Spatial--temporal mesoscale modeling of rainfall intensity using gage and radar data

Gridded estimated rainfall intensity values at very high spatial and temporal resolution levels are needed as main inputs for weather prediction models to obtain accurate precipitation forecasts, and to verify the performance of precipitation forecast models. These gridded rainfall fields are also the main driver for hydrological models that forecast flash floods, and they are essential for disaster prediction associated with heavy rain. Rainfall information can be obtained from rain gages that provide relatively accurate estimates of the actual rainfall values at point-referenced locations, but they do not characterize well enough the spatial and temporal structure of the rainfall fields. Doppler radar data offer better spatial and temporal coverage, but Doppler radar measures effective radar reflectivity ($Ze$) rather than rainfall rate ($R$). Thus, rainfall estimates from radar data suffer from various uncertainties due to their measuring principle and the conversion from $Ze$ to $R$. We introduce a framework to combine radar reflectivity and gage data, by writing the different sources of rainfall information in terms of an underlying unobservable spatial temporal process with the true rainfall values. We use spatial logistic regression to model the probability of rain for both sources of data in terms of the latent true rainfall process. We characterize the different sources of bias and error in the gage and radar data and we estimate the true rainfall intensity with its posterior predictive distribution, conditioning on the observed data.Comment: Published in at http://dx.doi.org/10.1214/08-AOAS166 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

A multivariate semiparametric Bayesian spatial modeling framework for hurricane surface wind fields

Storm surge, the onshore rush of sea water caused by the high winds and low pressure associated with a hurricane, can compound the effects of inland flooding caused by rainfall, leading to loss of property and loss of life for residents of coastal areas. Numerical ocean models are essential for creating storm surge forecasts for coastal areas. These models are driven primarily by the surface wind forcings. Currently, the gridded wind fields used by ocean models are specified by deterministic formulas that are based on the central pressure and location of the storm center. While these equations incorporate important physical knowledge about the structure of hurricane surface wind fields, they cannot always capture the asymmetric and dynamic nature of a hurricane. A new Bayesian multivariate spatial statistical modeling framework is introduced combining data with physical knowledge about the wind fields to improve the estimation of the wind vectors. Many spatial models assume the data follow a Gaussian distribution. However, this may be overly-restrictive for wind fields data which often display erratic behavior, such as sudden changes in time or space. In this paper we develop a semiparametric multivariate spatial model for these data. Our model builds on the stick-breaking prior, which is frequently used in Bayesian modeling to capture uncertainty in the parametric form of an outcome. The stick-breaking prior is extended to the spatial setting by assigning each location a different, unknown distribution, and smoothing the distributions in space with a series of kernel functions. This semiparametric spatial model is shown to improve prediction compared to usual Bayesian Kriging methods for the wind field of Hurricane Ivan.Comment: Published at http://dx.doi.org/10.1214/07-AOAS108 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Quantile regression for mixed models with an application to examine blood pressure trends in China

Cardiometabolic diseases have substantially increased in China in the past 20 years and blood pressure is a primary modifiable risk factor. Using data from the China Health and Nutrition Survey, we examine blood pressure trends in China from 1991 to 2009, with a concentration on age cohorts and urbanicity. Very large values of blood pressure are of interest, so we model the conditional quantile functions of systolic and diastolic blood pressure. This allows the covariate effects in the middle of the distribution to vary from those in the upper tail, the focal point of our analysis. We join the distributions of systolic and diastolic blood pressure using a copula, which permits the relationships between the covariates and the two responses to share information and enables probabilistic statements about systolic and diastolic blood pressure jointly. Our copula maintains the marginal distributions of the group quantile effects while accounting for within-subject dependence, enabling inference at the population and subject levels. Our population-level regression effects change across quantile level, year and blood pressure type, providing a rich environment for inference. To our knowledge, this is the first quantile function model to explicitly model within-subject autocorrelation and is the first quantile function approach that simultaneously models multivariate conditional response. We find that the association between high blood pressure and living in an urban area has evolved from positive to negative, with the strongest changes occurring in the upper tail. The increase in urbanization over the last twenty years coupled with the transition from the positive association between urbanization and blood pressure in earlier years to a more uniform association with urbanization suggests increasing blood pressure over time throughout China, even in less urbanized areas. Our methods are available in the R package BSquare.Comment: Published at http://dx.doi.org/10.1214/15-AOAS841 in the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Atención a las víctimas de violencia de género en la comunidad estudiantil de la Universidad Autónoma del Estado de México

La violencia de género afecta a las y los estudiantes de diversas formas y es un factor importante que impacta el pleno ejercicio de los derechos humanos y universitarios. Desde la perspectiva de género, se acepta que ciertos patrones de conducta son reproducidos en la práctica y legitimados en los discursos que ubican a la mujer como subordinada al hombre

El Enfoque del Desarrollo Territorial rural desde la perspectiva de género. Análisis en una localidad indígena del norte del estado de México

A través del Enfoque Territorial para el desarrollo rural, se analiza la participación de las y los actores en la gestión del desarrollo de la comunidad desde las instituciones formales como las informales, todo esto desde una perspectiva territorial y de género. El estudio de caso se realiza en una localidad indígena del municipio de Ixtlahuaca. San Pedro de los Baños, una localidad que a través del tiempo ha enfrentado cambios desde la llegada de la industria, hasta las políticas de apoyo a la reducción de la pobreza, así como el papel importante que han tenido las y los habitantes en un contexto de alta marginación. El presente documento tiene como fundamental objetivo dar a conocer el contexto de la localidad y de la situación de sus pobladores en cuanto a las acciones para disminuir y superar las condiciones de pobreza destacando las actividades diferenciadas por sexo. Se analiza también los modos de organización de los pobladores y se concluye con un análisis de la política de desarrollo territorial y cómo es que esta influye en el desarrollo del territorio a través de las características del mismo vista desde la perspectiva de género, en la cual se sugieren recomendaciones para la aplicación de las políticas enfocadas a los territorios rurales

Una mirada desde la salud intercultural en programas de cooperación al desarrollo

La dificultat i la complexitat que comporta parlar de salut intercultural fa necessari que s'abordi el tema amb rigor i des d'estudis sobre el terreny. Aquest article tracta de contribuir a l'anàlisi i l'estudi de la salut intercultural, de forma particular a Amèrica Llatina, on els processos de capacitació immersos en projectes de desenvolupament, lluny de traçar ponts entre els diferents sistemes mèdics, persegueixen hegemonitzar el model biomèdic participant en el manteniment de relacions etnocèntriques i asimètriques.The difficulty and complexity of talking about intercultural health makes it necessary to exercise rigor and consult case studies. This article seeks to contribute to the analysis and study of intercultural health, particularly in Latin America where the training processes involved in development projects, far removed from the building of bridges between different medical systems, seek to hegemonize the biomedical model by contributing to the maintenance of ethnocentric and asymmetrical relations.La dificultad y la complejidad que conlleva hablar de salud intercultural hace necesario que se aborde el tema con rigurosidad y desde estudios sobre el terreno. Este artículo trata de contribuir en el análisis y el estudio de la salud intercultural, de forma particular en América Latina, donde los procesos de capacitación inmersos en proyectos de desarrollo, lejos de trazar puentes entre los diferentes sistemas médicos, persiguen hegemonizar el modelo biomédico participando en el mantenimiento de relaciones etnocéntricas y asimétricas