2023
Global, regional, and national estimates of tuberculosis incidence and case detection among incarcerated individuals from 2000 to 2019: a systematic analysis
Martinez L, Warren J, Harries A, Croda J, Espinal M, Olarte R, Avedillo P, Lienhardt C, Bhatia V, Liu Q, Chakaya J, Denholm J, Lin Y, Kawatsu L, Zhu L, Horsburgh C, Cohen T, Andrews J. Global, regional, and national estimates of tuberculosis incidence and case detection among incarcerated individuals from 2000 to 2019: a systematic analysis. The Lancet Public Health 2023, 8: e511-e519. PMID: 37393090, PMCID: PMC10323309, DOI: 10.1016/s2468-2667(23)00097-x.Peer-Reviewed Original ResearchConceptsTuberculosis incidenceCase detection ratioIncidence rateCase detectionHigh tuberculosis incidence ratesGlobal tuberculosis control effortsIncident tuberculosis casesTuberculosis incidence rateIncarcerated individualsTuberculosis control effortsTuberculosis case detectionTuberculosis casesNotification ratesNational incidenceTuberculosis notificationsGlobal incidenceHigh riskPrevalence estimatesNational estimatesWHO regionsIncidenceStudy periodMeta-regression frameworkTuberculosisNational Institute
2022
Budget impact of next-generation sequencing for diagnosis of TB drug resistance in Moldova
Cates L, Codreanu A, Ciobanu N, Fosburgh H, Allender C, Centner H, Engelthaler D, Crudu V, Cohen T, Menzies N. Budget impact of next-generation sequencing for diagnosis of TB drug resistance in Moldova. The International Journal Of Tuberculosis And Lung Disease 2022, 26: 963-969. PMID: 36163669, DOI: 10.5588/ijtld.22.0104.Peer-Reviewed Original ResearchConceptsPhenotypic drug susceptibility testingConventional phenotypic drug susceptibility testingTB drug resistanceDrug resistanceNext-generation sequencingTB treatment regimensNational TB ProgrammeDrug resistance testingMTB/RIFDrug susceptibility testingBudget impact analysisMajority of costsFeasibility of NGSTB programsTreatment regimensBudget impactSusceptibility testingRoutine useResistance testingStudy periodTesting volume
2021
Global estimates of paediatric tuberculosis incidence in 2013–19: a mathematical modelling analysis
Yerramsetti S, Cohen T, Atun R, Menzies NA. Global estimates of paediatric tuberculosis incidence in 2013–19: a mathematical modelling analysis. The Lancet Global Health 2021, 10: e207-e215. PMID: 34895517, PMCID: PMC8800006, DOI: 10.1016/s2214-109x(21)00462-9.Peer-Reviewed Original ResearchConceptsPediatric tuberculosisTuberculosis incidenceStudy periodIncident tuberculosis casesTuberculosis incidence rateReporting systemHigh-burden settingsGlobal tuberculosis burdenTuberculosis natural historyPediatric incidenceInfectious exposurePrompt diagnosisSubstantial morbidityTuberculosis burdenTuberculosis casesIncidence rateRisk factorsCase detectionGlobal incidenceProbability of infectionInfected individualsAge groupsNatural historyTuberculosisIncidence
2013
Risk factors and timing of default from treatment for non-multidrug-resistant tuberculosis in Moldova
Jenkins HE, Ciobanu A, Plesca V, Crudu V, Galusca I, Soltan V, Cohen T. Risk factors and timing of default from treatment for non-multidrug-resistant tuberculosis in Moldova. The International Journal Of Tuberculosis And Lung Disease 2013, 17: 373-380. PMID: 23407226, PMCID: PMC3710709, DOI: 10.5588/ijtld.12.0464.Peer-Reviewed Original ResearchMeSH KeywordsAdultAntitubercular AgentsContinuity of Patient CareFemaleHumansInstitutionalizationLeast-Squares AnalysisLinear ModelsMaleMedication AdherenceMoldovaMultivariate AnalysisPatient DischargePrisonersProportional Hazards ModelsRetrospective StudiesRisk FactorsSocioeconomic FactorsTime FactorsTreatment OutcomeTuberculosisConceptsMultidrug-resistant tuberculosisMDR-TB patientsRisk factorsHighest MDR-TB ratesDrug resistanceGreater lung pathologyMDR-TB ratesAnti-tuberculosis treatmentIndependent risk factorHuman immunodeficiency virusTB drug resistanceContinuity of careRoutine surveillance dataTuberculosis patientsResistant tuberculosisImmunodeficiency virusLung pathologyTreatment adherenceRetrospective analysisHigh riskPatientsSociodemographic factorsCommunity careSurveillance dataStudy period