Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains
Izu A, Cohen T, Mitnick C, Murray M, De Gruttola V. Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains. Statistics In Medicine 2011, 30: 2708-2720. PMID: 21717491, PMCID: PMC3219798, DOI: 10.1002/sim.4287.Peer-Reviewed Original ResearchConceptsCharacterization of uncertaintyBayesian approachBayesian methodsBranching tree modelStatistical methodsMixture modelBranching treeNatural wayPrior informationDrug resistance-conferring mutationsSuch cross-sectional dataDrug-resistant TBResistant TB strainsCombination of antibioticsDrug resistance mutationsMeasurement errorResistance-conferring mutationsTB strainsSingle patientTreatment policyPatientsMultiple drugsDiagnostic specimensCross-sectional dataGenetic mutationsEpidemiologic Inference From the Distribution of Tuberculosis Cases in Households in Lima, Peru
Brooks-Pollock E, Becerra MC, Goldstein E, Cohen T, Murray MB. Epidemiologic Inference From the Distribution of Tuberculosis Cases in Households in Lima, Peru. The Journal Of Infectious Diseases 2011, 203: 1582-1589. PMID: 21592987, PMCID: PMC3096792, DOI: 10.1093/infdis/jir162.Peer-Reviewed Original ResearchConceptsHousehold contactsCommunity transmissionHousehold casesPrevious TB infectionNew TB casesHigh-incidence settingsHousehold risk factorsClustering of casesDistribution of casesMajority of casesRisk of diseaseTB infectionActive tuberculosisTB casesCase patientsProtective immunityTuberculosis casesHousehold transmissionRisk factorsNumber of casesHousehold exposureNatural historyTuberculosisCross-sectional dataImmunity