease mapping. The results reveal that while the estimated rates at the state level computed from both methods are identical, those at the zip code level are slightly different. These findings indicate that using either the adaptive KDE or spatial empirical Bayes method to map disease in urban areas may provide identical rate estimates, but caution is necessary when mapping diseases in non-urban (sparsely populated) areas. This study contributes insights on the relative performance in terms of accuracy of visual representation and associated limitations. Lastly, the study contributes a new approach for delimiting spatial units of disease risk using straightforward statistical and spatial methods and social determinants of health. The results show that the neighborhood risk map not only helps in geographically targeting where but also in tailoring interventions in those areas to those high risk populations. Moreover, when health data is limited, the neighborhood risk map alone is adequate for identifying where and which populations are at risk. These findings will benefit public health tasks of planning and targeting appropriate intervention even in areas with limited and poor-quality health data. This study not only fills the identified gaps of knowledge in disease mapping but also has a wide range of broader impacts. The findings of this study improve and enhance the use of the adaptive KDE method in health research, provide better awareness and understanding of disease mapping methods, and offer an alternative method to identify populations at risk in areas with limited health data. Overall, these findings will benefit public health practitioners and health researchers as well as enhance disease surveillance systems.

This thesis investigated the role of the supplementary motor area (SMA) in visuospatial processing using Parkinson’s disease (PD) patients as a model of pre-supplementary motor area (pre-SMA) dysfunction. The vector transformation hypothesis assumes that visuospatial transformation deficits in PD are a result of impairments in calculating vectors or co-ordinate remapping with a reference frame. These vector transformation processes were investigated in spatial normalisation during mental rotation and showed that PD patients demonstrate slower image normalisation rates indicative of a deficit compares with controls. It was then investigated how far these deficits extend to other vector transformation tasks such as abstract grid navigation. PD patients were less accurate than controls and these deficits were independent of spatial short term memory and serial processing suggesting that PD is associated with spatial transformation deficits. Comparisons of visual vector transformation and auditory vector transformation showed that PD patients were less accurate at visual vector transformation than auditory vector transformation suggesting that vector transformation processes may be more sensitive to the visual domain. The final study was a pilot study to investigate the feasibility of using a cognitive vector transformation task to remediate symptoms of bradykinesia in PD. Modest improvements in movement velocity following the vector transformation task but no significant change in movement velocity following a control task suggests that vector transformation can be used for therapeutic gain.

All wildlife populations harbour parasites. However, seabirds are likely to play a particularly important role in the maintenance and dispersal of infectious agents as a result of their colonial breeding habits. Seabird colonies are also known to be highly spatially structured, but little is known about the effects of this spatial structuring on seabird parasite dynamics. In this thesis, I use a tick-borne virus, Great Island virus (GIV), found in a large common guillemot (Uria aalge) colony bordering the North Sea as a model system to explore this relationship. I use a multidisciplinary approach, framed by a simple epidemiological model of the guillemot-tick-virus system. In Chapter 2, I describe a novel epidemiological model and parameterise it using the existing literature. The model suggests the importance of spatial structure within the guillemot colony, but also identifies a key missing parameter, the rate of virus transmission between pre-breeding and breeding areas. In Chapter 3, I go on to test the potential role of independent tick movement in driving transmission between these two areas, by quantifying the mobility of host-seeking seabird ticks, Ixodes uriae. I show the potential for ticks to walk ranges described anecdotally in the literature, in just a few minutes, but stress the importance of further experiments in the field. Chapter 4, I test the potential role of guillemot-mediated tick movement between pre-breeding and breeding areas. I show that pre-breeding guillemots spend a limited proportion of time ashore during daylight hours, which increases significantly as the season progresses and varies between individuals. A similar pattern is observed when considering how often they enter breeding areas when ashore; generally infrequently but varying spatiotemporally and between individuals. In Chapter 5, I apply finite mixture modelling techniques to improve existing estimates of age- and strain-specific GIV seroprevalence and force of infection in the guillemot colony. I also provide the first estimates of these parameters for eight strains, and highlight the importance of understanding strain-specific differences in GIV dynamics in future studies. Finally, I bring all four data chapters together in Chapter 6, by inputting my new parameter estimates (Chapters 3-5) into my existing model (Chapter 2). Taken together, my results suggest that GIV transmission within the guillemot colony may increase in the future as a result of declining breeding abundance and success, with more frequent or extreme disruption leading to a higher risk of infection within the colony. More generally, my results suggest that seabird colonies can be highly sensitive to changes in their spatial structure, and that endemic parasites have the potential to substantially impact, and hence to be an added threat to, their seabird hosts.

Alors que l’épidémiologie de la dengue dans le sud du Vietnam est caractérisée par un régime d’hyper-endémicité, la maladie est en train d’émerger dans le nord du pays depuis une quinzaine d’années. Les incidences annuelles augmentent de façon constante d’année en année et la maladie diffuse à partir de Hanoi vers les zones rurales environnantes. Le travail de recherche effectué durant cette thèse s’intéresse aux déterminants spatiaux et temporels de la transmission de la dengue dans un contexte d’émergence. Les résultats sont organisés en 3 parties. La première se concentre sur l’étude d’une épidémie qui frappa à l’automne 2013 l’île de Cat Ba, au large du Vietnam dans la baie d’Halong. Cette île est caractérisée par une population de petite taille vivant essentiellement de l’exploitation des produits de la mer ainsi que du tourisme. Une grande proportion de cette population vit sur des villages flottant au large de l’île. Nous avons comparé l’épidémiologie de la dengue sur les villages flottants et sur l’île. Pour cela nous avons testé l’agrégation spatio-temporelle des cas de dengue. Nos résultats montrent une incidence de dengue sur les villages flottant plus forte que sur l’île, malgré des densités de moustiques plus faibles. Les cas de dengue étaient également extrêmement agrégés dans le temps et l’espace, suggérant une importation de moustiques infectés plutôt qu’un cycle de transmission local complet.La seconde partie de cette thèse s’est intéressée aux déterminants environnementaux de la transmission de la dengue dans la province de Hanoi. Cette étude est basée sur l’analyse de 31906 cas de dengue géospatialisés de 2008 à 2013 et utilise des méthodes de SIG couplées avec des techniques modernes d’apprentissage automatique dans le but de quantifier en détail les influences de chaque covariable environnementale sur le risque de dengue. Nos résultats montrent une forte influence de la densité de population sur l’incidence de la dengue, comme précédemment documenté dans d’autres régions du monde. L’incidence de la dengue augmente avec la couverture végétale pour de faibles niveaux de couverture végétale et atteint de très faibles niveaux lorsque la couverture végétale est au-dessus d’un certain seuil. Une telle relation est cohérente avec ce qui est actuellement connu sur l’écologie des vecteurs de dengue. Finalement, nos résultats ont montré une forte association entre les incidences de dengue et les zones résidentielles universitaires. Ces zones sont peuplées d’étudiants venant des régions autour de Hanoi où l’incidence est faible. La susceptibilité à la dengue de cette population estudiantine est donc plus forte que dans le reste de la population de Hanoi.La dernière partie de cette thèse s’est intéressée aux relations entre les épidémies successives de dengue à Hanoi de 2011 à 2014. L’épidémiologie de la dengue à Hanoi est très saisonnière avec de très faibles incidences en hiver. Une question majeure dans une telle situation est de savoir si les virus de dengue persistent localement entre chaque épidémie. Si non, alors les cas de dengue observés en hiver correspondraient à des cas d’importation qui pourraient démarrer une nouvelle épidémie chaque été lorsque les conditions climatiques locales deviennent à nouveau favorables pour la transmission de la dengue. Nous avons utilisé une approche de phylogénie moléculaire de virus échantillonnés à Hanoi ainsi que dans d’autres localités en Asie du sud-est d’où les virus de dengue pourraient migrer. L’idée d’une telle approche consiste à comparer les distances phylogénétiques entre des virus circulants dans une localité une année donnée et des virus circulants soit la même année dans d’autres localités, soit durant les années précédentes dans la même localité. Nos résultats suggèrent que, chaque année, les épidémies de dengue à Hanoi démarrent à partir des virus de dengue importés depuis Ho Chi Minh ville. Ce schéma semble être le cas pour les 4 sérotypes de dengue
While high dengue transmission has been documented in the southern part of Vietnam since the late seventies, the disease started to emerge in the northern part of the country 15 years ago only. In northern Vietnam, annual incidences are consistently increasing from year to year and progressively spreading from Hanoi to the surrounding rural areas. Very little is known on the causes of this recent emergence.The research carried out in this PhD revolves around the spatial and temporal determinants of dengue epidemiological transmission in a context of emergence and the results are organized in 3 parts. The first one focuses on a single epidemic of dengue that occurred during the autumn of 2013 on the small island of Cat Ba, off the coast of Vietnam in Ha Long bay. Cat Ba island is characterized by a population of a small size mostly living from sea farming and tourism. Dengue transmission on this island has been historically rare until the major epidemics that stroke the island in 2013. The population of Cat Ba has this specificity that a large proportion of it lives of floating villages off the island coast. We were interested in investigating whether the epidemics had different behavior on the island and the floating villages. To achieve this aim, we focused on the identification of spatio-temporal clusters of cases. Our results show a higher dengue incidence on the floating villages than on the island despite lower mosquito densities. Dengue cases were also highly clustered in space and time suggesting importation of infected mosquitoes rather than a local complete transmission cycle.The second part focuses on the environmental determinants of dengue transmission in the province of Hanoi. This study is based on the use of 31,906 geospatialized cases of dengue from 2008 to 2013 and applies GIS techniques coupled with modern machine learning techniques in order to quantify in detail the influences of each environmental covariate on dengue risk. Our results showed a strong influence of population density on dengue incidence as previously reported in other parts of the world. Dengue incidence increased with tree coverage for low levels of tree coverage and then reached very low levels for tree coverage above a given threshold. This pattern is consistent with the current knowledge of the dengue vector ecology. Finally we showed a strong association of dengue incidence with academic residential areas. Such areas are populated with students coming from locations around Hanoi with low dengue incidence. The susceptibility of this student population to dengue infection is thus higher than the rest of the Hanoian population.The final part looked at the relationships between the successive epidemics in Hanoi from 2011 to 2014. Dengue epidemiology in Hanoi is very seasonal with very few cases documented in winter. A major question in such situations is whether viruses actually persist locally between epidemics. If not, then observed cases during the winter would correspond to imported cases igniting new epidemics every summer when the local climatic conditions are favorable again for local dengue transmission. To do so, we used phylogenetic analyses of virus sampled in Hanoi combined with virus sampled in other locations in Southeast Asia from where dengue viruses could migrate. The rationale behind this method is to compare the phylogenetic distances between sequences circulating in a given location in a given year and sequences circulating either the same year in other locations or previous years in the same location. Our results suggest that every year dengue epidemics in Hanoi are started from viruses imported from Ho Chi Minh city. This seems to be the case for the 4 dengue serotypes

Cancer is the leading contributor to the disease burden in Australia. This thesis develops and applies Bayesian hierarchical models to facilitate an investigation of the spatial and temporal associations for cancer diagnosis and survival among Queenslanders. The key objectives are to document and quantify the importance of spatial inequalities, explore factors influencing these inequalities, and investigate how spatial inequalities change over time. Existing Bayesian hierarchical models are refined, new models and methods developed, and tangible benefits obtained for cancer patients in Queensland. The versatility of using Bayesian models in cancer control are clearly demonstrated through these detailed and comprehensive analyses.

Magmatic-hydrothermal systems typically have vertical extents of several hundred
meters and their geochemical characteristics (e.g. mineral assemblages) vary considerably
over that vertical extent. As a consequence the expression in outcrop varies depending on
the level of erosion. Therefore understanding the geochemical zonation of magmatic-hydrothermal
ore deposits opens the possibility to detect deep magmatic-hydrothermal
systems, and to assess qualitatively the degree of erosion that has taken place in the area
and at which level the mineralization may occur. This dissertation presents the
characterization of two shallow hydrothermal systems and their potential relations with
deeper magmatic-hydrothermal systems. In addition, this dissertation develops the
equations to directly interpret thermometric data from the fluid inclusion type dominant in
one of those deposits (fluid inclusions that homogenize by halite disappearance).
Red Mountain, AZ is a porphyry copper system with a well-preserved lithocap
providing an ideal candidate to characterize the shallow expression of porphyry copper
systems in the southwestern US. The distribution of fluid inclusions, alteration mineralogy
and grade indicate that the intrusive responsible for the mineralization was only partially
intercepted during the exploration program and that one single magmatic event was likely
responsible for the mineralization detected. Fluid inclusion types and clay minerals are
systematically distributed within the deposit. The fluid responsible for the shallow
hypogene mineralization was a low pH-intermediate temperature-low density fluid while a
high salinity fluid was responsible for deep mineralization.
Wutong is a Pb-Zn-Ag deposit in the Nanling belt (southeast China). The combination
of fluid inclusion and mineral thermometry indicates that the Wutong deposit formed at
relatively low pressures. The age and isotopic composition of the mineralization indicates
that the deposit formed during the Cretaceous from crustal derived fluids. The occurrence
of a shallow magmatic-hydrothermal system of Cretaceous age in this region suggests that
Cretaceous intrusions, despite not outcropping very commonly in this particular region may
occur at deeper levels.
Ph. D.

This thesis develops and applies statistical methodologies to model brain atrophy in humans among multiple brain regions and how this may change over time. Throughout this work, Bayesian multilevel models are progressively developed for single and multiple regions at a given time point as well as modelling how connectivity between multiple regions evolves over time in conjunction with region level estimates. The application of these models provide insight into the detection of longitudinal brain atrophy patterns consistent with healthy ageing or progression towards Alzheimer's disease, and should be of interest to biostatisticians and researchers who deal with neurological spatial data.

Haemoglobinopathies, which include sickle-cell anaemia (SCA) and α- and β-thalassaemia, represent some of our few unequivocal examples of human evolution. The underlying genetic mutations reflect a recurring adaptation against one of the biggest infectious disease killers of humans, Plasmodium falciparum malaria. Inheritance of one copy of a sickle-cell or thalassaemic allele leads to protection against death from malaria, while two copies can result in a severe blood disorder. As a result, haemoglobinopathies have risen in frequency through balancing selection and pose a significant public health problem in parts of the world with a history of malaria transmission. Their study therefore lies at the interface between evolutionary biology and public health. In this thesis, I explore different aspects of the epidemiology and population genetics of haemoglobinopathies around the world. Using pre-existing epidemiological data, statistical and geostatistical methods and Geographic Information System tools, I develop detailed evidence-based maps of the α-thalassaemia allele frequency distribution and genetic diversity in Southeast Asia and sickle-cell allele frequency in India. Pairing these with birth data, I generate sub-national estimates of the number of newborns born with severe forms of α-thalassaemia and SCA in Thailand and India, respectively, together with uncertainty estimates. In addition, I use a flexible population genetic simulation model to explore evolutionary explanations for the contrasting spatial haplotype patterns observed for SCA and the severe form of β-thalassaemia (β0-thalassaemia) in sub-Saharan Africa and the Middle East, and resurrect a 20-year old question surrounding the genetic origin of sickle-cell. Understanding the fine-scale geographical heterogeneities in the distributions of malaria-protective haemoglobinopathies is critical for addressing basic science questions and applied public health queries. Working at the interface between evolutionary biology and public health has provided me with the opportunity to build a more complete overview of the neglected increasing public health burden that this group of human disorders represents.