2024
Cost-effectiveness and health impact of screening and treatment of Mycobacterium tuberculosis infection among formerly incarcerated individuals in Brazil: a Markov modelling study
van Lieshout Titan A, Klaassen F, Pelissari D, de Barros Silva J, Alves K, Alves L, Sanchez M, Bartholomay P, Johansen F, Croda J, Andrews J, Castro M, Cohen T, Vuik C, Menzies N. Cost-effectiveness and health impact of screening and treatment of Mycobacterium tuberculosis infection among formerly incarcerated individuals in Brazil: a Markov modelling study. The Lancet Global Health 2024, 12: e1446-e1455. PMID: 39151980, PMCID: PMC11339731, DOI: 10.1016/s2214-109x(24)00221-3.Peer-Reviewed Original ResearchConceptsDisability-adjusted life yearsTuberculosis preventive treatmentTuberculosis deathsHealth impactsImpact of screeningIntervention cost-effectivenessInfection screeningCost-effectiveNational Institutes of HealthHealth outcomesHealth gainsInstitutes of HealthQuantify health effectsTuberculosis casesCost-effectiveness ratioTreatment of Mycobacterium tuberculosis infectionPotential health impactsLife yearsGreater health benefitsTuberculosis preventionTarget populationMonths of isoniazidMarkov modelling studiesHealth statesHealth
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
Excess tuberculosis cases and deaths following an economic recession in Brazil: an analysis of nationally representative disease registry data
Li Y, de Macedo Couto R, Pelissari DM, Costa Alves L, Bartholomay P, Maciel EL, Sanchez M, Castro MC, Cohen T, Menzies NA. Excess tuberculosis cases and deaths following an economic recession in Brazil: an analysis of nationally representative disease registry data. The Lancet Global Health 2022, 10: e1463-e1472. PMID: 36049488, PMCID: PMC9472578, DOI: 10.1016/s2214-109x(22)00320-5.Peer-Reviewed Original ResearchConceptsNational Notifiable Diseases Information SystemTuberculosis casesTuberculosis deathsExcess casesTuberculosis case ratesTuberculosis transmissionCase ratesNotifiable Diseases Information SystemTuberculosis case notificationDisease registry dataMortality Information SystemMixed effects regression modelsSupplementary Materials sectionFraction of casesTuberculosis controlUS National InstitutesTuberculosis incidenceCase notificationRegistry dataExcess deathsAge groupsDeathPossible explanatory factorsNational InstituteYoung men
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 historyTuberculosisIncidenceLifetime burden of disease due to incident tuberculosis: a global reappraisal including post-tuberculosis sequelae
Menzies NA, Quaife M, Allwood BW, Byrne AL, Coussens AK, Harries AD, Marx FM, Meghji J, Pedrazzoli D, Salomon JA, Sweeney S, van Kampen SC, Wallis RS, Houben RMGJ, Cohen T. Lifetime burden of disease due to incident tuberculosis: a global reappraisal including post-tuberculosis sequelae. The Lancet Global Health 2021, 9: e1679-e1687. PMID: 34798027, PMCID: PMC8609280, DOI: 10.1016/s2214-109x(21)00367-3.Peer-Reviewed Original ResearchConceptsPost-tuberculosis sequelaeBurden estimatesTuberculosis diseaseDisease episodesIncident tuberculosisIncident tuberculosis casesIncident tuberculosis diseaseNon-fatal health lossOverall disease burdenPulmonary tuberculosis diseaseLifetime health outcomesDisease burden estimatesElevated mortality riskHigh incidence rateExtrapulmonary diseaseLung functionCase fatalityHIV statusLifetime burdenTuberculosis casesTotal DALYsDisease burdenIncidence rateHypothetical cohortTuberculosis survivorsThe escalating tuberculosis crisis in central and South American prisons
Walter KS, Martinez L, Arakaki-Sanchez D, Sequera VG, Sanabria G, Cohen T, Ko AI, García-Basteiro AL, Rueda ZV, López-Olarte RA, Espinal MA, Croda J, Andrews JR. The escalating tuberculosis crisis in central and South American prisons. The Lancet 2021, 397: 1591-1596. PMID: 33838724, PMCID: PMC9393884, DOI: 10.1016/s0140-6736(20)32578-2.Peer-Reviewed Original ResearchDevelopment of a Treatment-decision Algorithm for Human Immunodeficiency Virus–uninfected Children Evaluated for Pulmonary Tuberculosis
Gunasekera KS, Walters E, van der Zalm MM, Palmer M, Warren JL, Hesseling AC, Cohen T, Seddon JA. Development of a Treatment-decision Algorithm for Human Immunodeficiency Virus–uninfected Children Evaluated for Pulmonary Tuberculosis. Clinical Infectious Diseases 2021, 73: e904-e912. PMID: 33449999, PMCID: PMC8366829, DOI: 10.1093/cid/ciab018.Peer-Reviewed Original ResearchConceptsPulmonary tuberculosisClinical evidenceXpert MTB/RIFBaseline clinical evaluationChest radiographic resultsRapid treatment initiationNational Tuberculosis ProgrammeTreatment decision algorithmsEvidence-based algorithmMTB/RIFDiagnosis of tuberculosisChest radiographicAntituberculosis treatmentProspective cohortRadiographic resultsTreatment initiationTuberculosis casesTuberculosis ProgrammeClinical evaluationCase definitionTreatment decisionsGlobal burdenChildhood mortalityChildren EvaluatedRapid clinical diagnosis
2020
High-resolution estimates of tuberculosis incidence among non-U.S.-born persons residing in the United States, 2000–2016
Hill AN, Cohen T, Salomon JA, Menzies NA. High-resolution estimates of tuberculosis incidence among non-U.S.-born persons residing in the United States, 2000–2016. Epidemics 2020, 33: 100419. PMID: 33242759, PMCID: PMC7808561, DOI: 10.1016/j.epidem.2020.100419.Peer-Reviewed Original ResearchConceptsIncidence risk ratioTuberculosis incidence rateIncidence rateTuberculosis riskTuberculosis casesNational Tuberculosis Surveillance SystemTuberculosis prevention effortsNew tuberculosis casesLow incidence rateTuberculosis Surveillance SystemBirth countryTuberculosis incidenceRisk ratioTuberculosis trendsHigh-income countriesYounger agePrevention effortsEffective targetingCohortEntry yearCommunity surveySurveillance systemRegression modelsAgeUnited StatesChildren as sentinels of tuberculosis transmission: disease mapping of programmatic data
Gunasekera KS, Zelner J, Becerra MC, Contreras C, Franke MF, Lecca L, Murray MB, Warren JL, Cohen T. Children as sentinels of tuberculosis transmission: disease mapping of programmatic data. BMC Medicine 2020, 18: 234. PMID: 32873309, PMCID: PMC7466499, DOI: 10.1186/s12916-020-01702-x.Peer-Reviewed Original ResearchConceptsNational Tuberculosis ProgrammeActive case-finding interventionsCase-finding interventionsTuberculosis transmissionNotification dataTuberculosis ProgrammeTuberculosis incidenceChild casesChildhood tuberculosis casesRecent transmission eventsProportion of casesCase notification dataMolecular epidemiological methodsMolecular epidemiologic methodsEndemic infectious diseasesTuberculosis casesProspective studyAdult casesDisease progressionNotification registerProgrammatic dataDistricts of LimaEpidemiological methodsInfectious diseasesTransmission hotspotsTransmission Modeling with Regression Adjustment for Analyzing Household-based Studies of Infectious Disease: Application to Tuberculosis.
Crawford FW, Marx FM, Zelner J, Cohen T. Transmission Modeling with Regression Adjustment for Analyzing Household-based Studies of Infectious Disease: Application to Tuberculosis. Epidemiology 2020, 31: 238-247. PMID: 31764276, PMCID: PMC7718772, DOI: 10.1097/ede.0000000000001143.Peer-Reviewed Original ResearchConceptsSusceptible household contactsHousehold contactsTB casesBacillus Calmette-Guérin (BCG) vaccinationInfected household contactsIsoniazid preventive therapyActive tuberculosis casesCulture-positive casesRisk of diseaseCohort studyMicrobiological confirmationPreventive therapyTuberculosis casesRisk factorsInfection resultsAdult contactsInfection riskInfectious diseasesLogistic regressionRate of transmissionTransmissible diseasesDiseaseIndividual-level characteristicsHigher hazardDisease susceptibilityThe risk of tuberculosis in children after close exposure: a systematic review and individual-participant meta-analysis
Martinez L, Cords O, Horsburgh C, Andrews J, Consortium P, Acuna-Villaorduna C, Ahuja S, Altet N, Augusto O, Baliashvili D, Basu S, Becerra M, Bonnet M, Boom W, Borgdorff M, Boulahbal F, Carvalho A, Cayla J, Chakhaia T, Chan P, Cohen T, Croda J, Datta S, del Corral H, Denholm J, Dietze R, Dobler C, Donkor S, Egere U, Ellner J, Espinal M, Evans C, Fang C, Fielding K, Fox G, García L, García-Basteiro A, Geis S, Graham S, Grandjean L, Hannoun D, Hatherill M, Hauri A, Hesseling A, Hill P, Huang L, Huerga H, Hussain R, Jarlsberg L, Jones-López E, Kato S, Kato-Maeda M, Kampmann B, Kirchner H, Kritski A, Lange C, Lee C, Lee L, Lee M, Lemos A, Lienhardt C, Ling D, Liu Q, Lo N, Long R, Lopez-Varela E, Lu P, Magee M, Malone L, Mandalakas A, Martinson N, Mazahir R, Murray M, Netto E, Otero L, Parsonnet J, Reingold A, Schaaf H, Seddon J, Sharma S, Singh J, Singh S, Sloot R, Sotgiu G, Stein C, Iqbal N, Triasih R, Trieu L, van der Loeff M, Van der Stuyft P, van Schalkwyk C, Vashishtha R, Verhagen L, Villalba J, Wang J, Whalen C, Yoshiyama T, Zar H, Zellweger J, Zhu L. The risk of tuberculosis in children after close exposure: a systematic review and individual-participant meta-analysis. The Lancet 2020, 395: 973-984. PMID: 32199484, PMCID: PMC7289654, DOI: 10.1016/s0140-6736(20)30166-5.Peer-Reviewed Original ResearchConceptsYears of agePreventive therapyIncident tuberculosisTuberculosis infectionHazard ratioTuberculosis casesMixed-effects Poisson regression modelsSystematic reviewFinal analysisClose exposureIncident tuberculosis casesRisk of tuberculosisDevelopment of tuberculosisEMBASE electronic databasesIndividual participant dataPositive resultsPoisson regression modelsWeb of ScienceMixed-effects logistic modelBCG vaccinationCohort studyBaseline visitPrevalent tuberculosisContact investigationProspective study
2019
Disparities in access to diagnosis and care in Blantyre, Malawi, identified through enhanced tuberculosis surveillance and spatial analysis
MacPherson P, Khundi M, Nliwasa M, Choko AT, Phiri VK, Webb EL, Dodd PJ, Cohen T, Harris R, Corbett EL. Disparities in access to diagnosis and care in Blantyre, Malawi, identified through enhanced tuberculosis surveillance and spatial analysis. BMC Medicine 2019, 17: 21. PMID: 30691470, PMCID: PMC6350280, DOI: 10.1186/s12916-019-1260-6.Peer-Reviewed Original ResearchConceptsTB case notification ratesCase notification ratesCommunity health workersNotification ratesTB casesLow case detectionSingle sputum sampleInverse care lawArea-level factorsTB registrationTB clinicTB patientsClinical characteristicsTB diagnosisTuberculosis casesResultsIn totalTB surveillanceCase detectionModifiable predictorsSputum samplesHealth workersTB officersTB microscopyAdjusted modelTuberculosis surveillance
2018
Tuberculosis control interventions targeted to previously treated people in a high-incidence setting: a modelling study
Marx FM, Yaesoubi R, Menzies NA, Salomon JA, Bilinski A, Beyers N, Cohen T. Tuberculosis control interventions targeted to previously treated people in a high-incidence setting: a modelling study. The Lancet Global Health 2018, 6: e426-e435. PMID: 29472018, PMCID: PMC5849574, DOI: 10.1016/s2214-109x(18)30022-6.Peer-Reviewed Original ResearchConceptsHigh-incidence settingsIsoniazid preventive therapyPreventive therapyTuberculosis treatmentActive casesHIV prevalenceTuberculosis controlControl interventionsIncident tuberculosis casesPrevious tuberculosis treatmentTuberculosis control interventionsTB case notificationHigh-risk groupTransmission dynamic modelTuberculosis deathsHigh tuberculosisRecurrent diseasePrevalent tuberculosisTuberculosis casesTuberculosis incidenceCase notificationTreatment outcomesTuberculosis morbidityTuberculosis epidemicAdditional interventions
2017
Drivers of Tuberculosis Transmission
Mathema B, Andrews JR, Cohen T, Borgdorff MW, Behr M, Glynn JR, Rustomjee R, Silk BJ, Wood R. Drivers of Tuberculosis Transmission. The Journal Of Infectious Diseases 2017, 216: s644-s653. PMID: 29112745, PMCID: PMC5853844, DOI: 10.1093/infdis/jix354.Peer-Reviewed Original ResearchConceptsRecent transmissionTuberculosis transmissionTuberculosis casesCulture-positive tuberculosis casesInterferon-γ release assaysΓ release assaysTuberculin skin testMycobacterium tuberculosis infectionTuberculosis case notificationTransmission of tuberculosisPublic health systemPrevalent tuberculosisTuberculosis infectionSkin testIncident diseaseCase notificationClinical diseaseHealth systemCapacity of healthcareOngoing transmissionTuberculosisYoung childrenHighlight knowledge gapsInfection eventsWhole-genome sequencing
2015
Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data
Zelner JL, Murray MB, Becerra MC, Galea J, Lecca L, Calderon R, Yataco R, Contreras C, Zhang Z, Manjourides J, Grenfell BT, Cohen T. Identifying Hotspots of Multidrug-Resistant Tuberculosis Transmission Using Spatial and Molecular Genetic Data. The Journal Of Infectious Diseases 2015, 213: 287-294. PMID: 26175455, PMCID: PMC4690150, DOI: 10.1093/infdis/jiv387.Peer-Reviewed Original ResearchConceptsMDR tuberculosisDrug susceptibilityTuberculosis casesMultidrug-resistant tuberculosis (MDR-TB) transmissionCulture-confirmed diseaseHealth Center areaProspective cohort studyCapita incidenceHousehold contactsCohort studyTuberculosis riskTuberculosis transmissionSymptomatic individualsHigh riskPositive culturesNumber tandem repeatRiskEtiology
2014
Cigarette smoking among tuberculosis patients increases risk of transmission to child contacts
Huang CC, Tchetgen ET, Becerra MC, Cohen T, Galea J, Calderon R, Yataco R, Contreras C, Zhang ZB, Lecca L, Murray M. Cigarette smoking among tuberculosis patients increases risk of transmission to child contacts. The International Journal Of Tuberculosis And Lung Disease 2014, 18: 1285-1291. PMID: 25299859, DOI: 10.5588/ijtld.14.0309.Peer-Reviewed Original ResearchConceptsLatent tuberculous infectionTuberculin skin testTB patientsIndex caseChild household contactsDrug-susceptible TBIndex TB patientsObservational cohort studySecondhand smoke exposureRisk of transmissionPoisson regression modelsHousehold contactsCohort studyTST positivityTuberculosis patientsTuberculous infectionSmoke exposureSmoking statusTuberculosis casesCigarette smokingSkin testRisk factorsPatientsInfection statusTime pointsAge-Specific Risks of Tuberculosis Infection From Household and Community Exposures and Opportunities for Interventions in a High-Burden Setting
Zelner JL, Murray MB, Becerra MC, Galea J, Lecca L, Calderon R, Yataco R, Contreras C, Zhang Z, Grenfell BT, Cohen T. Age-Specific Risks of Tuberculosis Infection From Household and Community Exposures and Opportunities for Interventions in a High-Burden Setting. American Journal Of Epidemiology 2014, 180: 853-861. PMID: 25190676, PMCID: PMC4188339, DOI: 10.1093/aje/kwu192.Peer-Reviewed Original ResearchConceptsLatent tuberculosis infectionHousehold contactsAge-specific riskYears of ageTuberculosis infectionLarge population-based prospective cohort studyPopulation-based prospective cohort studyHousehold exposureBacillus Calmette-Guérin (BCG) vaccineIncident pulmonary tuberculosisCommunity exposureProspective cohort studyCalmette-Guérin vaccineHigh-burden settingsPublic Health CenterCommunity-based transmissionRisk of infectionCohort studyLTBI prevalencePreventive therapyPulmonary tuberculosisTuberculosis patientsTuberculosis casesHousehold transmissionExcess riskGeographical heterogeneity of multidrug-resistant tuberculosis in Georgia, January 2009 to June 2011.
Jenkins HE, Gegia M, Furin J, Kalandadze I, Nanava U, Chakhaia T, Cohen T. Geographical heterogeneity of multidrug-resistant tuberculosis in Georgia, January 2009 to June 2011. Eurosurveillance 2014, 19 PMID: 24679722, PMCID: PMC4090679, DOI: 10.2807/1560-7917.es2014.19.11.20743.Peer-Reviewed Original ResearchConceptsMultidrug-resistant TBMDR-TB risk factorsTB casesRisk factorsMDR-TB incidenceMDR-TB riskMDR-TB transmissionMDR-TB casesMultidrug-resistant tuberculosisTreatment-naïve individualsMDR-TB burdenTuberculosis casesHigh riskTargeted interventionsSurveillance dataGeographical heterogeneityRegression modellingInterventionRiskRural areasCasesTuberculosisIncidencePercentage
2013
Evaluation of the Tuberculosis Strain Typing Service (TB-STS) in England
Mears J, Vynnycky E, Lord J, Borgdorff M, Cohen T, Abubakar I, Sonnenberg P, group O. Evaluation of the Tuberculosis Strain Typing Service (TB-STS) in England. The Lancet 2013, 382: s73. DOI: 10.1016/s0140-6736(13)62498-8.Peer-Reviewed Original ResearchTuberculosis incidenceProportion of infectionsDiagnostic delayBase-case assumptionsLatent infectionPulmonary tuberculosis casesTuberculosis control effortsHigh-incidence settingsMycobacterium tuberculosis isolatesCluster investigationsTuberculosis notification ratesPost-implementation dataComplex public health interventionsPopulation-level interventionsPublic health interventionsMIRU-VNTR typingTuberculosis infectionTuberculosis casesPreventive treatmentPublic health outcomesNotification ratesTuberculosis isolatesSenior Research FellowshipDeterministic compartmental modelProportion of individualsBayesian Estimation of Mixture Models with Prespecified Elements to Compare Drug Resistance in Treatment-Naïve and Experienced Tuberculosis Cases
Izu A, Cohen T, DeGruttola V. Bayesian Estimation of Mixture Models with Prespecified Elements to Compare Drug Resistance in Treatment-Naïve and Experienced Tuberculosis Cases. PLOS Computational Biology 2013, 9: e1002973. PMID: 23555210, PMCID: PMC3605089, DOI: 10.1371/journal.pcbi.1002973.Peer-Reviewed Original ResearchConceptsTreatment-experienced patientsDrug-resistant strainsMultiple drug-resistant strainsTreatment-naïve patientsDrug-resistant tuberculosisMycobacterium tuberculosis isolatesWorld Health OrganizationDrug resistance pathwaysTreatment-naïveTuberculosis casesTuberculosis isolatesWorldwide surveillanceDrug resistancePatientsHealth OrganizationResistant strainsResistant pathogensResistance pathwaysLow transmissibilityPathwayTuberculosis