showing 66 related works from this author
Determinants of between-hospital variations in outcomes for patients admitted with COPD exacerbations: findings from a nationwide clinical audit (AUD…
2015
Background Previous studies have demonstrated significant variability in the processes of care and outcomes of chronic obstructive pulmonary disease (COPD) exacerbations. The AUDIPOC is a Spanish nationwide clinical audit that identified large between-hospital variations in care and clinical outcomes. Here, we test the hypothesis that these variations can be attributed to either patient characteristics, hospital characteristics and/or the so-called hospital-clustering effect, which indicates that patients with similar characteristics may experience different processes of care and outcomes depending on the hospital to which they are admitted. Methods A clinical audit of 5178 COPD patients co…
Spatio-Temporal Analysis of Infectious Diseases
2019
Epidemiological research on the pathogenesis, diagnosis, and treatment of infectious diseases is a broad field of study with renewed validity in the face of social changes and new threats [...]
Bayesian Markov switching models for the early detection of influenza epidemics
2008
The early detection of outbreaks of diseases is one of the most challenging objectives of epidemiological surveillance systems. In this paper, a Markov switching model is introduced to determine the epidemic and non-epidemic periods from influenza surveillance data: the process of differenced incidence rates is modelled either with a first-order autoregressive process or with a Gaussian white-noise process depending on whether the system is in an epidemic or in a non-epidemic phase. The transition between phases of the disease is modelled as a Markovian process. Bayesian inference is carried out on the former model to detect influenza epidemics at the very moment of their onset. Moreover, t…
The Integrated Nested Laplace Approximation for fitting Dirichlet regression models
2022
This paper introduces a Laplace approximation to Bayesian inference in Dirichlet regression models, which can be used to analyze a set of variables on a simplex exhibiting skewness and heteroscedasticity, without having to transform the data.These data, which mainly consist of proportions or percentages of disjoint categories, are widely known as compositional data and are common in areas such as ecology, geology, and psychology. We provide both the theoretical foundations and a description of how Laplace approximation can be implemented in the case of Dirichlet regression.The paper also introduces the package dirinla in the R-language that extends the RINLA package, which can not deal dire…
Relation between temperature and mortality in thirteen Spanish cities
2010
In this study we examined the shape of the association between temperature and mortality in 13 Spanish cities representing a wide range of climatic and socio-demographic conditions. The temperature value linked with minimum mortality (MMT) and the slopes before and after the turning point (MMT) were calculated. Most cities showed a V-shaped temperature-mortality relationship. MMTs were generally higher in cities with warmer climates. Cold and heat effects also depended on climate: effects were greater in hotter cities but lesser in cities with higher variability. The effect of heat was greater than the effect of cold. The effect of cold and MMT was, in general, greater for cardio-respirator…
Bayesian spatio-temporal discard model in a demersal trawl fishery
2014
Spatial management of discards has recently been proposed as a useful tool for the protection of juveniles, by reducing discard rates and can be used as a buffer against management errors and recruitment failure. In this study Bayesian hierarchical spatial models have been used to analyze about 440 trawl fishing operations of two different metiers, sampled between 2009 and 2012, in order to improve our understanding of factors that influence the quantity of discards and to identify their spatio-temporal distribution in the study area. Our analysis showed that the relative importance of each variable was different for each metier, with a few similarities. In particular, the random vessel eff…
Neighborhood characteristics and violence behind closed doors: The spatial overlap of child maltreatment and intimate partner violence
2018
In this study, we analyze first whether there is a common spatial distribution of child maltreatment (CM) and intimate partner violence (IPV), and second, whether the risks of CM and IPV are influenced by the same neighborhood characteristics, and if these risks spatially overlap. To this end we used geocoded data of CM referrals (N = 588) and IPV incidents (N = 1450) in the city of Valencia (Spain). As neighborhood proxies, we used 552 census block groups. Neighborhood characteristics analyzed at the aggregated level (census block groups) were: Neighborhood concentrated disadvantage (neighborhood economic status, neighborhood education level, and policing activity), immigrant concentration…
Epidemiology of sharka disease in Spain
2006
Le PPV a ete detecte pour la premiere fois en Espagne en 1984 sur des pruniers japonais (Prunus salicina Lind1) cv. Red Beaut et s'est dissemine tres rapidement a d'autres cultivars de pruniers et d'abricotiers japonais et europeens tout en epargnant les cultivars de pechers. Dans les annees suivant la detection du PPV, l'espece de puceron predominante qui visitait les vergers de Prunus dans les regions mediterraneennes etait Aphis gossypii suivie par Aphis spiraecola, cette derniere etant la principale espece de puceron trouvee actuellement. Les deux especes sont considerees comme les principaux vecteurs du PPV dans les regions de culture de Prunus precoces. Une analyse spatiale de la diss…
An autoregressive approach to spatio-temporal disease mapping
2007
Disease mapping has been a very active research field during recent years. Nevertheless, time trends in risks have been ignored in most of these studies, yet they can provide information with a very high epidemiological value. Lately, several spatio-temporal models have been proposed, either based on a parametric description of time trends, on independent risk estimates for every period, or on the definition of the joint covariance matrix for all the periods as a Kronecker product of matrices. The following paper offers an autoregressive approach to spatio-temporal disease mapping by fusing ideas from autoregressive time series in order to link information in time and by spatial modelling t…
A Bayesian Multilevel Random-Effects Model for Estimating Noise in Image Sensors
2020
Sensor noise sources cause differences in the signal recorded across pixels in a single image and across multiple images. This paper presents a Bayesian approach to decomposing and characterizing the sensor noise sources involved in imaging with digital cameras. A Bayesian probabilistic model based on the (theoretical) model for noise sources in image sensing is fitted to a set of a time-series of images with different reflectance and wavelengths under controlled lighting conditions. The image sensing model is a complex model, with several interacting components dependent on reflectance and wavelength. The properties of the Bayesian approach of defining conditional dependencies among parame…
Evidence for spatiotemporal shift in demersal fishery management priority areas in the western Mediterranean
2022
14 pages, 10 figures, 2 tables, 1 appendix
Epidemiological Information Systems
2008
Modelling the presence of disease under spatial misalignment using Bayesian latent Gaussian models.
2015
Modelling patterns of the spatial incidence of diseases using local environmental factors has been a growing problem in the last few years. Geostatistical models have become popular lately because they allow estimating and predicting the underlying disease risk and relating it with possible risk factors. Our approach to these models is based on the fact that the presence/absence of a disease can be expressed with a hierarchical Bayesian spatial model that incorporates the information provided by the geographical and environmental characteristics of the region of interest. Nevertheless, our main interest here is to tackle the misalignment problem arising when information about possible covar…
Mapping child maltreatment risk: a 12-year spatio-temporal analysis of neighborhood influences.
2017
Abstract Background ‘Place’ matters in understanding prevalence variations and inequalities in child maltreatment risk. However, most studies examining ecological variations in child maltreatment risk fail to take into account the implications of the spatial and temporal dimensions of neighborhoods. In this study, we conduct a high-resolution small-area study to analyze the influence of neighborhood characteristics on the spatio-temporal epidemiology of child maltreatment risk. Methods We conducted a 12-year (2004–2015) small-area Bayesian spatio-temporal epidemiological study with all families with child maltreatment protection measures in the city of Valencia, Spain. As neighborhood units…
Disadvantaged neighborhoods and the spatial overlap of substantiated and unsubstantiated child maltreatment referrals
2019
Abstract Background Considerable debate exists on whether the substantiation decision is a reliable measure for rates of maltreatment. Studies have shown that risks among children victims of maltreatment versus children investigated but unsubstantiated are similar. Objective This paper aims to respond to two research questions: (1) Do most child maltreatment referrals, substantiated and unsubstantiated, come from the same neighborhoods? (2) Do substantiated and unsubstantiated referrals share the same neighborhood risk factors? Participants and settings We used geocoded data from substantiated (n = 1799) and unsubstantiated (n = 1638) child maltreatment referrals in Valencia, Spain (2004–20…
Exploring Neighborhood Influences on Small-Area Variations in Intimate Partner Violence Risk: A Bayesian Random-Effects Modeling Approach
2014
This paper uses spatial data of cases of intimate partner violence against women (IPVAW) to examine neighborhood-level influences on small-area variations in IPVAW risk in a police district of the city of Valencia (Spain). To analyze area variations in IPVAW risk and its association with neighborhood-level explanatory variables we use a Bayesian spatial random-effects modeling approach, as well as disease mapping methods to represent risk probabilities in each area. Analyses show that IPVAW cases are more likely in areas of high immigrant concentration, high public disorder and crime, and high physical disorder. Results also show a spatial component indicating remaining variability attribut…
The university campus environment as a protective factor for intimate partner violence against women: An exploratory study
2017
Some neighborhood characteristics linked to social disorganization theory have been related to intimate partner violence against women (IPVAW). The study of other neighborhood-level factors that may influence IPVAW risk, however, has received less attention. The aim of this study is to analyze the influence of university campuses on IPVAW risk. To conduct the study, IPVAW cases from 2011 to 2013 in the city of Valencia, Spain, were geocoded (n = 1,623). Census block groups were used as the neighborhood analysis unit. Distance between each census block group and the nearest university campus was measured. A Bayesian spatial model adjusted for census block group-level characteristics was perf…
Spatial Bayesian Modeling Applied to the Surveys of Xylella fastidiosa in Alicante (Spain) and Apulia (Italy)
2020
The plant-pathogenic bacterium Xylella fastidiosa was first reported in Europe in 2013, in the province of Lecce, Italy, where extensive areas were affected by the olive quick decline syndrome, caused by the subsp. pauca. In Alicante, Spain, almond leaf scorch, caused by X. fastidiosa subsp. multiplex, was detected in 2017. The effects of climatic and spatial factors on the geographic distribution of X. fastidiosa in these two infested regions in Europe were studied. The presence/absence data of X. fastidiosa in the official surveys were analyzed using Bayesian hierarchical models through the integrated nested Laplace approximation (INLA) methodology. Climatic covariates were obtained from …
Bovine paramphistomosis in Galicia (Spain): Prevalence, intensity, aetiology and geospatial distribution of the infection
2013
12 páginas, 5 figuras, 4 tablas.
Neighborhood Characteristics, Alcohol Outlet Density, and Alcohol-Related Calls-for-Service: A Spatiotemporal Analysis in a Wet Drinking Country
2017
Alcohol outlets have been associated with different social problems, such as crime, violence, intimate partner violence, and child maltreatment. The spatial analysis of neighborhood availability of alcohol outlets is key for better understanding of these influences. Most studies on the spatial distribution of alcohol outlets in the community have been conducted in U.S. cities, but few studies have assessed this spatial distribution in other countries where the drinking culture may differ. The aim of this study was to analyze the spatiotemporal distribution of alcohol outlets in the city of Valencia, Spain, and its relationship with neighborhood-level characteristics, as well as to examine t…
Bayesian spatio-temporal approach to identifying fish nurseries by validating persistence areas
2015
Spatial and temporal closures of fish nursery areas to fishing have recently been recognized as useful tools for efficient fisheries management, as they preserve the reproductive potential of populations and increase the recruitment of target species. In order to identify and locate potential nursery areas for spatio-temporal closures, a solid understanding of species− environment relationships is needed, as well as spatial identification of fish nurseries through the application of robust analyses. One way to achieve knowledge of fish nurseries is to analyse the persistence of recruitment hotspots. In this study, we propose the comparison of different spatiotemporal model structures to ass…
Spatial moving average risk smoothing
2013
This paper introduces spatial moving average risk smoothing (SMARS) as a new way of carrying out disease mapping. This proposal applies the moving average ideas of time series theory to the spatial domain, making use of a spatial moving average process of unknown order to define dependence on the risk of a disease occurring. Correlation of the risks for different locations will be a function of m values (m being unknown), providing a rich class of correlation functions that may be reproduced by SMARS. Moreover, the distance (in terms of neighborhoods) that should be covered for two units to be found to make the correlation of their risks 0 is a quantity to be fitted by the model. This way, …
Spatial Vote Redistribution in Redrawn Polling Units
2012
Summary A large proportion of electoral analyses using geography are performed on a small area basis. In each new election there are always modifications to the previously existing polling units. The use of past voting results in small area aggregate data electoral forecasting models and political analyses therefore requires establishing a correspondence between old and new polling units. Traditionally, the task of tracking changes to assign an electoral history to the new units properly has been carried out by hand, comparing unit codes and census figures. This is an extremely cumbersome task that cannot always be performed, as when a massive (geographically intense) reorganization of poll…
Real-time parameter estimation of Zika outbreaks using model averaging
2017
SUMMARYEarly prediction of the final size of any epidemic and in particular for Zika disease outbreaks can be useful for health authorities in order to plan the response to the outbreak. The Richards model is often been used to estimate epidemiological parameters for arboviral diseases based on the reported cumulative cases in single- and multi-wave outbreaks. However, other non-linear models can also fit the data as well. Typically, one follows the so called post selection estimation procedure, i.e., selects the best fitting model out of the set of candidate models and ignores the model uncertainty in both estimation and inference since these procedures are based on a single model. In this…
A Classification System for Decision-Making in the Management of Patients with Chronic Conditions
2021
Patients with chronic diseases are frequent users of healthcare services. The systematic use of stratification tools and predictive models for this group of patients can be useful for health professionals in decision-making processes. The aim of this study was to design two new classifier systems for detecting the risk of hospital admission for elderly patients with chronic conditions. In this retrospective cohort study, a set of variables related to hospital admission for patients with chronic conditions was obtained through focus groups, a health database analysis and statistical processing. To predict the probability of admission from the set of predictor variables, a logistic regression…
Prediction and Surveillance Sampling Assessment in Plant Nurseries and Fields
2022
In this paper, we propose a structured additive regression (STAR) model for modeling the occurrence of a disease in fields or nurseries. The methodological approach involves a Gaussian field (GF) affected by a spatial process represented by an approximation to a Gaussian Markov random field (GMRF). This modeling allows the building of maps with prediction probabilities regarding the presence of a disease in plants using Bayesian kriging. The advantage of this modeling is its computational benefit when compared with known spatial hierarchical models and with the Bayesian inference based on Markov chain Monte Carlo (MCMC) methods. Inference through the use of the integrated nested Laplace app…
Modelling Inoculum Availability ofPlurivorosphaerella nawaein Persimmon Leaf Litter with Bayesian Beta Regression
2019
AbstractCircular leaf spot (CLS), caused byPlurivorosphaerella nawae, is a serious disease of persimmon (Diospyros kaki) inducing necrotic lesions on leaves, defoliation and fruit drop. Under Mediter-ranean conditions,P. nawaeforms pseudothecia in the leaf litter during winter and ascospores are released in spring infecting susceptible leaves. Persimmon growers are advised to apply fungicides for CLS control during the period of inoculum availability, which was defined based on ascospore counts under the microscope. A model of inoculum availability ofP. nawaewas developed and evaluated as an alternative to ascospore counts. Leaf litter samples were collected weekly in L’Alcúdia from 2010 to…
The Spatial Overlap of Police Calls Reporting Street-Level and Behind-Closed-Doors Crime: A Bayesian Modeling Approach
2021
Traditionally, intimate-partner violence has been considered a special type of crime that occurs behind closed doors, with different characteristics from street-level crime. The aim of this study is to analyze the spatial overlap of police calls reporting street-level and behind-closed-doors crime. We analyzed geocoded police calls in the 552 census-block groups of the city of Valencia, Spain, related to street-level crime (N = 26,624) and to intimate-partner violence against women (N = 11,673). A Bayesian joint model was run to analyze the spatial overlap. In addition, two Bayesian hierarchical models controlled for different neighborhood characteristics to analyze the relative risks. Resu…
Modelling spatially sampled proportion processes
2018
Many ecological processes are measured as proportions and are spatially sampled. In all these cases the standard procedure has long been the transformation of proportional data with the arcsine square root or logit transformation, without considering the spatial correlation in any way. This paper presents a robust regression model to analyse this kind of data using a beta regression and including a spatially correlated term within the Bayesian framework. As a practical example, we apply the proposed approach to a spatio-temporally sampled fishery discard dataset.
Deciphering genomic heterogeneity and the internal composition of tumour activities through a hierarchical factorisation model
2021
Genomic heterogeneity constitutes one of the most distinctive features of cancer diseases, limiting the efficacy and availability of medical treatments. Tumorigenesis emerges as a strongly stochastic process, producing a variable landscape of genomic configurations. In this context, matrix factorisation techniques represent a suitable approach for modelling such complex patterns of variability. In this work, we present a hierarchical factorisation model conceived from a systems biology point of view. The model integrates the topology of molecular pathways, allowing to simultaneously factorise genes and pathways activity matrices. The protocol was evaluated by using simulations, showing a hi…
Bayesian approach to urinary ESBL-producing Escherichia coli
2014
This is a retrospective study about the prevalence of ESBL-producing Escherichia coli (EEC) in urinary specimens from patients from the Comunitat Valenciana from January 2007 to December 2008. Data were retrieved from RedMIVA, and Bayesian generalized linear mixed models were considered to study the prevalence of EEC with regard to demographical and microbiological factors. The total number of infections considered was 164,502, the amount of urinary isolates was 70,827 belonging to 49,304 different patients, and 5,161 (7.3%) of the urinary isolates were EEC. Three out of four E. coli were isolated in women (76.8%), men showed higher rates of EEC (9.7% in men vs. 6.5% in women). EEC patients…
Joint Estimation of Relative Risk for Dengue and Zika Infections, Colombia, 2015–2016
2019
We jointly estimated relative risk for dengue and Zika virus disease (Zika) in Colombia, establishing the spatial association between them at the department and city levels for October 2015–December 2016. Cases of dengue and Zika were allocated to the 87 municipalities of 1 department and the 293 census sections of 1 city in Colombia. We fitted 8 hierarchical Bayesian Poisson joint models of relative risk for dengue and Zika, including area- and disease-specific random effects accounting for several spatial patterns of disease risk (clustered or uncorrelated heterogeneity) within and between both diseases. Most of the dengue and Zika high-risk municipalities varied in their risk distributio…
ASSESSING NEIGHBORHOOD DISORDER: VALIDATION OF A THREE-FACTOR OBSERVATIONAL SCALE
2015
AbstractThis study presents data on the development and preliminary validation of an observational scale assessing neighborhood disorder. Independent observations by trained raters of neighborhood disorder were conducted in 552 census block groups in the city of Valencia (Spain). Intraclass correlation coefficients assessing inter-rater reliability indicated fair to substantial levels of agreement among raters. Confirmatory factor analyses supported a final three-factor model scale measuring physical disorder, social disorder, and physical decay. Results for the internal consistency showed large composite reliability indices indicating good reliability for all neighborhood disorder factors.…
Modelling sensitive elasmobranchs habitat
2013
Basic information on the distribution and habitat preferences of ecologically important species is essential for their management and protection. In the Mediterranean Sea there is increasing concern over elasmobranch species because their biological (ecological) characteristics make them highly vulnerable to fishing pressure. Their removal could affect the structure and function of marine ecosystems, inducing changes in trophic interactions at the community level due to the selective elimination of predators or prey species, competitors and species replacement. In this study Bayesian hierarchical spatial models are used to map the sensitive habitats of the three most caught elasmobranch spe…
Procesos puntuales como herramienta para el análisis de posibles fuentes de contaminación
2002
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 Alc…
Tracking the outbreak. An optimized delimiting survey strategy for Xylella fastidiosa
2020
SummaryCurrent legislation enforces the implementation of intensive surveillance programs for quarantine plant pathogens. After an outbreak, surveys are implemented to delimit the geographic extent of the pathogen and execute disease control. The feasibility of control programs is highly dependent on budget availability, thus it is necessary to target and optimize surveillance strategies.A sequential adaptive delimiting survey involving a three-phase and a two-phase design with increasing spatial resolution was developed and implemented for the Xylella fastidiosa outbreak in Alicante, Spain. Inspection and sampling intensities were optimized using simulation-based methods and results were v…
Bayesian methods in cost-effectiveness studies: objectivity, computation and other relevant aspects.
2009
In a probabilistic sensitivity analysis (PSA) of a cost-effectiveness (CE) study, the unknown parameters are considered as random variables. A crucial question is what probabilistic distribution is suitable for synthesizing the available information (mainly data from clinical trials) about these parameters. In this context, the important role of Bayesian methodology has been recognized, where the parameters are of a random nature. We explore, in the context of CE analyses, how formal objective Bayesian methods can be implemented. We fully illustrate the methodology using two CE problems that frequently appear in the CE literature. The results are compared with those obtained with other popu…
Bayesian dynamic modeling of time series of dengue disease case counts
2017
The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order …
Integrating fishing spatial patterns and strategies to improve high sea fisheries management
2018
Fishing activity in waters beyond national jurisdiction generates multiple management issues, such as data poor fisheries, management of straddling fish stocks and lack of impact assessments on deep-sea Vulnerable Marine Ecosystems (VMEs). Fishing strategy is the key to understanding and managing high seas fisheries, targeting highly migratory resources that are widely distributed. An international fleet, including Spanish flag bottom trawlers, operates along the Patagonian shelf in Southwest Atlantic waters, which includes an unregulated strip of continental shelf beyond national jurisdiction. The Spanish fleet’s fishing strategy was analyzed, and based on on-board observer data collected …
Spatio-Temporal Modeling of Zika and Dengue Infections within Colombia
2018
The aim of this study is to estimate the parallel relative risk of Zika virus disease (ZVD) and dengue using spatio-temporal interaction effects models for one department and one city of Colombia during the 2015&ndash
FluDetWeb: an interactive web-based system for the early detection of the onset of influenza epidemics
2009
Abstract Background The early identification of influenza outbreaks has became a priority in public health practice. A large variety of statistical algorithms for the automated monitoring of influenza surveillance have been proposed, but most of them require not only a lot of computational effort but also operation of sometimes not-so-friendly software. Results In this paper, we introduce FluDetWeb, an implementation of a prospective influenza surveillance methodology based on a client-server architecture with a thin (web-based) client application design. Users can introduce and edit their own data consisting of a series of weekly influenza incidence rates. The system returns the probabilit…
Identifying the best fishing-suitable areas under the new European discard ban
2016
Abstract The spatial management of fisheries has been repeatedly proposed as a discard mitigation measure. A number of studies have assessed the fishing suitability of an area based on units of by-catch or discard per unit effort. However, correct identification of fishing-suitable areas should assess biomass loss with respect to the benefits. This study therefore, proposes the analysis of by-catch ratios, which do represent benefit vs. loss and are standardized to a wide range of effort characteristics. Furthermore, our study proposes the use of two ratios: the proportion of total unwanted biomass out of the total catch as an indicator of the overall ecological impact, and the proportion o…
Bayesian assessment of times to diagnosis in breast cancer screening
2008
Breast cancer is one of the diseases with the most profound impact on health in developed countries and mammography is the most popular method for detecting breast cancer at a very early stage. This paper focuses on the waiting period from a positive mammogram until a confirmatory diagnosis is carried out in hospital. Generalized linear mixed models are used to perform the statistical analysis, always within the Bayesian reasoning. Markov chain Monte Carlo algorithms are applied for estimation by simulating the posterior distribution of the parameters and hyperparameters of the model through the free software WinBUGS.
Statistical Methods for the Geographical Analysis of Rare Diseases
2010
In this chapter we provide a summary of different methods for the detection of disease clusters. First of all, we give a summary of methods for computing estimates of the relative risk. These estimates provide smoothed values of the relative risks that can account for its spatial variation. Some methods for assessing spatial autocorrelation and general clustering are also discussed to test for significant spatial variation of the risk. In order to find the actual location of the clusters, scan methods are introduced. The spatial scan statistic is discussed as well as its extension by means of Generalised Linear Models that allows for the inclusion of covariates and cluster effects. In this …
Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks
2015
Considerable effort has been devoted to the development of statistical algorithms for the automated monitoring of influenza surveillance data. In this article, we introduce a framework of models for the early detection of the onset of an influenza epidemic which is applicable to different kinds of surveillance data. In particular, the process of the observed cases is modelled via a Bayesian Hierarchical Poisson model in which the intensity parameter is a function of the incidence rate. The key point is to consider this incidence rate as a normal distribution in which both parameters (mean and variance) are modelled differently, depending on whether the system is in an epidemic or non-epide…
Statistical relationship between hardness of drinking water and cerebrovascular mortality in Valencia: a comparison of spatiotemporal models
2003
The statistical detection of environmental risk factors in public health studies is usually difficult due to the weakness of their effects and their confounding with other covariates. Small area geographical data bring the opportunity of observing health response in a wide variety of exposure values. Temporal sequences of these geographical datasets are crucial to gaining statistical power in detecting factors. The spatiotemporal models required to perform the statistical analysis have to allow for spatial and temporal correlations, which are more easily modelled via hierarchical structures of hidden random factors. These models have produced important research activity during the last deca…
Geostatistical computing of acoustic maps in the presence of barriers
2009
Acoustic maps are the main diagnostic tools used by authorities for addressing the growing problem of urban acoustic contamination. Geostatistics models phenomena with spatial variation, but restricted to homogeneous prediction regions. The presence of barriers such as buildings introduces discontinuities in prediction areas. In this paper we investigate how to incorporate information of a geographical nature into the process of geostatistical prediction. In addition, we study the use of a Cost-Based distance to quantify the correlation between locations.
Re: Antimicrobial Resistance in More Than 100,000 Escherichia coli Isolates According to Culture Site and Patient Age, Gender, and Location
2011
ABSTRACT Escherichia coli and the antimicrobial pressure exerted on this microorganism can be modulated by factors dependent on the host. In this paper, we describe the distribution of antimicrobial resistance to amikacin, tobramycin, ampicillin, amoxicillin clavulanate, cefuroxime, cefoxitin, cefotaxime, imipenem, ciprofloxacin, fosfomycin, nitrofurantoin, and trimetoprim-sulfametoxazole in more than 100,000 E. coli isolates according to culture site and patient age, gender, and location. Bayesian inference was planned in all statistical analysis, and Markov chain Monte Carlo simulation was employed to estimate the model parameters. Our findings show the existence of a marked difference in…
Fishery-dependent and -independent data lead to consistent estimations of essential habitats
2016
AbstractSpecies mapping is an essential tool for conservation programmes as it provides clear pictures of the distribution of marine resources. However, in fishery ecology, the amount of objective scientific information is limited and data may not always be directly comparable. Information about the distribution of marine species can be derived from two main sources: fishery-independent data (scientific surveys at sea) and fishery-dependent data (collection and sampling by observers in commercial vessels). The aim of this paper is to compare whether these two different sources produce similar, complementary, or different results. We compare them in the specific context of identifying the Es…
Incorporating Biotic Information in Species Distribution Models: A Coregionalized Approach
2021
In this work, we discuss the use of a methodological approach for modelling spatial relationships among species by means of a Bayesian spatial coregionalized model. Inference and prediction is performed using the integrated nested Laplace approximation methodology to reduce the computational burden. We illustrate the performance of the coregionalized model in species interaction scenarios using both simulated and real data. The simulation demonstrates the better predictive performance of the coregionalized model with respect to the univariate models. The case study focus on the spatial distribution of a prey species, the European anchovy (Engraulis encrasicolus), and one of its predator spe…
Spatio-Temporal model structures with shared components for semi-continuous species distribution modelling
2017
Abstract Understanding the spatio-temporal dynamism and environmental relationships of species is essential for the conservation of natural resources. Many spatio-temporally sampled processes result in continuous positive [ 0 , ∞ ) abundance datasets that have many zero values observed in areas that lie outside their optimum niche. In such cases the most common option is to use two-part or hurdle models, which fit independent models and consequently independent environmental effects to occurrence and conditional-to-presence abundance. This may be correct in some cases, but not as much in others where the detection probability is related to the abundance. The aim of this work is to infer the…
Geographical variation in pharmacological prescription
2009
Promoting rational drug administration in treatments is one of the most important issues in Public Health. Bayesian hierarchical models are a very useful tool for incorporating geographical information into the analysis of pharmacological prescription data. They allow the mapping of spatial components which express the trend of geographical variation. In addition, these models are able to deal with uncertainty in a sequential way through prior distributions on parameters and hyperparameters. Bayes' theorem combines all types of information and provides the posterior distribution which is computed through Markov Chain Monte Carlo (MCMC) simulation methods. Simulated data for pharmacological …
Source Detection in an Outbreak of Legionnaire’s Disease
2006
Spatial statistics have broadly been applied, developed and demanded from the field of epidemiology. The point process theory is an appropriate framework to analyse the spatial variation of risk of disease from information at individual level.
A probabilistic expert system for predicting the risk of Legionella in evaporative installations
2011
Research highlights? The bacterium Legionella usually lives in water sources such as cooling towers. ? We discuss a probabilistic expert system for predicting the risk of Legionella. ? The expert system has a master-slave architecture. ? The inference engine is implemented through Bayesian reasoning. ? Bayesian networks model and connect relationships for chemical and physical variables. Early detection in water evaporative installations is one of the keys to fighting against the bacterium Legionella, the main cause of Legionnaire's disease. This paper discusses the general structure, elements and operation of a probabilistic expert system capable of predicting the risk of Legionella in rea…
Accounting for preferential sampling in species distribution models
2019
D. C., A. L. Q. and F. M. would like to thank the Ministerio de Educación y Ciencia (Spain) for financial support (jointly financed by the European Regional Development Fund) via Research Grants MTM2013‐42323‐P and MTM2016‐77501‐P, and ACOMP/2015/202 from Generalitat Valenciana (Spain). Species distribution models (SDMs) are now being widely used in ecology for management and conservation purposes across terrestrial, freshwater, and marine realms. The increasing interest in SDMs has drawn the attention of ecologists to spatial models and, in particular, to geostatistical models, which are used to associate observations of species occurrence or abundance with environmental covariates in a fi…
Two-level resolution of relative risk of dengue disease in a hyperendemic city of Colombia.
2018
Risk maps of dengue disease offer to the public health officers a tool to model disease risk in space and time. We analyzed the geographical distribution of relative incidence risk of dengue disease in a high incidence city from Colombia, and its evolution in time during the period January 2009—December 2015, identifying regional effects at different levels of spatial aggregations. Cases of dengue disease were geocoded and spatially allocated to census sectors, and temporally aggregated by epidemiological periods. The census sectors are nested in administrative divisions defined as communes, configuring two levels of spatial aggregation for the dengue cases. Spatio-temporal models including…
Reference genome assessment from a population scale perspective: an accurate profile of variability and noise.
2017
Abstract Motivation Current plant and animal genomic studies are often based on newly assembled genomes that have not been properly consolidated. In this scenario, misassembled regions can easily lead to false-positive findings. Despite quality control scores are included within genotyping protocols, they are usually employed to evaluate individual sample quality rather than reference sequence reliability. We propose a statistical model that combines quality control scores across samples in order to detect incongruent patterns at every genomic region. Our model is inherently robust since common artifact signals are expected to be shared between independent samples over misassembled regions …
Assessing the spatiotemporal persistence of fish distributions: a case study on two red mullet species (Mullus surmuletus and M. barbatus) in the wes…
2020
Understanding the spatiotemporal persistence of fish distributions is key to defining fish hotspots and effective fisheries-restricted areas (FRAs). Hierarchical Bayesian spatiotemporal models provide an excellent framework to understand these distributions, as they can accommodate different spatiotemporal behaviour in the data, primarily due to their flexibility. The aim of this research was to characterize the fundamental behavioural patterns of fish as persistent, opportunistic or progressive by comparing different spatiotemporal model structures in order to provide better information for marine spatial planning. To illustrate this method, the spatiotemporal distributions of 2 sympatric …
Relative risk estimation of dengue disease at small spatial scale
2017
Abstract Background Dengue is a high incidence arboviral disease in tropical countries around the world. Colombia is an endemic country due to the favourable environmental conditions for vector survival and spread. Dengue surveillance in Colombia is based in passive notification of cases, supporting monitoring, prediction, risk factor identification and intervention measures. Even though the surveillance network works adequately, disease mapping techniques currently developed and employed for many health problems are not widely applied. We select the Colombian city of Bucaramanga to apply Bayesian areal disease mapping models, testing the challenges and difficulties of the approach. Methods…
Auditoria clínica de los pacientes hospitalizados por exacerbación de EPOC en España (estudio AUDIPOC): método y organización del trabajo
2010
Antecedentes Existe poca informacion sobre el manejo clinico de pacientes ingresados en hospitales publicos espanoles con un diagnostico de exacerbacion de enfermedad pulmonar obstructiva cronica. AUDIPOC es una auditoria clinica sobre el manejo de exacerbacion de EPOC en Espana. Objetivos Validar la adecuacion y validez de los instrumentos de medicion de las variables propuestas en AUDIPOC Espana (estudio preliminar) y verificar su viabilidad en un medio complejo con hospitales de tamano, recursos y organizacion diferentes (estudio piloto). Material y metodos El estudio preliminar se realizo en 4 hospitales y 213 casos. El estudio piloto en 30 hospitales de 6 comunidades autonomas y 1.203 …
Spatio-Temporal Analysis of Suicide-Related Emergency Calls
2017
Considerable effort has been devoted to incorporate temporal trends in disease mapping. In this line, this work describes the importance of including the effect of the seasonality in a particular setting related with suicides. In particular, the number of suicide-related emergency calls is modeled by means of an autoregressive approach to spatio-temporal disease mapping that allows for incorporating the possible interaction between both temporal and spatial effects. Results show the importance of including seasonality effect, as there are differences between the number of suicide-related emergency calls between the four seasons of each year.
Chronic high risk of intimate partner violence against women in disadvantaged neighborhoods: An eight-year space-time analysis
2020
Abstract We conducted a small-area ecological longitudinal study to analyze neighborhood contextual influences on the spatio-temporal variations in intimate partner violence against women (IPVAW) risk in a southern European city over an eight-year period. We used geocoded data of IPVAW cases with associated protection orders (n = 5867) in the city of Valencia, Spain (2011–2018). The city's 552 census block groups were used as the neighborhood units. Neighborhood-level covariates were: income, education, immigrant concentration, residential instability, alcohol outlet density, and criminality. We used a Bayesian autoregressive approach to spatio-temporal disease mapping. Neighborhoods with l…
Child maltreatment and alcohol outlets in Spain: Does the country drinking culture matters?
2019
Abstract Background Alcohol outlet density has been linked to rates of substantiated maltreatment both cross-sectionally and over time. Most of these studies have been conducted in Anglo-Saxon countries, especially in the U.S., but other countries, where alcohol outlets and alcohol consumption may have different social meanings, are clearly underrepresented in the literature. Objective The aim of this study was to analyze whether alcohol outlet density is associated with neighborhood-level child maltreatment risk in a South-European city. Participants and setting A longitudinal study was conducted in the city of Valencia (Spain). As spatial units, we used 552 census block groups. Family uni…
Spatial analysis of bovine spongiform encephalopathy in Galicia, Spain (2000–2005)
2007
Abstract In Spain, the first bovine spongiform encephalopathy (BSE) case was detected in 2000 in a cow born in the Galicia region (Northwestern Spain). From then and until October 2005, 590 cases were detected, 223 of them in Galicia. In 1994, meat and bone meal (MBM) was banned on ruminant feed and, in 1996, an EU decision mandating an overall change in MBM processing was implemented. This decision was gradually applied in the territory and not enforced before July 1998. The objective of this study was to explore clustering of BSE cases and estimate the standard incidence ratio (SIR) of BSE in Galicia. Our study was based on the BSE cases detected during the surveillance period 2000–2005 i…
What calls for service tell us about suicide: A 7-year spatio-temporal analysis of neighborhood correlates of suicide-related calls.
2018
AbstractPrevious research has shown that neighborhood-level variables such as social deprivation, social fragmentation or rurality are related to suicide risk, but most of these studies have been conducted in the U.S. or northern European countries. The aim of this study was to analyze the spatio-temporal distribution of suicide in a southern European city (Valencia, Spain), and determine whether this distribution was related to a set of neighborhood-level characteristics. We used suicide-related calls for service as an indicator of suicide cases (n = 6,537), and analyzed the relationship of the outcome variable with several neighborhood-level variables: economic status, education level, po…
Evaluación del desorden en los vecindarios: validación de una escala observacional de tres factores
2015
This study presents data on the development and preliminary validation of an observational scale assessing neighborhood disorder. Independent observations by trained raters of neighborhood disorder were conducted in 552 census block groups in the city of Valencia (Spain). Intraclass correlation coefficients assessing inter-rater reliability indicated fair to substantial levels of agreement among raters. Confirmatory factor analyses supported a final three-factor model scale measuring physical disorder, social disorder, and physical decay. Results for the internal consistency showed large composite reliability indices indicating good reliability for all neighborhood disorder factors. Evidenc…