[Growth charts: Impact on the prevalence of nutritional disorders]. / Tablas de crecimiento: impacto sobre la prevalencia de los trastornos nutritivos.

INTRODUCTION: The references used to assess child growth in Spain are the graphs of the Orbegozo Foundation and the charts of the World Health Organization (WHO). The objective of this study is to analyze the differences between the two charts for weight, height and body mass index, and assess their relevance to identify growth or nutritional problems. MATERIAL AND METHODS: The values of the extreme percentiles of height, weight and body mass index for each sex from 0 to 10 years in both charts are compared. For each value Absolute differences and Z scores are calculated for each value. To evaluate the impact on the prevalence of the various nutritional or growth disorders the location of the value of the respective percentiles of in each of the charts were assessed. RESULTS: Significant differences were observed between the 3th percentile of height and weight, 97th of weight, and 85th and 97th of body mass index. Marked differences were observed for the extreme values of body mass index. During the first years, the Orbegozo charts overestimate the prevalence of malnutrition (between 2% and 19% depending on age and sex) compared to the WHO charts. In subsequent ages Orbegozo underestimates WHO between 0.7% and 2.89%. Orbegozo underestimates the prevalence of overweight (between 2.5% and 14.8%) compared to the WHO charts. The 97th percentile of Body mass index in the Orbegozo charts corresponds in most cases with WHO percentiles above 99.99%. CONCLUSION: The two charts analyzed have significant differences from a clinical and the public health point of view, in the estimation of overweight/obesity and malnutrition.

Metagenomics and development of the gut microbiota in infants.

The establishment of a balanced intestinal microbiota is essential for numerous aspects of human health, yet the microbial colonization of the gastrointestinal tract of infants is both complex and highly variable among individuals. In addition, the gastrointestinal tract microbiota is often exposed to antibiotics, and may be an important reservoir of resistant strains and of transferable resistance genes from early infancy. We are investigating by means of diverse metagenomic approaches several areas of microbiota development in infants, including the deployment of functional capabilities at the community level, the presence of antibiotic resistances and the population dynamics of the most abundant genera.

Metagenomics of human microbiome: beyond 16s rDNA.

The gut microbiota presents a symbiotic relationship with the human host playing a beneficial role in human health. Since its establishment, the bacterial community is subjected to the influence of many different factors that shape its composition within each individual. However, an important convergence is observed at functional level in the gut microbiota. A metatranscriptomic study of healthy individuals showed homogeneity in the composition of the active microbiota that increased further at functional level.

A Bayesian hierarchical analysis to compare classical and atypical scrapie surveillance data; Wales 2002-2006.

We describe the application of Bayesian hierarchical models (BHM) to the analysis of risk of sheep scrapie using data from multiple surveillance sources. More specifically, we analysed data from the test results of three surveillance sources on classical and atypical scrapie in Wales for the period 2002-2006. For each form of scrapie, a BHM was fitted to assess the occurrence of spatial patterns of risk shared by the multiple surveillance sources and the association between covariates and disease. We defined a shared-component model whereby the two types of data sources: exhaustive lists (e.g. reports of clinical cases) and sample-based data sources (e.g. abattoir survey) shared a common spatial pattern of risks at parish level. This shared component was adjusted by a risk-gradient parameter that moderated the individual contribution of the datasets. For both forms of scrapie, the risk-gradient was not significantly different indicating that the sensitivity of the two types of dataset was similar for the two diseases. The spatial patterns of the combinations of data sources appeared similar within disease. However, our results suggest that classical and atypical scrapie differ in their spatial patterns and disease determinants. The joint approach permitted inference from all the available evidence and resulted in robust and less biased estimates of risk, particularly for atypical scrapie where the number of observations was very limited.

Geographic density of landfill sites and risk of congenital anomalies in England.

OBJECTIVE: To investigate the risk of congenital anomalies in relation to an index of geographic density of landfill sites across 5x5 km grid squares in England. METHODS: 2 km zones were constructed in a geographical information system around 8804 landfill sites, including 607 that handled special (hazardous) wastes, and intersected with postcode coordinates of over 10 million births (136,821 with congenital anomalies), 1983-98. A landfill exposure index was calculated to represent the geographic density of landfill sites within 2 km of births for each 5x5 km grid square, calculated separately for landfill sites handling special, and non-special or unknown, waste. For each group of landfills, the index was classified into four categories of intensity, and risks for the second, third and top categories were compared to the bottom category, comprising areas with no such landfill sites within 2 km (index of zero). We used hierarchical logistic regression modelling in a Bayesian framework, with adjustment for potential confounding. RESULTS: For special waste sites, adjusted odds ratios were significant for the third category of the landfill exposure index for all anomalies combined and cardiovascular defects (OR 1.08 (95% credible interval 1.02 to 1.13) and 1.16 (1.00 to 1.33), respectively) and for hypospadias and epispadias for the third and top categories (OR 1.11 (1.02 to 1.21) and 1.12 (1.02 to 1.22), respectively). After adjustment, there were no excess risks in relation to sites handling non-special or unknown waste types. CONCLUSIONS: There was a weak spatial association between risk of certain congenital anomalies and geographic density of special (hazardous) waste sites at the level of 5x5 km grid squares. Exposure pathways and mechanisms to help interpret these findings are not well-established.

Distributed support vector machines.

A truly distributed (as opposed to parallelized) support vector machine (SVM) algorithm is presented. Training data are assumed to come from the same distribution and are locally stored in a number of different locations with processing capabilities (nodes). In several examples, it has been found that a reasonably small amount of information is interchanged among nodes to obtain an SVM solution, which is better than that obtained when classifiers are trained only with the local data and comparable (although a little bit worse) to that of the centralized approach (obtained when all the training data are available at the same place). We propose and analyze two distributed schemes: a "naïve" distributed chunking approach, where raw data (support vectors) are communicated, and the more elaborated distributed semiparametric SVM, which aims at further reducing the total amount of information passed between nodes while providing a privacy-preserving mechanism for information sharing. We show the feasibility of our proposal by evaluating the performance of the algorithms in benchmarks with both synthetic and real-world datasets.

Analysis of the renal transplant waiting list in the País Valencià (Spain).

In this paper we analyse the renal transplant waiting list of the País Valencià in Spain, using Queueing theory. The customers of this queue are patients with end-stage renal failure waiting for a kidney transplant. We set up a simplified model to represent the flow of the customers through the system, and perform Bayesian inference to estimate parameters in the model. Finally, we consider several scenarios by tuning the estimations achieved and computationally simulate the behaviour of the queue under each one. The results indicate that the system could reach equilibrium at some point in the future and the model forecasts a slow decrease in the size of the waiting list in the short and middle term.

[Point processes as a tool for analyzing possible sources of contamination]. / Procesos puntuales como herramienta para el análisis de posibles fuentes de contaminación.

Point pattern analysis pattern comprises a series of techniques that enables the distribution of a series of events occurring in the vicinity of a particular region of a map to be studied. In epidemiology, this problem arises when a potential source of environmental contamination, possibly leading to cases of a specific disease, is investigated.The present study provides a brief description of point pattern analysis. The approach is illustrated through determination of the environmental source and study of the areas of greatest risk of incidence of an outbreak of legionella pneumonia that occurred between the middle of September and beginning of October in the city of Alcoi in Alicante (Spain).Point pattern analysis was able to confirm the environmental source of the outbreak and identify the areas of the city at greatest risk. This provided the justification for an exhaustive inspection of the installations generating aerosols after which, to date, the epidemics ceased.

Procesos puntuales como herramienta para el análisis de posibles fuentes de contaminación / Point processes as a tool for analyzing possible sources of contamination

El análisis de un patrón puntual engloba una serie de técnicas que permiten estudiar la distribución de un conjunto de eventos ocurridos sobre una región del plano. Este problema surge en epidemiología cuando se investiga una potencial fuente de contaminación ambiental alrededor de la cual se sospecha que surgen casos de una determinada enfermedad. En el presente trabajo, se explica brevemente en qué consiste el análisis de un patrón puntual y se ilustra con una aplicación a la determinación del origen medioambiental y al estudio de las zonas de mayor riesgo de incidencia en un brote de neumonía por Legionella ocurrido entre mediados de septiembre y principios de octubre en la ciudad de Alcoi (Alicante). El estudio permitió confirmar el origen medioambiental del brote y señalar las zonas de la ciudad con mayor riesgo, convirtiéndose en el argumento básico para llevar a cabo una exhaustiva inspección de las instalaciones generadoras de aerosoles, tras la cual, hasta la fecha, cesaron los brotes epidémicos (AU)

Point pattern analysis pattern comprises a series of techniques that enables the distribution of a series of events occurring in the vicinity of a particular region of a map to be studied. In epidemiology, this problem arises when a potential source of environmental contamination, possibly leading to cases of a specific disease, is investigated. The present study provides a brief description of point pattern analysis. The approach is illustrated through determination of the environmental source and study of the areas of greatest risk of incidence of an outbreak of legionella pneumonia that occurred between the middle of September and beginning of October in the city of Alcoi in Alicante (Spain). Point pattern analysis was able to confirm the environmental source of the outbreak and identify the areas of the city at greatest risk. This provided the justification for an exhaustive inspection of the installations generating aerosols after which, to date, the epidemics ceased (AU)

Incorporación de la metodología geoestadística a la vigilancia de la gripe en una red centinela / Incorporation of geostatistical methodology for influenza surveillance in a sentinel network

Objetivo: Valorar la descripción geoestadística realizada de los datos de gripe recogidos a través de la Red Centinela Sanitaria de la Comunidad Valenciana (RCSCV) mediante la utilización del método kriging con la finalidad de evaluar la posibilidad de su incorporación a la vigilancia rutinaria Método: Se han utilizado los datos de vigilancia de gripe de la RCSCV en tres temporadas gripales (1997-1998, 1998-1999 y 1999-2000), construyéndose una matriz de datos de incidencia de gripe geocodificada. La distribución geográfica fue estudiada mediante la técnica geoestadística kriging, que permite estimar la incidencia de la enfermedad en cualquier punto del territorio, a partir de la incidencia observada en unos pocos puntos estratégicamente distribuidos. Se elaboraron mapas de curvas de isoincidencia de gripe para cada semana. La valoración de la técnica se realizó mediante validación cruzada. Resultados: En la mayoría de las semanas, los valores tanto de la desviación estándar (DE) reducida, como de la media reducida estuvieron cercanos a los valores considerados óptimos (0 o 1, respectivamente), y sólo en la última temporada se obtuvieron valores de la DE reducida alejados de los considerados como de buen ajuste en 12 de las 20 semanas. La estimación de tasas en todas las temporadas demostró una coherencia en su distribución espacial. También se observó coherencia en la evolución temporal. Conclusiones: En la mayoría de las situaciones los resultados pueden considerarse aceptables, no requiere recursos informáticos extraordinarios ni un empleo de tiempo excesivo, y necesita tan sólo una adaptación anual. Su facilidad de uso lo hace apto para su utilización como una técnica de rutina, pese a que puede mejorarse la precisión de las estimaciones, incrementando la complejidad del modelo (AU)

Objectives: To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kriging method and to assess the possibility of incorporating this method into routine surveillance. Methods: We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kriging method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method. Results: In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution. Conclusions: In most situations the results were acceptable. The method does not requiere extra computer resources or an excessive amount of time and requires only annual adaptation. Becauseit is easy to use, the technique is appropriate for routine use but the accuracy of estimations could be improved by increasing the complexity of the model (AU)

[Incorporation of geostatistical methodology for influenza surveillance in a sentinel network]. / Incorporación de la metodología geoestadística a la vigilancia de la gripe en una red centinela.

OBJECTIVES: To evaluate geostatistical description of influenza data from the Valencian Sentinel Network (VSN) in Spain using the kringing method and to assess the possibility of incorporating this method into routine surveillance. METHODS: We use influenza surveillance data on three influenza seasons (1997-1998, 1998-1999 and 1999-2000) from the VSN to construct a geocodified data matrix of the incidence of this disease. The geographic distribution was studied using the kringing method, which enables estimation of the incidence in a few strategically distributed points. Influenza isoincidence maps for each week were plotted. Cross validation was used to evaluate the method. RESULTS: In most of the weeks, the values of reduced standard deviation and reduced mean were close to the optimal values (0 and 1, respectively). Out of range reduced standard deviation values were found in 12 of 20 weeks in the last season only. The estimation of rates in all three seasons showed coherence in spatial distribution and temporal evolution. CONCLUSIONS: In most situations the results were acceptable. The method does not require extra computer resources or an excessive amount of time and requires only annual adaptation. Because it is easy to use, the technique is appropriate for routine use but the accuracy of estimations could be improved by increasing the complexity of the model.