Endemic tuberculosis, the homeless, and public transportation: A merging of geographical information systems surveillance and the Houston Tuberculosis Initiative Surveillance project

To reach the goals established by the Institute of Medicine (IOM) and the Centers for Disease Control's (CDC) STOP TB USA, measures must be taken to curtail a future peak in Tuberculosis (TB) incidence and speed the currently stagnant rate of TB elimination. Both efforts will require, at minimum, the consideration and understanding of the third dimension of TB transmission: the location-based spread of an airborne pathogen among persons known and unknown to each other. This consideration will require an elucidation of the areas within the U.S. that have endemic TB. The Houston Tuberculosis Initiative (HTI) was a population-based active surveillance of confirmed Houston/Harris County TB cases from 1995–2004. Strengths in this dataset include the molecular characterization of laboratory confirmed cases, the collection of geographic locations (including home addresses) frequented by cases, and the HTI time period that parallels a decline in TB incidence in the United States (U.S.). The HTI dataset was used in this secondary data analysis to implement a GIS analysis of TB cases, the locations frequented by cases, and their association with risk factors associated with TB transmission. ^ This study reports, for the first time, the incidence of TB among the homeless in Houston, Texas. The homeless are an at-risk population for TB disease, yet they are also a population whose TB incidence has been unknown and unreported due to their non-enumeration. The first section of this dissertation identifies local areas in Houston with endemic TB disease. Many Houston TB cases who reported living in these endemic areas also share the TB risk factor of current or recent homelessness. Merging the 2004–2005 Houston enumeration of the homeless with historical HTI surveillance data of TB cases in Houston enabled this first-time report of TB risk among the homeless in Houston. The homeless were more likely to be US-born, belong to a genotypic cluster, and belong to a cluster of a larger size. The calculated average incidence among homeless persons was 411/100,000, compared to 9.5/100,000 among housed. These alarming rates are not driven by a co-infection but by social determinants. The unsheltered persons were hospitalized more days and required more follow-up time by staff than those who reported a steady housing situation. The homeless are a specific example of the increased targeting of prevention dollars that could occur if TB rates were reported for specific areas with known health disparities rather than as a generalized rate normalized over a diverse population. ^ It has been estimated that 27% of Houstonians use public transportation. The city layout allows bus routes to run like veins connecting even the most diverse of populations within the metropolitan area. Secondary data analysis of frequent bus use (defined as riding a route weekly) among TB cases was assessed for its relationship with known TB risk factors. The spatial distribution of genotypic clusters associated with bus use was assessed, along with the reported routes and epidemiologic-links among cases belonging to the identified clusters. ^ TB cases who reported frequent bus use were more likely to have demographic and social risk factors associated with poverty, immune suppression and health disparities. An equal proportion of bus riders and non-bus riders were cultured for Mycobacterium tuberculosis, yet 75% of bus riders were genotypically clustered, indicating recent transmission, compared to 56% of non-bus riders (OR=2.4, 95%CI(2.0, 2.8), p<0.001). Bus riders had a mean cluster size of 50.14 vs. 28.9 (p<0.001). Second order spatial analysis of clustered fingerprint 2 (n=122), a Beijing family cluster, revealed geographic clustering among cases based on their report of bus use. Univariate and multivariate analysis of routes reported by cases belonging to these clusters found that 10 of the 14 clusters were associated with use. Individual Metro routes, including one route servicing the local hospitals, were found to be risk factors for belonging to a cluster shown to be endemic in Houston. The routes themselves geographically connect the census tracts previously identified as having endemic TB. 78% (15/23) of Houston Metro routes investigated had one or more print groups reporting frequent use for every HTI study year. We present data on three specific but clonally related print groups and show that bus-use is clustered in time by route and is the only known link between cases in one of the three prints: print 22. (Abstract shortened by UMI.)^

Raster maps for 29 environmental variables in three geographical regions

Aim: Greater understanding of the processes underlying biological invasions is required to determine and predict invasion risk. Two subspecies of olive (Olea europaea subsp. europaea and Olea europaea subsp. cuspidata) have been introduced into Australia from the Mediterranean Basin and southern Africa during the 19th century. Our aim was to determine to what extent the native environmental niches of these two olive subspecies explain the current spatial segregation of the subspecies in their non-native range. We also assessed whether niche shifts had occurred in the non-native range, and examined whether invasion was associated with increased or decreased occupancy of niche space in the non-native range relative to the native range. Location: South-eastern Australia, Mediterranean Basin and southern Africa. Methods: Ecological niche models (ENMs) were used to quantify the similarity of native and non-native realized niches. Niche shifts were characterized by the relative contribution of niche expansion, stability and contraction based on the relative occupancy of environmental space by the native and non-native populations. Results: Native ENMs indicated that the spatial segregation of the two subspecies in their non-native range was partly determined by differences in their native niches. However, we found that environmentally suitable niches were less occupied in the non-native range relative to the native range, indicating that niche shifts had occurred through a contraction of the native niches after invasion, for both subspecies. Main conclusions: The mapping of environmental factors associated with niche expansion, stability or contraction allowed us to identify areas of greater invasion risk. This study provides an example of successful invasions that are associated with niche shifts, illustrating that introduced plant species are sometimes readily able to establish in novel environments. In these situations the assumption of niche stasis during invasion, which is implicitly assumed by ENMs, may be unreasonable.

Tab. 1: Muskoxen observed in the different geographical units

Muskoxen populations were surveyed in the course of 3 expeditions to North East Greenland to provide data on present status and habitat requirements in the region between 72 and 74 deg latitude North. The distribution is primarily affected by the snow cover pattern and shows densities from less than 0.1 ind/km**2 to 1.5 ind/km**2. Ranges unutilized by muskoxen prior to 1940 now support high densities. The snow cover influences also the population dynamics, as shown by the streng correlation between the calf crop and the amount of snow. The total population is estimated to be about 1000 to 1500 individuals far the whole region.

Tab. 1: Geographical, temperature and chemical features of sites on Bear Island and Spitsbergen

In arctic populations of Macrothrix hirsuticornis life cycles are mainly governed by temperature. This was found by using laboratory cultures in combination with the analysis of population samples from waters in Svalbard. In arctic waters ex-ephippio-++ usually produce gamogenetic F1-++ together with a high percentage of oo, which have to fertilize the resting eggs. Temperatures around 14°C, which are very rare in waters of Svalbard, will induce parthenogenetic oo in the F1 and even the F2-generation, a mode of reproduction normally found in Macrothrix-populations of Central Europe. This was found in laboratory cultures of M. hirsuticornis from Bear Island, and there was evidence, that a similar cycle occurs in warm wells in Spitsbergen. The arctic distribution of M. hirsuticornis mainly depends on temperature, which regulates the speed of individual development. But this can only be understood together with the length of time, during which suitable life conditions are given. Physiological adaptations to life in waters in high latitudes could not be found, in spite of the extreme northern occurrence of M. hirsuticornis.

Geographical variation in shell morphology of juvenile snails (Concholepas concholepas) along the physical-chemical gradient of the Chilean coast

Changes in phenotypic traits, such as mollusc shells, are indicative of variations in selective pressure along environmental gradients. Recently, increased sea surface temperature (SST) and ocean acidification (OA) due to increased levels of carbon dioxide in the seawater have been described as selective agents that may affect the biological processes underlying shell formation in calcifying marine organisms. The benthic snail Concholepas concholepas (Muricidae) is widely distributed along the Chilean coast, and so is naturally exposed to a strong physical-chemical latitudinal gradient. In this study, based on elliptical Fourier analysis, we assess changes in shell morphology (outlines analysis) in juvenile C. concholepas collected at northern (23°S), central (33°S) and southern (39°S) locations off the Chilean coast. Shell morphology of individuals collected in northern and central regions correspond to extreme morphotypes, which is in agreement with both the observed regional differences in the shell apex outlines, the high reclassification success of individuals (discriminant function analysis) collected in these regions, and the scaling relationship in shell weight variability among regions. However, these extreme morphotypes showed similar patterns of mineralization of calcium carbonate forms (calcite and aragonite). Geographical variability in shell shape of C. concholepas described by discriminant functions was partially explained by environmental variables (pCO2, SST). This suggests the influence of corrosive waters, such as upwelling and freshwaters penetrating into the coastal ocean, upon spatial variation in shell morphology. Changes in the proportion of calcium carbonate forms precipitated by C. concholepas across their shells and its susceptibility to corrosive coastal waters are discussed.

The IDE geographical simulation model : predicting long-term effects of infrastructure development projects

It is important to be able to predict changes in the location of populations and industries in regions that are in the process of economic integration. The IDE Geographical Simulation Model (IDE-GSM) has been developed with two major objectives: (1) to determine the dynamics of locations of populations and industries in East Asia in the long-term, and (2) to analyze the impact of specific infrastructure projects on the regional economy at sub-national levels. The basic structure of the IDE-GSM is introduced in this article and accompanied with results of test analyses on the effects of the East West Economic Corridor on regions in Continental South East Asia. Results indicate that border costs appear to play a big role in the location choice of populations and industries, often a more important role than physical infrastructures themselves.

Chapter 2 On the usage of the measurements of geographical concentration and specialization with areal data

Measures have been developed to understand tendencies in the distribution of economic activity. The merits of these measures are in the convenience of data collection and processing. In this interim report, investigating the property of such measures to determine the geographical spread of economic activities, we summarize the merits and limitations of measures, and make clear that we must apply caution in their usage. As a first trial to access areal data, this project focus on administrative areas, not on point data and input-output data. Firm level data is not within the scope of this article. The rest of this article is organized as follows. In Section 2, we touch on the the limitations and problems associated with the measures and areal data. Specific measures are introduced in Section 3, and applied in Section 4. The conclusion summarizes the findings and discusses future work.

Chapter 5 Product Differentiation versus Geographical Differentiation: Evidence from the Pork Processing Industry in China

This chapter attempts to identify whether product differentiation or geographical differentiation is the main source of profit for firms in developing economies by employing a simple idea from the recently developed method of empirical industrial organization. Theoretically, location choice and product choice have been considered as analogues in differentiation, but in the real world, which of these strategies is chosen will result in an immense difference in firm behavior and in the development process of the industry. Development of the technique of empirical industrial organization enabled us to identify market outcomes with endogeneity. A typical case is the market outcome with differentiation, where price or product choice is endogenously determined. Our original survey contains data on market location, differences in product types, and price. The results show that product differentiation rather than geographical differentiation mitigates pressure on price competition, but 70 per cent secures geographical monopoly.

Geographical simulation analysis for logistics enhancement in Asia

This paper presents a simulation of the reduction of several components in trade cost for Asia and examines its impact on the economy. Our simulation model based on the new economic geography embraces seven sectors, including manufacturing and non-manufacturing sectors, and 1,715 regions in 18 countries/economies in Asia, in addition to the two economies of the US and the European Union. The geographical course of transactions among regions is modeled as determined based on firms’ modal choice. The model also includes estimates of some border cost measures such as tariff rates, non-tariff barriers, other border clearance costs, transshipment costs and so on. Our simulation analysis for Asia includes several scenarios involving the improvement/development of routes and the reduction of the above-mentioned border cost. We have shown that the contribution of physical and non-physical infrastructure improvements conducted together is larger than the sum of the contribution by each when conducted independently.

Modelling the Impact of Built Environment, Geographical Scales and Latent Constructs On Individual Travel Behaviour

La relación entre la estructura urbana y la movilidad ha sido estudiada desde hace más de 70 años. El entorno urbano incluye múltiples dimensiones como por ejemplo: la estructura urbana, los usos de suelo, la distribución de instalaciones diversas (comercios, escuelas y zonas de restauración, parking, etc.). Al realizar una revisión de la literatura existente en este contexto, se encuentran distintos análisis, metodologías, escalas geográficas y dimensiones, tanto de la movilidad como de la estructura urbana. En este sentido, se trata de una relación muy estudiada pero muy compleja, sobre la que no existe hasta el momento un consenso sobre qué dimensión del entorno urbano influye sobre qué dimensión de la movilidad, y cuál es la manera apropiada de representar esta relación. Con el propósito de contestar estas preguntas investigación, la presente tesis tiene los siguientes objetivos generales: (1) Contribuir al mejor entendimiento de la compleja relación estructura urbana y movilidad. y (2) Entender el rol de los atributos latentes en la relación entorno urbano y movilidad. El objetivo específico de la tesis es analizar la influencia del entorno urbano sobre dos dimensiones de la movilidad: número de viajes y tipo de tour. Vista la complejidad de la relación entorno urbano y movilidad, se pretende contribuir al mejor entendimiento de la relación a través de la utilización de 3 escalas geográficas de las variables y del análisis de la influencia de efectos inobservados en la movilidad. Para el análisis se utiliza una base de datos conformada por tres tipos de datos: (1) Una encuesta de movilidad realizada durante los años 2006 y 2007. Se obtuvo un total de 943 encuestas, en 3 barrios de Madrid: Chamberí, Pozuelo y Algete. (2) Información municipal del Instituto Nacional de Estadística: dicha información se encuentra enlazada con los orígenes y destinos de los viajes recogidos en la encuesta. Y (3) Información georeferenciada en Arc-GIS de los hogares participantes en la encuesta: la base de datos contiene información respecto a la estructura de las calles, localización de escuelas, parking, centros médicos y lugares de restauración. Se analizó la correlación entre e intra-grupos y se modelizaron 4 casos de atributos bajo la estructura ordinal logit. Posteriormente se evalúa la auto-selección a través de la estimación conjunta de las elecciones de tipo de barrio y número de viajes. La elección del tipo de barrio consta de 3 alternativas: CBD, Urban y Suburban, según la zona de residencia recogida en las encuestas. Mientras que la elección del número de viajes consta de 4 categorías ordinales: 0 viajes, 1-2 viajes, 3-4 viajes y 5 o más viajes. A partir de la mejor especificación del modelo ordinal logit. Se desarrolló un modelo joint mixed-ordinal conjunto. Los resultados indican que las variables exógenas requieren un análisis exhaustivo de correlaciones con el fin de evitar resultados sesgados. ha determinado que es importante medir los atributos del BE donde se realiza el viaje, pero también la información municipal es muy explicativa de la movilidad individual. Por tanto, la percepción de las zonas de destino a nivel municipal es considerada importante. En el contexto de la Auto-selección (self-selection) es importante modelizar conjuntamente las decisiones. La Auto-selección existe, puesto que los parámetros estimados conjuntamente son significativos. Sin embargo, sólo ciertos atributos del entorno urbano son igualmente importantes sobre la elección de la zona de residencia y frecuencia de viajes. Para analizar la Propensión al Viaje, se desarrolló un modelo híbrido, formado por: una variable latente, un indicador y un modelo de elección discreta. La variable latente se denomina “Propensión al Viaje”, cuyo indicador en ecuación de medida es el número de viajes; la elección discreta es el tipo de tour. El modelo de elección consiste en 5 alternativas, según la jerarquía de actividades establecida en la tesis: HOME, no realiza viajes durante el día de estudio, HWH tour cuya actividad principal es el trabajo o estudios, y no se realizan paradas intermedias; HWHs tour si el individuo reaiza paradas intermedias; HOH tour cuya actividad principal es distinta a trabajo y estudios, y no se realizan paradas intermedias; HOHs donde se realizan paradas intermedias. Para llegar a la mejor especificación del modelo, se realizó un trabajo importante considerando diferentes estructuras de modelos y tres tipos de estimaciones. De tal manera, se obtuvieron parámetros consistentes y eficientes. Los resultados muestran que la modelización de los tours, representa una ventaja sobre la modelización de los viajes, puesto que supera las limitaciones de espacio y tiempo, enlazando los viajes realizados por la misma persona en el día de estudio. La propensión al viaje (PT) existe y es específica para cada tipo de tour. Los parámetros estimados en el modelo híbrido resultaron significativos y distintos para cada alternativa de tipo de tour. Por último, en la tesis se verifica que los modelos híbridos representan una mejora sobre los modelos tradicionales de elección discreta, dando como resultado parámetros consistentes y más robustos. En cuanto a políticas de transporte, se ha demostrado que los atributos del entorno urbano son más importantes que los LOS (Level of Service) en la generación de tours multi-etapas. la presente tesis representa el primer análisis empírico de la relación entre los tipos de tours y la propensión al viaje. El concepto Propensity to Travel ha sido desarrollado exclusivamente para la tesis. Igualmente, el desarrollo de un modelo conjunto RC-Number of trips basado en tres escalas de medida representa innovación en cuanto a la comparación de las escalas geográficas, que no había sido hecha en la modelización de la self-selection. The relationship between built environment (BE) and travel behaviour (TB) has been studied in a number of cases, using several methods - aggregate and disaggregate approaches - and different focuses – trip frequency, automobile use, and vehicle miles travelled and so on. Definitely, travel is generated by the need to undertake activities and obtain services, and there is a general consensus that urban components affect TB. However researches are still needed to better understand which components of the travel behaviour are affected most and by which of the urban components. In order to fill the gap in the research, the present dissertation faced two main objectives: (1) To contribute to the better understanding of the relationship between travel demand and urban environment. And (2) To develop an econometric model for estimating travel demand with urban environment attributes. With this purpose, the present thesis faced an exhaustive research and computation of land-use variables in order to find the best representation of BE for modelling trip frequency. In particular two empirical analyses are carried out: 1. Estimation of three dimensions of travel demand using dimensions of urban environment. We compare different travel dimensions and geographical scales, and we measure self-selection contribution following the joint models. 2. Develop a hybrid model, integrated latent variable and discrete choice model. The implementation of hybrid models is new in the analysis of land-use and travel behaviour. BE and TB explicitly interact and allow richness information about a specific individual decision process For all empirical analysis is used a data-base from a survey conducted in 2006 and 2007 in Madrid. Spatial attributes describing neighbourhood environment are derived from different data sources: National Institute of Statistics-INE (Administrative: municipality and district) and GIS (circular units). INE provides raw data for such spatial units as: municipality and district. The construction of census units is trivial as the census bureau provides tables that readily define districts and municipalities. The construction of circular units requires us to determine the radius and associate the spatial information to our households. The first empirical part analyzes trip frequency by applying an ordered logit model. In this part is studied the effect of socio-economic, transport and land use characteristics on two travel dimensions: trip frequency and type of tour. In particular the land use is defined in terms of type of neighbourhoods and types of dwellers. Three neighbourhood representations are explored, and described three for constructing neighbourhood attributes. In particular administrative units are examined to represent neighbourhood and circular – unit representation. Ordered logit models are applied, while ordinal logit models are well-known, an intensive work for constructing a spatial attributes was carried out. On the other hand, the second empirical analysis consists of the development of an innovative econometric model that considers a latent variable called “propensity to travel”, and choice model is the choice of type of tour. The first two specifications of ordinal models help to estimate this latent variable. The latent variable is unobserved but the manifestation is called “indicators”, then the probability of choosing an alternative of tour is conditional to the probability of latent variable and type of tour. Since latent variable is unknown we fit the integral over its distribution. Four “sets of best variables” are specified, following the specification obtained from the correlation analysis. The results evidence that the relative importance of SE variables versus BE variables depends on how BE variables are measured. We found that each of these three spatial scales has its intangible qualities and drawbacks. Spatial scales play an important role on predicting travel demand due to the variability in measures at trip origin/destinations within the same administrative unit (municipality, district and so on). Larger units will produce less variation in data; but it does not affect certain variables, such as public transport supply, that are more significant at municipality level. By contrast, land-use measures are more efficient at district level. Self-selection in this context, is weak. Thus, the influence of BE attributes is true. The results of the hybrid model show that unobserved factors affect the choice of tour complexity. The latent variable used in this model is propensity to travel that is explained by socioeconomic aspects and neighbourhood attributes. The results show that neighbourhood attributes have indeed a significant impact on the choice of the type of tours either directly and through the propensity to travel. The propensity to travel has a different impact depending on the structure of each tour and increases the probability of choosing more complex tours, such as tours with many intermediate stops. The integration of choice and latent variable model shows that omitting important perception and attitudes leads to inconsistent estimates. The results also indicate that goodness of fit improves by adding the latent variable in both sequential and simultaneous estimation. There are significant differences in the sensitivity to the latent variable across alternatives. In general, as expected, the hybrid models show a major improvement into the goodness of fit of the model, compared to a classical discrete choice model that does not incorporate latent effects. The integrated model leads to a more detailed analysis of the behavioural process. Summarizing, the effect that built environment characteristics on trip frequency studied is deeply analyzed. In particular we tried to better understand how land use characteristics can be defined and measured and which of these measures do have really an impact on trip frequency. We also tried to test the superiority of HCM on this field. We can concluded that HCM shows a major improvement into the goodness of fit of the model, compared to classical discrete choice model that does not incorporate latent effects. And consequently, the application of HCM shows the importance of LV on the decision of tour complexity. People are more elastic to built environment attributes than level of services. Thus, policy implications must take place to develop more mixed areas, work-places in combination with commercial retails.

MIRACLE’s Ad-Hoc and Geographical IR Approaches for CLEF 2006

This paper presents the 2006 Miracle team’s approaches to the Ad-Hoc and Geographical Information Retrieval tasks. A first set of runs was obtained using a set of basic components. Then, by putting together special combinations of these runs, an extended set was obtained. With respect to previous campaigns some improvements have been introduced in our system: an entity recognition prototype is integrated in our tokenization scheme, and the performance of our indexing and retrieval engine has been improved. For GeoCLEF, we tested retrieving using geo-entity and textual references separately, and then combining them with different approaches.