0000000000172652

AUTHOR

A. Iftimi

showing 2 related works from this author

A Bayesian unified framework for risk estimation and cluster identification in small area health data analysis.

2020

Many statistical models have been proposed to analyse small area disease data with the aim of describing spatial variation in disease risk. In this paper, we propose a Bayesian hierarchical model that simultaneously allows for risk estimation and cluster identification. Our model formulation assumes that there is an unknown number of risk classes and small areas are assigned to a risk class by means of independent allocation variables. Therefore, areas within each cluster are assumed to share a common risk but they may be geographically separated. The posterior distribution of the parameter representing the number of risk classes is estimated using a novel procedure that combines its prior …

Computer scienceEpidemiologyPathology and Laboratory Medicine01 natural sciencesGeographical locations010104 statistics & probabilityChickenpoxMathematical and Statistical TechniquesStatisticsMedicine and Health SciencesPublic and Occupational Health0303 health sciencesMultidisciplinarySimulation and ModelingQREuropeIdentification (information)Medical MicrobiologySmall-Area AnalysisViral PathogensVirusesPhysical SciencesMedicinePathogensAlgorithmsResearch ArticleHerpesvirusesScienceBayesian probabilityPosterior probabilityBayesian MethodDisease SurveillanceDisease clusterResearch and Analysis MethodsRisk AssessmentMicrobiologyVaricella Zoster Virus03 medical and health sciencesRisk classPrior probabilityCovariateBayesian hierarchical modelingHumansEuropean Union0101 mathematicsMicrobial Pathogens030304 developmental biologyBiology and life sciencesOrganismsStatistical modelBayes TheoremProbability TheoryProbability DistributionMarginal likelihoodConvolutionSpainPeople and placesDNA virusesMathematical FunctionsMathematicsPloS one
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Temporal association between the influenza virus and respiratory syncytial virus (RSV): RSV as a predictor of seasonal influenza.

2016

SUMMARYEpidemiologists agree that there is a prevailing seasonality in the presentation of epidemic waves of respiratory syncytial virus (RSV) infections and influenza. The aim of this study is to quantify the potential relationship between the activity of RSV, with respect to the influenza virus, in order to use the RSV seasonal curve as a predictor of the evolution of an influenza virus epidemic wave. Two statistical tools, logistic regression and time series, are used for predicting the evolution of influenza. Both logistic models and time series of influenza consider RSV information from previous weeks. Data consist of influenza and confirmed RSV cases reported in Comunitat Valenciana (…

0301 basic medicineAdultMaleTime FactorsMultinomial logistic modelAdolescentEpidemiologyBinomial regression030106 microbiologyRespiratory Syncytial Virus InfectionsBiologyLogistic regressionmedicine.disease_causeVirusSeasonal influenza03 medical and health sciencesYoung AdultInfluenza HumanmedicineHumansChildEpidemicsAgedAged 80 and overInfant Newbornvirus diseasesInfantMiddle AgedOrthomyxoviridaeVirologyOriginal PapersInfectious DiseasesRespiratory syncytial virus (RSV)Logistic ModelsSpainChild PreschoolRespiratory Syncytial Virus HumanFemaleSeasonsEpidemiology and infection
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