A model of osteoporosis impact in Switzerland 2000-2020

The aim of our study was to develop a modeling framework suitable to quantify the incidence, absolute number and economic impact of osteoporosis-attributable hip, vertebral and distal forearm fractures, with a particular focus on change over time, and with application to the situation in Switzerland from 2000 to 2020. A Markov process model was developed and analyzed by Monte Carlo simulation. A demographic scenario provided by the Swiss Federal Statistical Office and various Swiss and international data sources were used as model inputs. Demographic and epidemiologic input parameters were reproduced correctly, confirming the internal validity of the model. The proportion of the Swiss population aged 50 years or over will rise from 33.3% in 2000 to 41.3% in 2020. At the total population level, osteoporosis-attributable incidence will rise from 1.16 to 1.54 per 1,000 person-years in the case of hip fracture, from 3.28 to 4.18 per 1,000 person-years in the case of radiographic vertebral fracture, and from 0.59 to 0.70 per 1,000 person-years in the case of distal forearm fracture. Osteoporosis-attributable hip fracture numbers will rise from 8,375 to 11,353, vertebral fracture numbers will rise from 23,584 to 30,883, and distal forearm fracture numbers will rise from 4,209 to 5,186. Population-level osteoporosis-related direct medical inpatient costs per year will rise from 713.4 million Swiss francs (CHF) to CHF946.2 million. These figures correspond to 1.6% and 2.2% of Swiss health care expenditures in 2000. The modeling framework described can be applied to a wide variety of settings. It can be used to assess the impact of new prevention, diagnostic and treatment strategies. In Switzerland incidences of osteoporotic hip, vertebral and distal forearm fracture will rise by 33%, 27%, and 19%, respectively, between 2000 and 2020, if current prevention and treatment patterns are maintained. Corresponding absolute fracture numbers will rise by 36%, 31%, and 23%. Related direct medical inpatient costs are predicted to increase by 33%; however, this estimate is subject to uncertainty due to limited availability of input data.

Risk of Second Malignant Neoplasms Following Proton Arc Therapy and Volumetric Modulated Arc Therapy for Prostate Cancer

The risk of second malignant neoplasms (SMNs) following prostate radiotherapy is a concern due to the large population of survivors and decreasing age at diagnosis. It is known that parallel-opposed beam proton therapy carries a lower risk than photon IMRT. However, a comparison of SMN risk following proton and photon arc therapies has not previously been reported. The purpose of this study was to predict the ratio of excess relative risk (RRR) of SMN incidence following proton arc therapy to that after volumetric modulated arc therapy (VMAT). Additionally, we investigated the impact of margin size and the effect of risk-minimized proton beam weighting on predicted RRR. Physician-approved treatment plans were created for both modalities for three patients. Therapeutic dose was obtained with differential dose-volume histograms from the treatment planning system, and stray dose was estimated from the literature or calculated with Monte Carlo simulations. Then, various risk models were applied to the total dose. Additional treatment plans were also investigated with varying margin size and risk-minimized proton beam weighting. The mean RRR ranged from 0.74 to 0.99, depending on risk model. The additional treatment plans revealed that the RRR remained approximately constant with varying margin size, and that the predicted RRR was reduced by 12% using a risk-minimized proton arc therapy planning technique. In conclusion, proton arc therapy was found to provide an advantage over VMAT in regard to predicted risk of SMN following prostate radiotherapy. This advantage was independent of margin size and was amplified with risk-optimized proton beam weighting.

Prophylactic mastectomy and oophorectomy for women at risk of breast and ovarian cancer: Incorporating preferences in a decision analysis

The discoveries of the BRCA1 and BRCA2 genes have made it possible for women of families with hereditary breast/ovarian cancer to determine if they carry cancer-predisposing genetic mutations. Women with germline mutations have significantly higher probabilities of developing both cancers than the general population. Since the presence of a BRCA1 or BRCA2 mutation does not guarantee future cancer development, the appropriate course of action remains uncertain for these women. Prophylactic mastectomy and oophorectomy remain controversial since the underlying premise for surgical intervention is based more upon reduction in the estimated risk of cancer than on actual evidence of clinical benefit. Issues that are incorporated in a woman's decision making process include quality of life without breasts, ovaries, attitudes toward possible surgical morbidity as well as a remaining risk of future development of breast/ovarian cancer despite prophylactic surgery. The incorporation of patient preferences into decision analysis models can determine the quality-adjusted survival of different prophylactic approaches to breast/ovarian cancer prevention. Monte Carlo simulation was conducted on 4 separate decision models representing prophylactic oophorectomy, prophylactic mastectomy, prophylactic oophorectomy/mastectomy and screening. The use of 3 separate preference assessment methods across different populations of women allows researchers to determine how quality adjusted survival varies according to clinical strategy, method of preference assessment and the population from which preferences are assessed. ^

A multivariate frailty model for disease recurrences and survival

A multivariate frailty hazard model is developed for joint-modeling of three correlated time-to-event outcomes: (1) local recurrence, (2) distant recurrence, and (3) overall survival. The term frailty is introduced to model population heterogeneity. The dependence is modeled by conditioning on a shared frailty that is included in the three hazard functions. Independent variables can be included in the model as covariates. The Markov chain Monte Carlo methods are used to estimate the posterior distributions of model parameters. The algorithm used in present application is the hybrid Metropolis-Hastings algorithm, which simultaneously updates all parameters with evaluations of gradient of log posterior density. The performance of this approach is examined based on simulation studies using Exponential and Weibull distributions. We apply the proposed methods to a study of patients with soft tissue sarcoma, which motivated this research. Our results indicate that patients with chemotherapy had better overall survival with hazard ratio of 0.242 (95% CI: 0.094 - 0.564) and lower risk of distant recurrence with hazard ratio of 0.636 (95% CI: 0.487 - 0.860), but not significantly better in local recurrence with hazard ratio of 0.799 (95% CI: 0.575 - 1.054). The advantages and limitations of the proposed models, and future research directions are discussed. ^

A Bayesian analysis for spatial processes with application to mapping

In geographical epidemiology, maps of disease rates and disease risk provide a spatial perspective for researching disease etiology. For rare diseases or when the population base is small, the rate and risk estimates may be unstable. Empirical Bayesian (EB) methods have been used to spatially smooth the estimates by permitting an area estimate to "borrow strength" from its neighbors. Such EB methods include the use of a Gamma model, of a James-Stein estimator, and of a conditional autoregressive (CAR) process. A fully Bayesian analysis of the CAR process is proposed. One advantage of this fully Bayesian analysis is that it can be implemented simply by using repeated sampling from the posterior densities. Use of a Markov chain Monte Carlo technique such as Gibbs sampler was not necessary. Direct resampling from the posterior densities provides exact small sample inferences instead of the approximate asymptotic analyses of maximum likelihood methods (Clayton & Kaldor, 1987). Further, the proposed CAR model provides for covariates to be included in the model. A simulation demonstrates the effect of sample size on the fully Bayesian analysis of the CAR process. The methods are applied to lip cancer data from Scotland, and the results are compared. ^

Bayesian and survival model for tumor relapse status and disease-specific survival, with applications to breast cancer

Breast cancer is the most common non-skin cancer and the second leading cause of cancer-related death in women in the United States. Studies on ipsilateral breast tumor relapse (IBTR) status and disease-specific survival will help guide clinic treatment and predict patient prognosis.^ After breast conservation therapy, patients with breast cancer may experience breast tumor relapse. This relapse is classified into two distinct types: true local recurrence (TR) and new ipsilateral primary tumor (NP). However, the methods used to classify the relapse types are imperfect and are prone to misclassification. In addition, some observed survival data (e.g., time to relapse and time from relapse to death)are strongly correlated with relapse types. The first part of this dissertation presents a Bayesian approach to (1) modeling the potentially misclassified relapse status and the correlated survival information, (2) estimating the sensitivity and specificity of the diagnostic methods, and (3) quantify the covariate effects on event probabilities. A shared frailty was used to account for the within-subject correlation between survival times. The inference was conducted using a Bayesian framework via Markov Chain Monte Carlo simulation implemented in softwareWinBUGS. Simulation was used to validate the Bayesian method and assess its frequentist properties. The new model has two important innovations: (1) it utilizes the additional survival times correlated with the relapse status to improve the parameter estimation, and (2) it provides tools to address the correlation between the two diagnostic methods conditional to the true relapse types.^ Prediction of patients at highest risk for IBTR after local excision of ductal carcinoma in situ (DCIS) remains a clinical concern. The goals of the second part of this dissertation were to evaluate a published nomogram from Memorial Sloan-Kettering Cancer Center, to determine the risk of IBTR in patients with DCIS treated with local excision, and to determine whether there is a subset of patients at low risk of IBTR. Patients who had undergone local excision from 1990 through 2007 at MD Anderson Cancer Center with a final diagnosis of DCIS (n=794) were included in this part. Clinicopathologic factors and the performance of the Memorial Sloan-Kettering Cancer Center nomogram for prediction of IBTR were assessed for 734 patients with complete data. Nomogram for prediction of 5- and 10-year IBTR probabilities were found to demonstrate imperfect calibration and discrimination, with an area under the receiver operating characteristic curve of .63 and a concordance index of .63. In conclusion, predictive models for IBTR in DCIS patients treated with local excision are imperfect. Our current ability to accurately predict recurrence based on clinical parameters is limited.^ The American Joint Committee on Cancer (AJCC) staging of breast cancer is widely used to determine prognosis, yet survival within each AJCC stage shows wide variation and remains unpredictable. For the third part of this dissertation, biologic markers were hypothesized to be responsible for some of this variation, and the addition of biologic markers to current AJCC staging were examined for possibly provide improved prognostication. The initial cohort included patients treated with surgery as first intervention at MDACC from 1997 to 2006. Cox proportional hazards models were used to create prognostic scoring systems. AJCC pathologic staging parameters and biologic tumor markers were investigated to devise the scoring systems. Surveillance Epidemiology and End Results (SEER) data was used as the external cohort to validate the scoring systems. Binary indicators for pathologic stage (PS), estrogen receptor status (E), and tumor grade (G) were summed to create PS+EG scoring systems devised to predict 5-year patient outcomes. These scoring systems facilitated separation of the study population into more refined subgroups than the current AJCC staging system. The ability of the PS+EG score to stratify outcomes was confirmed in both internal and external validation cohorts. The current study proposes and validates a new staging system by incorporating tumor grade and ER status into current AJCC staging. We recommend that biologic markers be incorporating into revised versions of the AJCC staging system for patients receiving surgery as the first intervention.^ Chapter 1 focuses on developing a Bayesian method to solve misclassified relapse status and application to breast cancer data. Chapter 2 focuses on evaluation of a breast cancer nomogram for predicting risk of IBTR in patients with DCIS after local excision gives the statement of the problem in the clinical research. Chapter 3 focuses on validation of a novel staging system for disease-specific survival in patients with breast cancer treated with surgery as the first intervention. ^

Orthogonal MCMC algorithms

Monte Carlo (MC) methods are widely used in signal processing, machine learning and stochastic optimization. A well-known class of MC methods are Markov Chain Monte Carlo (MCMC) algorithms. In this work, we introduce a novel parallel interacting MCMC scheme, where the parallel chains share information using another MCMC technique working on the entire population of current states. These parallel ?vertical? chains are led by random-walk proposals, whereas the ?horizontal? MCMC uses a independent proposal, which can be easily adapted by making use of all the generated samples. Numerical results show the advantages of the proposed sampling scheme in terms of mean absolute error, as well as robustness w.r.t. to initial values and parameter choice.

Methodologies for Collision Risk Computation = Metodologías para Cálculo de Riesgo de Colisión

Esta tesis aborda metodologías para el cálculo de riesgo de colisión de satélites. La minimización del riesgo de colisión se debe abordar desde dos puntos de vista distintos. Desde el punto de vista operacional, es necesario filtrar los objetos que pueden presentar un encuentro entre todos los objetos que comparten el espacio con un satélite operacional. Puesto que las órbitas, del objeto operacional y del objeto envuelto en la colisión, no se conocen perfectamente, la geometría del encuentro y el riesgo de colisión deben ser evaluados. De acuerdo con dicha geometría o riesgo, una maniobra evasiva puede ser necesaria para evitar la colisión. Dichas maniobras implican un consumo de combustible que impacta en la capacidad de mantenimiento orbital y por tanto de la visa útil del satélite. Por tanto, el combustible necesario a lo largo de la vida útil de un satélite debe ser estimado en fase de diseño de la misión para una correcta definición de su vida útil, especialmente para satélites orbitando en regímenes orbitales muy poblados. Los dos aspectos, diseño de misión y aspectos operacionales en relación con el riesgo de colisión están abordados en esta tesis y se resumen en la Figura 3. En relación con los aspectos relacionados con el diseño de misión (parte inferior de la figura), es necesario evaluar estadísticamente las características de de la población espacial y las teorías que permiten calcular el número medio de eventos encontrados por una misión y su capacidad de reducir riesgo de colisión. Estos dos aspectos definen los procedimientos más apropiados para reducir el riesgo de colisión en fase operacional. Este aspecto es abordado, comenzando por la teoría descrita en [Sánchez-Ortiz, 2006]T.14 e implementada por el autor de esta tesis en la herramienta ARES [Sánchez-Ortiz, 2004b]T.15 proporcionada por ESA para la evaluación de estrategias de evitación de colisión. Esta teoría es extendida en esta tesis para considerar las características de los datos orbitales disponibles en las fases operacionales de un satélite (sección 4.3.3). Además, esta teoría se ha extendido para considerar riesgo máximo de colisión cuando la incertidumbre de las órbitas de objetos catalogados no es conocida (como se da el caso para los TLE), y en el caso de querer sólo considerar riesgo de colisión catastrófico (sección 4.3.2.3). Dichas mejoras se han incluido en la nueva versión de ARES [Domínguez-González and Sánchez-Ortiz, 2012b]T.12 puesta a disposición a través de [SDUP,2014]R.60. En fase operacional, los catálogos que proporcionan datos orbitales de los objetos espaciales, son procesados rutinariamente, para identificar posibles encuentros que se analizan en base a algoritmos de cálculo de riesgo de colisión para proponer maniobras de evasión. Actualmente existe una única fuente de datos públicos, el catálogo TLE (de sus siglas en inglés, Two Line Elements). Además, el Joint Space Operation Center (JSpOC) Americano proporciona mensajes con alertas de colisión (CSM) cuando el sistema de vigilancia americano identifica un posible encuentro. En función de los datos usados en fase operacional (TLE o CSM), la estrategia de evitación puede ser diferente debido a las características de dicha información. Es preciso conocer las principales características de los datos disponibles (respecto a la precisión de los datos orbitales) para estimar los posibles eventos de colisión encontrados por un satélite a lo largo de su vida útil. En caso de los TLE, cuya precisión orbital no es proporcionada, la información de precisión orbital derivada de un análisis estadístico se puede usar también en el proceso operacional así como en el diseño de la misión. En caso de utilizar CSM como base de las operaciones de evitación de colisiones, se conoce la precisión orbital de los dos objetos involucrados. Estas características se han analizado en detalle, evaluando estadísticamente las características de ambos tipos de datos. Una vez concluido dicho análisis, se ha analizado el impacto de utilizar TLE o CSM en las operaciones del satélite (sección 5.1). Este análisis se ha publicado en una revista especializada [Sánchez-Ortiz, 2015b]T.3. En dicho análisis, se proporcionan recomendaciones para distintas misiones (tamaño del satélite y régimen orbital) en relación con las estrategias de evitación de colisión para reducir el riesgo de colisión de manera significativa. Por ejemplo, en el caso de un satélite en órbita heliosíncrona en régimen orbital LEO, el valor típico del ACPL que se usa de manera extendida es 10-4. Este valor no es adecuado cuando los esquemas de evitación de colisión se realizan sobre datos TLE. En este caso, la capacidad de reducción de riesgo es prácticamente nula (debido a las grandes incertidumbres de los datos TLE) incluso para tiempos cortos de predicción. Para conseguir una reducción significativa del riesgo, sería necesario usar un ACPL en torno a 10-6 o inferior, produciendo unas 10 alarmas al año por satélite (considerando predicciones a un día) o 100 alarmas al año (con predicciones a tres días). Por tanto, la principal conclusión es la falta de idoneidad de los datos TLE para el cálculo de eventos de colisión. Al contrario, usando los datos CSM, debido a su mejor precisión orbital, se puede obtener una reducción significativa del riesgo con ACPL en torno a 10-4 (considerando 3 días de predicción). Incluso 5 días de predicción pueden ser considerados con ACPL en torno a 10-5. Incluso tiempos de predicción más largos se pueden usar (7 días) con reducción del 90% del riesgo y unas 5 alarmas al año (en caso de predicciones de 5 días, el número de maniobras se mantiene en unas 2 al año). La dinámica en GEO es diferente al caso LEO y hace que el crecimiento de las incertidumbres orbitales con el tiempo de propagación sea menor. Por el contrario, las incertidumbres derivadas de la determinación orbital son peores que en LEO por las diferencias en las capacidades de observación de uno y otro régimen orbital. Además, se debe considerar que los tiempos de predicción considerados para LEO pueden no ser apropiados para el caso de un satélite GEO (puesto que tiene un periodo orbital mayor). En este caso usando datos TLE, una reducción significativa del riesgo sólo se consigue con valores pequeños de ACPL, produciendo una alarma por año cuando los eventos de colisión se predicen a un día vista (tiempo muy corto para implementar maniobras de evitación de colisión).Valores más adecuados de ACPL se encuentran entre 5•10-8 y 10-7, muy por debajo de los valores usados en las operaciones actuales de la mayoría de las misiones GEO (de nuevo, no se recomienda en este régimen orbital basar las estrategias de evitación de colisión en TLE). Los datos CSM permiten una reducción de riesgo apropiada con ACPL entre 10-5 y 10-4 con tiempos de predicción cortos y medios (10-5 se recomienda para predicciones a 5 o 7 días). El número de maniobras realizadas sería una en 10 años de misión. Se debe notar que estos cálculos están realizados para un satélite de unos 2 metros de radio. En el futuro, otros sistemas de vigilancia espacial (como el programa SSA de la ESA), proporcionarán catálogos adicionales de objetos espaciales con el objetivo de reducir el riesgo de colisión de los satélites. Para definir dichos sistemas de vigilancia, es necesario identificar las prestaciones del catalogo en función de la reducción de riesgo que se pretende conseguir. Las características del catálogo que afectan principalmente a dicha capacidad son la cobertura (número de objetos incluidos en el catalogo, limitado principalmente por el tamaño mínimo de los objetos en función de las limitaciones de los sensores utilizados) y la precisión de los datos orbitales (derivada de las prestaciones de los sensores en relación con la precisión de las medidas y la capacidad de re-observación de los objetos). El resultado de dicho análisis (sección 5.2) se ha publicado en una revista especializada [Sánchez-Ortiz, 2015a]T.2. Este análisis no estaba inicialmente previsto durante la tesis, y permite mostrar como la teoría descrita en esta tesis, inicialmente definida para facilitar el diseño de misiones (parte superior de la figura 1) se ha extendido y se puede aplicar para otros propósitos como el dimensionado de un sistema de vigilancia espacial (parte inferior de la figura 1). La principal diferencia de los dos análisis se basa en considerar las capacidades de catalogación (precisión y tamaño de objetos observados) como una variable a modificar en el caso de un diseño de un sistema de vigilancia), siendo fijas en el caso de un diseño de misión. En el caso de las salidas generadas en el análisis, todos los aspectos calculados en un análisis estadístico de riesgo de colisión son importantes para diseño de misión (con el objetivo de calcular la estrategia de evitación y la cantidad de combustible a utilizar), mientras que en el caso de un diseño de un sistema de vigilancia, los aspectos más importantes son el número de maniobras y falsas alarmas (fiabilidad del sistema) y la capacidad de reducción de riesgo (efectividad del sistema). Adicionalmente, un sistema de vigilancia espacial debe ser caracterizado por su capacidad de evitar colisiones catastróficas (evitando así in incremento dramático de la población de basura espacial), mientras que el diseño de una misión debe considerar todo tipo de encuentros, puesto que un operador está interesado en evitar tanto las colisiones catastróficas como las letales. Del análisis de las prestaciones (tamaño de objetos a catalogar y precisión orbital) requeridas a un sistema de vigilancia espacial se concluye que ambos aspectos han de ser fijados de manera diferente para los distintos regímenes orbitales. En el caso de LEO se hace necesario observar objetos de hasta 5cm de radio, mientras que en GEO se rebaja este requisito hasta los 100 cm para cubrir las colisiones catastróficas. La razón principal para esta diferencia viene de las diferentes velocidades relativas entre los objetos en ambos regímenes orbitales. En relación con la precisión orbital, ésta ha de ser muy buena en LEO para poder reducir el número de falsas alarmas, mientras que en regímenes orbitales más altos se pueden considerar precisiones medias. En relación con los aspectos operaciones de la determinación de riesgo de colisión, existen varios algoritmos de cálculo de riesgo entre dos objetos espaciales. La Figura 2 proporciona un resumen de los casos en cuanto a algoritmos de cálculo de riesgo de colisión y como se abordan en esta tesis. Normalmente se consideran objetos esféricos para simplificar el cálculo de riesgo (caso A). Este caso está ampliamente abordado en la literatura y no se analiza en detalle en esta tesis. Un caso de ejemplo se proporciona en la sección 4.2. Considerar la forma real de los objetos (caso B) permite calcular el riesgo de una manera más precisa. Un nuevo algoritmo es definido en esta tesis para calcular el riesgo de colisión cuando al menos uno de los objetos se considera complejo (sección 4.4.2). Dicho algoritmo permite calcular el riesgo de colisión para objetos formados por un conjunto de cajas, y se ha presentado en varias conferencias internacionales. Para evaluar las prestaciones de dicho algoritmo, sus resultados se han comparado con un análisis de Monte Carlo que se ha definido para considerar colisiones entre cajas de manera adecuada (sección 4.1.2.3), pues la búsqueda de colisiones simples aplicables para objetos esféricos no es aplicable a este caso. Este análisis de Monte Carlo se considera la verdad a la hora de calcular los resultados del algoritmos, dicha comparativa se presenta en la sección 4.4.4. En el caso de satélites que no se pueden considerar esféricos, el uso de un modelo de la geometría del satélite permite descartar eventos que no son colisiones reales o estimar con mayor precisión el riesgo asociado a un evento. El uso de estos algoritmos con geometrías complejas es más relevante para objetos de dimensiones grandes debido a las prestaciones de precisión orbital actuales. En el futuro, si los sistemas de vigilancia mejoran y las órbitas son conocidas con mayor precisión, la importancia de considerar la geometría real de los satélites será cada vez más relevante. La sección 5.4 presenta un ejemplo para un sistema de grandes dimensiones (satélite con un tether). Adicionalmente, si los dos objetos involucrados en la colisión tienen velocidad relativa baja (y geometría simple, Caso C en la Figura 2), la mayor parte de los algoritmos no son aplicables requiriendo implementaciones dedicadas para este caso particular. En esta tesis, uno de estos algoritmos presentado en la literatura [Patera, 2001]R.26 se ha analizado para determinar su idoneidad en distintos tipos de eventos (sección 4.5). La evaluación frete a un análisis de Monte Carlo se proporciona en la sección 4.5.2. Tras este análisis, se ha considerado adecuado para abordar las colisiones de baja velocidad. En particular, se ha concluido que el uso de algoritmos dedicados para baja velocidad son necesarios en función del tamaño del volumen de colisión proyectado en el plano de encuentro (B-plane) y del tamaño de la incertidumbre asociada al vector posición entre los dos objetos. Para incertidumbres grandes, estos algoritmos se hacen más necesarios pues la duración del intervalo en que los elipsoides de error de los dos objetos pueden intersecar es mayor. Dicho algoritmo se ha probado integrando el algoritmo de colisión para objetos con geometrías complejas. El resultado de dicho análisis muestra que este algoritmo puede ser extendido fácilmente para considerar diferentes tipos de algoritmos de cálculo de riesgo de colisión (sección 4.5.3). Ambos algoritmos, junto con el método Monte Carlo para geometrías complejas, se han implementado en la herramienta operacional de la ESA CORAM, que es utilizada para evaluar el riesgo de colisión en las actividades rutinarias de los satélites operados por ESA [Sánchez-Ortiz, 2013a]T.11. Este hecho muestra el interés y relevancia de los algoritmos desarrollados para la mejora de las operaciones de los satélites. Dichos algoritmos han sido presentados en varias conferencias internacionales [Sánchez-Ortiz, 2013b]T.9, [Pulido, 2014]T.7,[Grande-Olalla, 2013]T.10, [Pulido, 2014]T.5, [Sánchez-Ortiz, 2015c]T.1. ABSTRACT This document addresses methodologies for computation of the collision risk of a satellite. Two different approaches need to be considered for collision risk minimisation. On an operational basis, it is needed to perform a sieve of possible objects approaching the satellite, among all objects sharing the space with an operational satellite. As the orbits of both, satellite and the eventual collider, are not perfectly known but only estimated, the miss-encounter geometry and the actual risk of collision shall be evaluated. In the basis of the encounter geometry or the risk, an eventual manoeuvre may be required to avoid the conjunction. Those manoeuvres will be associated to a reduction in the fuel for the mission orbit maintenance, and thus, may reduce the satellite operational lifetime. Thus, avoidance manoeuvre fuel budget shall be estimated, at mission design phase, for a better estimation of mission lifetime, especially for those satellites orbiting in very populated orbital regimes. These two aspects, mission design and operational collision risk aspects, are summarised in Figure 3, and covered along this thesis. Bottom part of the figure identifies the aspects to be consider for the mission design phase (statistical characterisation of the space object population data and theory computing the mean number of events and risk reduction capability) which will define the most appropriate collision avoidance approach at mission operational phase. This part is covered in this work by starting from the theory described in [Sánchez-Ortiz, 2006]T.14 and implemented by this author in ARES tool [Sánchez-Ortiz, 2004b]T.15 provided by ESA for evaluation of collision avoidance approaches. This methodology has been now extended to account for the particular features of the available data sets in operational environment (section 4.3.3). Additionally, the formulation has been extended to allow evaluating risk computation approached when orbital uncertainty is not available (like the TLE case) and when only catastrophic collisions are subject to study (section 4.3.2.3). These improvements to the theory have been included in the new version of ESA ARES tool [Domínguez-González and Sánchez-Ortiz, 2012b]T.12 and available through [SDUP,2014]R.60. At the operation phase, the real catalogue data will be processed on a routine basis, with adequate collision risk computation algorithms to propose conjunction avoidance manoeuvre optimised for every event. The optimisation of manoeuvres in an operational basis is not approached along this document. Currently, American Two Line Element (TLE) catalogue is the only public source of data providing orbits of objects in space to identify eventual conjunction events. Additionally, Conjunction Summary Message (CSM) is provided by Joint Space Operation Center (JSpOC) when the American system identifies a possible collision among satellites and debris. Depending on the data used for collision avoidance evaluation, the conjunction avoidance approach may be different. The main features of currently available data need to be analysed (in regards to accuracy) in order to perform estimation of eventual encounters to be found along the mission lifetime. In the case of TLE, as these data is not provided with accuracy information, operational collision avoidance may be also based on statistical accuracy information as the one used in the mission design approach. This is not the case for CSM data, which includes the state vector and orbital accuracy of the two involved objects. This aspect has been analysed in detail and is depicted in the document, evaluating in statistical way the characteristics of both data sets in regards to the main aspects related to collision avoidance. Once the analysis of data set was completed, investigations on the impact of those features in the most convenient avoidance approaches have been addressed (section 5.1). This analysis is published in a peer-reviewed journal [Sánchez-Ortiz, 2015b]T.3. The analysis provides recommendations for different mission types (satellite size and orbital regime) in regards to the most appropriate collision avoidance approach for relevant risk reduction. The risk reduction capability is very much dependent on the accuracy of the catalogue utilized to identify eventual collisions. Approaches based on CSM data are recommended against the TLE based approach. Some approaches based on the maximum risk associated to envisaged encounters are demonstrated to report a very large number of events, which makes the approach not suitable for operational activities. Accepted Collision Probability Levels are recommended for the definition of the avoidance strategies for different mission types. For example for the case of a LEO satellite in the Sun-synchronous regime, the typically used ACPL value of 10-4 is not a suitable value for collision avoidance schemes based on TLE data. In this case the risk reduction capacity is almost null (due to the large uncertainties associated to TLE data sets, even for short time-to-event values). For significant reduction of risk when using TLE data, ACPL on the order of 10-6 (or lower) seems to be required, producing about 10 warnings per year and mission (if one-day ahead events are considered) or 100 warnings per year (for three-days ahead estimations). Thus, the main conclusion from these results is the lack of feasibility of TLE for a proper collision avoidance approach. On the contrary, for CSM data, and due to the better accuracy of the orbital information when compared with TLE, ACPL on the order of 10-4 allows to significantly reduce the risk. This is true for events estimated up to 3 days ahead. Even 5 days ahead events can be considered, but ACPL values down to 10-5 should be considered in such case. Even larger prediction times can be considered (7 days) for risk reduction about 90%, at the cost of larger number of warnings up to 5 events per year, when 5 days prediction allows to keep the manoeuvre rate in 2 manoeuvres per year. Dynamics of the GEO orbits is different to that in LEO, impacting on a lower increase of orbits uncertainty along time. On the contrary, uncertainties at short prediction times at this orbital regime are larger than those at LEO due to the differences in observation capabilities. Additionally, it has to be accounted that short prediction times feasible at LEO may not be appropriate for a GEO mission due to the orbital period being much larger at this regime. In the case of TLE data sets, significant reduction of risk is only achieved for small ACPL values, producing about a warning event per year if warnings are raised one day in advance to the event (too short for any reaction to be considered). Suitable ACPL values would lay in between 5•10-8 and 10-7, well below the normal values used in current operations for most of the GEO missions (TLE-based strategies for collision avoidance at this regime are not recommended). On the contrary, CSM data allows a good reduction of risk with ACPL in between 10-5 and 10-4 for short and medium prediction times. 10-5 is recommended for prediction times of five or seven days. The number of events raised for a suitable warning time of seven days would be about one in a 10-year mission. It must be noted, that these results are associated to a 2 m radius spacecraft, impact of the satellite size are also analysed within the thesis. In the future, other Space Situational Awareness Systems (SSA, ESA program) may provide additional catalogues of objects in space with the aim of reducing the risk. It is needed to investigate which are the required performances of those catalogues for allowing such risk reduction. The main performance aspects are coverage (objects included in the catalogue, mainly limited by a minimum object size derived from sensor performances) and the accuracy of the orbital data to accurately evaluate the conjunctions (derived from sensor performance in regards to object observation frequency and accuracy). The results of these investigations (section 5.2) are published in a peer-reviewed journal [Sánchez-Ortiz, 2015a]T.2. This aspect was not initially foreseen as objective of the thesis, but it shows how the theory described in the thesis, initially defined for mission design in regards to avoidance manoeuvre fuel allocation (upper part of figure 1), is extended and serves for additional purposes as dimensioning a Space Surveillance and Tracking (SST) system (bottom part of figure below). The main difference between the two approaches is the consideration of the catalogue features as part of the theory which are not modified (for the satellite mission design case) instead of being an input for the analysis (in the case of the SST design). In regards to the outputs, all the features computed by the statistical conjunction analysis are of importance for mission design (with the objective of proper global avoidance strategy definition and fuel allocation), whereas for the case of SST design, the most relevant aspects are the manoeuvre and false alarm rates (defining a reliable system) and the Risk Reduction capability (driving the effectiveness of the system). In regards to the methodology for computing the risk, the SST system shall be driven by the capacity of providing the means to avoid catastrophic conjunction events (avoiding the dramatic increase of the population), whereas the satellite mission design should consider all type of encounters, as the operator is interested on avoiding both lethal and catastrophic collisions. From the analysis of the SST features (object coverage and orbital uncertainty) for a reliable system, it is concluded that those two characteristics are to be imposed differently for the different orbital regimes, as the population level is different depending on the orbit type. Coverage values range from 5 cm for very populated LEO regime up to 100 cm in the case of GEO region. The difference on this requirement derives mainly from the relative velocity of the encounters at those regimes. Regarding the orbital knowledge of the catalogues, very accurate information is required for objects in the LEO region in order to limit the number of false alarms, whereas intermediate orbital accuracy can be considered for higher orbital regimes. In regards to the operational collision avoidance approaches, several collision risk algorithms are used for evaluation of collision risk of two pair of objects. Figure 2 provides a summary of the different collision risk algorithm cases and indicates how they are covered along this document. The typical case with high relative velocity is well covered in literature for the case of spherical objects (case A), with a large number of available algorithms, that are not analysed in detailed in this work. Only a sample case is provided in section 4.2. If complex geometries are considered (Case B), a more realistic risk evaluation can be computed. New approach for the evaluation of risk in the case of complex geometries is presented in this thesis (section 4.4.2), and it has been presented in several international conferences. The developed algorithm allows evaluating the risk for complex objects formed by a set of boxes. A dedicated Monte Carlo method has also been described (section 4.1.2.3) and implemented to allow the evaluation of the actual collisions among a large number of simulation shots. This Monte Carlo runs are considered the truth for comparison of the algorithm results (section 4.4.4). For spacecrafts that cannot be considered as spheres, the consideration of the real geometry of the objects may allow to discard events which are not real conjunctions, or estimate with larger reliability the risk associated to the event. This is of particular importance for the case of large spacecrafts as the uncertainty in positions of actual catalogues does not reach small values to make a difference for the case of objects below meter size. As the tracking systems improve and the orbits of catalogued objects are known more precisely, the importance of considering actual shapes of the objects will become more relevant. The particular case of a very large system (as a tethered satellite) is analysed in section 5.4. Additionally, if the two colliding objects have low relative velocity (and simple geometries, case C in figure above), the most common collision risk algorithms fail and adequate theories need to be applied. In this document, a low relative velocity algorithm presented in the literature [Patera, 2001]R.26 is described and evaluated (section 4.5). Evaluation through comparison with Monte Carlo approach is provided in section 4.5.2. The main conclusion of this analysis is the suitability of this algorithm for the most common encounter characteristics, and thus it is selected as adequate for collision risk estimation. Its performances are evaluated in order to characterise when it can be safely used for a large variety of encounter characteristics. In particular, it is found that the need of using dedicated algorithms depend on both the size of collision volume in the B-plane and the miss-distance uncertainty. For large uncertainties, the need of such algorithms is more relevant since for small uncertainties the encounter duration where the covariance ellipsoids intersect is smaller. Additionally, its application for the case of complex satellite geometries is assessed (case D in figure above) by integrating the developed algorithm in this thesis with Patera’s formulation for low relative velocity encounters. The results of this analysis show that the algorithm can be easily extended for collision risk estimation process suitable for complex geometry objects (section 4.5.3). The two algorithms, together with the Monte Carlo method, have been implemented in the operational tool CORAM for ESA which is used for the evaluation of collision risk of ESA operated missions, [Sánchez-Ortiz, 2013a]T.11. This fact shows the interest and relevance of the developed algorithms for improvement of satellite operations. The algorithms have been presented in several international conferences, [Sánchez-Ortiz, 2013b]T.9, [Pulido, 2014]T.7,[Grande-Olalla, 2013]T.10, [Pulido, 2014]T.5, [Sánchez-Ortiz, 2015c]T.1.

Desarrollo de un Modelo de Gestión de Riesgos Operacionales basado en las Directrices del Comité de Basilea

La presente investigación tiene como objetivo principal diseñar un Modelo de Gestión de Riesgos Operacionales (MGRO) según las Directrices de los Acuerdos II y III del Comité de Supervisión Bancaria de Basilea del Banco de Pagos Internacionales (CSBB-BPI). Se considera importante realizar un estudio sobre este tema dado que son los riesgos operacionales (OpR) los responsables en gran medida de las últimas crisis financieras mundiales y por la dificultad para detectarlos en las organizaciones. Se ha planteado un modelo de gestión subdividido en dos vías de influencias. La primera acoge el paradigma holístico en el que se considera que hay múltiples maneras de percibir un proceso cíclico, así como las herramientas para observar, conocer y entender el objeto o sujeto percibido. La segunda vía la representa el paradigma totalizante, en el que se obtienen datos tanto cualitativos como cuantitativos, los cuales son complementarios entre si. Por otra parte, este trabajo plantea el diseño de un programa informático de OpR Cualitativo, que ha sido diseñado para determinar la raíz de los riesgos en las organizaciones y su Valor en Riesgo Operacional (OpVaR) basado en el método del indicador básico. Aplicando el ciclo holístico al caso de estudio, se obtuvo el siguiente diseño de investigación: no experimental, univariable, transversal descriptiva, contemporánea, retrospectiva, de fuente mixta, cualitativa (fenomenológica y etnográfica) y cuantitativa (descriptiva y analítica). La toma de decisiones y recolección de información se realizó en dos fases en la unidad de estudio. En la primera se tomó en cuenta la totalidad de la empresa Corpoelec-EDELCA, en la que se presentó un universo estadístico de 4271 personas, una población de 2390 personas y una unidad de muestreo de 87 personas. Se repitió el proceso en una segunda fase, para la Central Hidroeléctrica Simón Bolívar, y se determinó un segundo universo estadístico de 300 trabajadores, una población de 191 personas y una muestra de 58 profesionales. Como fuentes de recolección de información se utilizaron fuentes primarias y secundarias. Para recabar la información primaria se realizaron observaciones directas, dos encuestas para detectar las áreas y procesos con mayor nivel de riesgos y se diseñó un cuestionario combinado con otra encuesta (ad hoc) para establecer las estimaciones de frecuencia y severidad de pérdidas operacionales. La información de fuentes secundarias se extrajo de las bases de datos de Corpoelec-EDELCA, de la IEA, del Banco Mundial, del CSBB-BPI, de la UPM y de la UC at Berkeley, entre otras. Se establecieron las distribuciones de frecuencia y de severidad de pérdidas operacionales como las variables independientes y el OpVaR como la variable dependiente. No se realizó ningún tipo de seguimiento o control a las variables bajo análisis, ya que se consideraron estas para un instante especifico y solo se determinan con la finalidad de establecer la existencia y valoración puntual de los OpR en la unidad de estudio. El análisis cualitativo planteado en el MGRO, permitió detectar que en la unidad de investigación, el 67% de los OpR detectados provienen de dos fuentes principales: procesos (32%) y eventos externos (35%). Adicionalmente, la validación del MGRO en Corpoelec-EDELCA, permitió detectar que el 63% de los OpR en la organización provienen de tres categorías principales, siendo los fraudes externos los presentes con mayor regularidad y severidad de pérdidas en la organización. La exposición al riesgo se determinó fundamentándose en la adaptación del concepto de OpVaR que generalmente se utiliza para series temporales y que en el caso de estudio presenta la primicia de aplicarlo a datos cualitativos transformados con la escala Likert. La posibilidad de utilizar distribuciones de probabilidad típicas para datos cuantitativos en distribuciones de frecuencia y severidad de pérdidas con datos de origen cualitativo fueron analizadas. Para el 64% de los OpR estudiados se obtuvo que la frecuencia tiene un comportamiento semejante al de la distribución de probabilidad de Poisson y en un 55% de los casos para la severidad de pérdidas se obtuvo a las log-normal como las distribuciones de probabilidad más comunes, con lo que se concluyó que los enfoques sugeridos por el BCBS-BIS para series de tiempo son aplicables a los datos cualitativos. Obtenidas las distribuciones de frecuencia y severidad de pérdidas, se convolucionaron estas implementando el método de Montecarlo, con lo que se obtuvieron los enfoques de distribuciones de pérdidas (LDA) para cada uno de los OpR. El OpVaR se dedujo como lo sugiere el CSBB-BPI del percentil 99,9 o 99% de cada una de las LDA, obteniéndose que los OpR presentan un comportamiento similar al sistema financiero, resultando como los de mayor peligrosidad los que se ubican con baja frecuencia y alto impacto, por su dificultad para ser detectados y monitoreados. Finalmente, se considera que el MGRO permitirá a los agentes del mercado y sus grupos de interés conocer con efectividad, fiabilidad y eficiencia el status de sus entidades, lo que reducirá la incertidumbre de sus inversiones y les permitirá establecer una nueva cultura de gestión en sus organizaciones. ABSTRACT This research has as main objective the design of a Model for Operational Risk Management (MORM) according to the guidelines of Accords II and III of the Basel Committee on Banking Supervision of the Bank for International Settlements (BCBS- BIS). It is considered important to conduct a study on this issue since operational risks (OpR) are largely responsible for the recent world financial crisis and due to the difficulty in detecting them in organizations. A management model has been designed which is divided into two way of influences. The first supports the holistic paradigm in which it is considered that there are multiple ways of perceiving a cyclical process and contains the tools to observe, know and understand the subject or object perceived. The second way is the totalizing paradigm, in which both qualitative and quantitative data are obtained, which are complementary to each other. Moreover, this paper presents the design of qualitative OpR software which is designed to determine the root of risks in organizations and their Operational Value at Risk (OpVaR) based on the basic indicator approach. Applying the holistic cycle to the case study, the following research design was obtained: non- experimental, univariate, descriptive cross-sectional, contemporary, retrospective, mixed-source, qualitative (phenomenological and ethnographic) and quantitative (descriptive and analytical). Decision making and data collection was conducted in two phases in the study unit. The first took into account the totality of the Corpoelec-EDELCA company, which presented a statistical universe of 4271 individuals, a population of 2390 individuals and a sampling unit of 87 individuals. The process was repeated in a second phase to the Simon Bolivar Hydroelectric Power Plant, and a second statistical universe of 300 workers, a population of 191 people and a sample of 58 professionals was determined. As sources of information gathering primary and secondary sources were used. To obtain the primary information direct observations were conducted and two surveys to identify the areas and processes with higher risks were designed. A questionnaire was combined with an ad hoc survey to establish estimates of frequency and severity of operational losses was also considered. The secondary information was extracted from the databases of Corpoelec-EDELCA, IEA, the World Bank, the BCBS-BIS, UPM and UC at Berkeley, among others. The operational loss frequency distributions and the operational loss severity distributions were established as the independent variables and OpVaR as the dependent variable. No monitoring or control of the variables under analysis was performed, as these were considered for a specific time and are determined only for the purpose of establishing the existence and timely assessment of the OpR in the study unit. Qualitative analysis raised in the MORM made it possible to detect that in the research unit, 67% of detected OpR come from two main sources: external processes (32%) and external events (35%). Additionally, validation of the MORM in Corpoelec-EDELCA, enabled to estimate that 63% of OpR in the organization come from three main categories, with external fraud being present more regularly and greater severity of losses in the organization. Risk exposure is determined basing on adapting the concept of OpVaR generally used for time series and in the case study it presents the advantage of applying it to qualitative data transformed with the Likert scale. The possibility of using typical probability distributions for quantitative data in loss frequency and loss severity distributions with data of qualitative origin were analyzed. For the 64% of OpR studied it was found that the frequency has a similar behavior to that of the Poisson probability distribution and 55% of the cases for loss severity it was found that the log-normal were the most common probability distributions. It was concluded that the approach suggested by the BCBS-BIS for time series can be applied to qualitative data. Once obtained the distributions of loss frequency and severity have been obtained they were subjected to convolution implementing the Monte Carlo method. Thus the loss distribution approaches (LDA) were obtained for each of the OpR. The OpVaR was derived as suggested by the BCBS-BIS 99.9 percentile or 99% of each of the LDA. It was determined that the OpR exhibits a similar behavior to the financial system, being the most dangerous those with low frequency and high impact for their difficulty in being detected and monitored. Finally, it is considered that the MORM will allows market players and their stakeholders to know with effectiveness, efficiency and reliability the status of their entities, which will reduce the uncertainty of their investments and enable them to establish a new management culture in their organizations.

Modeling and optimization of populations subject to time-dependent mutation.

It has become clear that many organisms possess the ability to regulate their mutation rate in response to environmental conditions. So the question of finding an optimal mutation rate must be replaced by that of finding an optimal mutation schedule. We show that this task cannot be accomplished with standard population-dynamic models. We then develop a "hybrid" model for populations experiencing time-dependent mutation that treats population growth as deterministic but the time of first appearance of new variants as stochastic. We show that the hybrid model agrees well with a Monte Carlo simulation. From this model, we derive a deterministic approximation, a "threshold" model, that is similar to standard population dynamic models but differs in the initial rate of generation of new mutants. We use these techniques to model antibody affinity maturation by somatic hypermutation. We had previously shown that the optimal mutation schedule for the deterministic threshold model is phasic, with periods of mutation between intervals of mutation-free growth. To establish the validity of this schedule, we now show that the phasic schedule that optimizes the deterministic threshold model significantly improves upon the best constant-rate schedule for the hybrid and Monte Carlo models.

Interactions between quantitative trait loci in soybean in which trait variation at one locus is conditional upon a specific allele at another.

A large recombinant inbred population of soybean has been characterized for 220 restriction fragment-length polymorphism (RFLP) markers. Values for agronomic traits also have been measured. Quantitative trait loci (QTL) for height, yield, and maturity were located by their linkage to RFLP markers. QTL controlling large amounts of trait variation were analyzed for the dependence of trait variation on particular alleles at a second locus by comparing cumulative distributions of the trait for each genotype (four genotypes per pair of loci). Interesting pairs of loci were analyzed statistically with maximum likelihood and Monte Carlo comparison of additive and epistatic models. For each locus affecting height, variation was conditional upon the presence of a particular allele at a second unlinked locus that itself explained little or no trait variation. The results show that interactions between QTL are frequent and control large effects. Interactions distinguished between different QTL in a single linkage group and between QTL that affect different traits closely linked to one RFLP marker--i.e., distinguished between pleiotropy and closely linked genes. The implications for the evolution of inbreeding plants and for the construction of agronomic breeding strategies are discussed.

In situ isolation of mRNA from individual plant cells: creation of cell-specific cDNA libraries.

A method for isolating and cloning mRNA populations from individual cells in living, intact plant tissues is described. The contents of individual cells were aspirated into micropipette tips filled with RNA extraction buffer. The mRNA from these cells was purified by binding to oligo(dT)-linked magnetic beads and amplified on the beads using reverse transcription and PCR. The cell-specific nature of the isolated mRNA was verified by creating cDNA libraries from individual tomato leaf epidermal and guard cell mRNA preparations. In testing the reproducibility of the method, we discovered an inherent limitation of PCR amplification from small amounts of any complex template. This phenomenon, which we have termed the "Monte Carlo" effect, is created by small and random differences in amplification efficiency between individual templates in an amplifying cDNA population. The Monte Carlo effect is dependent upon template concentration: the lower the abundance of any template, the less likely its true abundance will be reflected in the amplified library. Quantitative assessment of the Monte Carlo effect revealed that only rare mRNAs (< or = 0.04% of polyadenylylated mRNA) exhibited significant variation in amplification at the single-cell level. The cDNA cloning approach we describe should be useful for a broad range of cell-specific biological applications.

Pathways to quiescence: SHARDS view on the star formation histories of massive quiescent galaxies at 1.0 < z < 1.5

We present star formation histories (SFHs) for a sample of 104 massive (stellar mass M > 10^10 M_⊙) quiescent galaxies (MQGs) at z = 1.0–1.5 from the analysis of spectrophotometric data from the Survey for High-z Absorption Red and Dead Sources (SHARDS) and HST/WFC3 G102 and G141 surveys of the GOODS-North field, jointly with broad-band observations from ultraviolet (UV) to far-infrared (far-IR). The sample is constructed on the basis of rest-frame UVJ colours and specific star formation rates (sSFRs = SFR/Mass). The spectral energy distributions (SEDs) of each galaxy are compared to models assuming a delayed exponentially declining SFH. A Monte Carlo algorithm characterizes the degeneracies, which we are able to break taking advantage of the SHARDS data resolution, by measuring indices such as MgUV and D4000. The population of MQGs shows a duality in their properties. The sample is dominated (85 per cent) by galaxies with young mass-weighted ages, t_M t_M < 2 Gyr, short star formation time-scales, 〈τ〉 ∼ 60–200 Myr, and masses log(M/M_⊙) ∼ 10.5. There is an older population (15 per cent) with t_M t_M = 2–4 Gyr, longer star formation time-scales, 〈τ〉∼ 400 Myr, and larger masses, log(M/M_⊙) ∼ 10.7. The SFHs of our MQGs are consistent with the slope and the location of the main sequence of star-forming galaxies at z > 1.0, when our galaxies were 0.5–1.0 Gyr old. According to these SFHs, all the MQGs experienced a luminous infrared galaxy phase that lasts for ∼500 Myr, and half of them an ultraluminous infrared galaxy phase for ∼100 Myr. We find that the MQG population is almost assembled at z ∼ 1, and continues evolving passively with few additions to the population.

Birthplace Effects on the Development of Female Athletic Talent

This study examined the extent to which an athlete's place of birth can influence the likelihood of playing professional sport. Information regarding the birthplace of all American female athletes in the Ladies Professional Golf Association and Women's United Soccer Association was gathered from official league websites. Monte Carlo simulations were used to determine if the birthplace of these professional athletes differed in any systematic way from official census population distributions. Odds-ratios were determined for cities within specific population ranges to ascertain if the likelihood of playing professional sport was influenced in any systematic way by city size. The analyses revealed that female professional soccer players born in cities of less than 1,000,000 were over-represented, as were female professional golfers born in cities of less than 250,000. Results are consistent with those of male professional athletes in suggesting that areas of lower population provide conditions more conducive to the development of expertise than do larger city environments.

When “Where” is More Important Than “When”: Birthplace and Birthdate Effects On The Achievement Of Sporting Expertise

In this study, we assessed whether contextual factors related to where or when an athlete is born influence their likelihood of playing professional sport. The birthplace and birth month of all American players in the National Hockey League, National Basketball Association, Major League Baseball, and Professional Golfer's Association, and all Canadian players in the National Hockey League were collected from official websites. Monte Carlo simulations were used to verify if the birthplace of these professional athletes deviated in any systematic way from the official census population distribution, and chi-square analyses were conducted to determine whether the players' birth months were evenly distributed throughout the year. Results showed a birthplace bias towards smaller cities, with professional athletes being over-represented in cities of less than 500,000 and under-represented in cities of 500,000 and over. A birth month/relative age effect (in the form of a distinct bias towards elite athletes being relatively older than their peers) was found for hockey and baseball but not for basketball and golf. Comparative analyses suggested that contextual factors associated with place of birth contribute more influentially to the achievement of an elite level of sport performance than does relative age and that these factors are essentially independent in their influences on expertise development.