Search results for "Spain"
showing 10 items of 2556 documents
Prevalence of bacteria and absence of anisakid parasites in raw and prepared fish and seafood dishes in Spanish restaurants
2015
This study evaluated the presence of bacteria and anisakid parasites in 45 samples of raw anchovies in vinegar, a dish widely eaten in Spain, and in 227 samples of cooked fish and cephalopods served in Spanish food service establishments. Our analysis showed that, according to European and Spanish regulation, 14 to 30% of the prepared fish and cephalopod dishes exceeded the maximum allowable level for mesophilic aerobic counts, and 10 to 40% of these samples exceeded the allowable levels for Enterobacteriaceae. None of the studied samples showed evidence of anisakid parasites, Escherichia coli, Staphylococcus aureus, Salmonella, or Listeria monocyto genes. These results indicate that applic…
Detection of spatial disease clusters with LISA functions.
2011
Detection of disease clusters is an important tool in epidemiology that can help to identify risk factors associated with the disease and in understanding its etiology. In this article we propose a method for the detection of spatial clusters where the locations of a set of cases and a set of controls are available. The method is based on local indicators of spatial association functions (LISA functions), particularly on the development of a local version of the product density, which is a second-order characteristic of spatial point processes. The behavior of the method is evaluated and compared with Kulldorff's spatial scan statistic by means of a simulation study. It is shown that the LI…
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…
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…
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…
Analysis of the renal transplant waiting list in the País Valencià (Spain).
2005
In this paper we analyse the renal transplant waiting list of the Pais Valencia 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 mid…
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, …
Overcoming the “lost before translation” problem: An exploratory study
2019
This paper draws on Stokes’ (1997) framework to position the disconnection between theory and practice as a knowledge production problem. In this sense, we argue that a better understanding of different academic profiles is extremely important to focus efforts on those academics that may overcome the ‘lost before translation’ problem. Our data, that come from a survey of researchers affiliated to the Spanish National Research Council (CSIC), provide a good opportunity to explore the factors that might increase or impede the likelihood that researchers engage in research that reconciles the quest for fundamental understanding with the consideration of use (Pasteur’s profile), rather than in …
The cumulative effect of multiple dimensions of lifestyle on risky drinking during the Covid-19 pandemic
2021
Lifestyle impacts morbidity and mortality worldwide. Herein, we evaluated the association of a multidimensional lifestyle measure and its domains (diet/nutrition, substance use, physical activity, social, stress management, sleep, environmental exposure) with risky drinking. Also, we analyzed the cumulative effect of unhealthy domains in the likelihood of presenting risky drinking. To reach these objectives, data from a web survey conducted in Brazil and Spain was analyzed. The main outcome was risky drinking assessed by the AUDIT-C. Lifestyle was measured using the Short Multidimensional Inventory Lifestyle Evaluation (SMILE). Fixed logistic models were used to evaluate associations betwee…
Lifestyle in Undergraduate Students and Demographically Matched Controls during the COVID-19 Pandemic in Spain
2021
Few studies have used a multidimensional approach to describe lifestyle changes among undergraduate students during the COVID-19 pandemic or have included controls. This study aimed to evaluate lifestyle behaviors and mental health of undergraduate students and compare them with an age and sex-matched control group. A cross-sectional web survey using snowball sampling was conducted several months after the beginning of COVID-19 pandemic in Spain. A sample of 221 students was recruited. The main outcome was the total SMILE-C score. Students showed a better SMILE-C score than controls (79.8 + 8.1 vs. 77.2 + 8.3