2024
The long-term effects of domestic and international tuberculosis service improvements on tuberculosis trends within the USA: a mathematical modelling study
Menzies N, Swartwood N, Cohen T, Marks S, Maloney S, Chappelle C, Miller J, Asay G, Date A, Horsburgh C, Salomon J. The long-term effects of domestic and international tuberculosis service improvements on tuberculosis trends within the USA: a mathematical modelling study. The Lancet Public Health 2024, 9: e573-e582. PMID: 39095134, PMCID: PMC11344642, DOI: 10.1016/s2468-2667(24)00150-6.Peer-Reviewed Original ResearchConceptsTuberculosis servicesTuberculosis incidenceCenters for Disease Control and PreventionUS Centers for Disease Control and PreventionDisease Control and PreventionControl and PreventionCombination of interventionsTuberculosis eliminationCountry of originIntervention scenariosInternational interventionLow tuberculosis incidenceService improvementCurrent serviceTuberculosis ProgrammeTuberculosis deathsEconomic outcomesInterventionEpidemiological dataTuberculosis burdenLong-term effectsTotal populationSimulate healthTuberculosis trendsServicesRacial and ethnic disparities in diagnosis and treatment outcomes among US-born people diagnosed with tuberculosis, 2003–19: an analysis of national surveillance data
Regan M, Li Y, Swartwood N, Barham T, Asay G, Cohen T, Hill A, Horsburgh C, Khan A, Marks S, Myles R, Salomon J, Self J, Menzies N. Racial and ethnic disparities in diagnosis and treatment outcomes among US-born people diagnosed with tuberculosis, 2003–19: an analysis of national surveillance data. The Lancet Public Health 2024, 9: e47-e56. PMID: 38176842, DOI: 10.1016/s2468-2667(23)00276-1.Peer-Reviewed Original ResearchConceptsNational surveillance dataNon-Hispanic White peopleTreatment outcomesEthnic disparitiesSurveillance dataTuberculosis diagnosisUS National Tuberculosis Surveillance SystemIndex of disparityLog-binomial regression modelsNational Tuberculosis Surveillance SystemNon-Hispanic black peopleOverall high riskTuberculosis Surveillance SystemAlaska Native peopleTuberculosis patientsDiagnostic delayAdverse outcomesTuberculosis diseaseTuberculosis incidence
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 InstituteDevelopment of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis
Gunasekera K, Marcy O, Muñoz J, Lopez-Varela E, Sekadde M, Franke M, Bonnet M, Ahmed S, Amanullah F, Anwar A, Augusto O, Aurilio R, Banu S, Batool I, Brands A, Cain K, Carratalá-Castro L, Caws M, Click E, Cranmer L, García-Basteiro A, Hesseling A, Huynh J, Kabir S, Lecca L, Mandalakas A, Mavhunga F, Myint A, Myo K, Nampijja D, Nicol M, Orikiriza P, Palmer M, Sant'Anna C, Siddiqui S, Smith J, Song R, Thuong Thuong N, Ung V, van der Zalm M, Verkuijl S, Viney K, Walters E, Warren J, Zar H, Marais B, Graham S, Debray T, Cohen T, Seddon J. Development of treatment-decision algorithms for children evaluated for pulmonary tuberculosis: an individual participant data meta-analysis. The Lancet Child & Adolescent Health 2023, 7: 336-346. PMID: 36924781, PMCID: PMC10127218, DOI: 10.1016/s2352-4642(23)00004-4.Peer-Reviewed Original ResearchConceptsTreatment decision algorithmsPrimary health care settingsIndividual participant dataHigh tuberculosis incidencePulmonary tuberculosisManagement of tuberculosisHealth care centersComposite reference standardHealth care settingsClinical featuresTuberculosis incidenceClinical evaluationParticipant dataTreatment decisionsChest X-ray featuresPrimary health care centersFuture prospective evaluationTuberculosis-related mortalityEvidence-based algorithmChest X-rayVariable diagnostic performanceMultivariable prediction modelReference standardEvidence-based approachTuberculosis experts
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 historyTuberculosisIncidenceTrends, Mechanisms, and Racial/Ethnic Differences of Tuberculosis Incidence in the US-Born Population Aged 50 Years or Older in the United States
Kim S, Cohen T, Horsburgh CR, Miller JW, Hill AN, Marks SM, Li R, Kammerer JS, Salomon JA, Menzies NA. Trends, Mechanisms, and Racial/Ethnic Differences of Tuberculosis Incidence in the US-Born Population Aged 50 Years or Older in the United States. Clinical Infectious Diseases 2021, 74: 1594-1603. PMID: 34323959, PMCID: PMC8799750, DOI: 10.1093/cid/ciab668.Peer-Reviewed Original ResearchConceptsAnnual percentage declineIncidence rateRemote infectionBirth cohortOlder individualsPercentage declineUS National TB Surveillance SystemAverage annual percentage declineNational TB Surveillance SystemRace/ethnicity strataTB incidence rateTB surveillance systemLow-incidence settingsEthnic differencesEarlier birth cohortsRecent birth cohortsRace/ethnicityOverall cohortTB casesTB incidenceIncidence settingsRecent infectionTB ratesTuberculosis incidenceRisk factorsThe 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 ResearchTrends in Untreated Tuberculosis in Large Municipalities, Brazil, 2008–2017 - Volume 27, Number 3—March 2021 - Emerging Infectious Diseases journal - CDC
Chitwood MH, Pelissari DM, da Silva G, Bartholomay P, Rocha MS, Arakaki-Sanchez D, Sanchez M, Cohen T, Castro MC, Menzies NA. Trends in Untreated Tuberculosis in Large Municipalities, Brazil, 2008–2017 - Volume 27, Number 3—March 2021 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2021, 27: 957-960. PMID: 33622464, PMCID: PMC7920690, DOI: 10.3201/eid2703.204094.Peer-Reviewed Original Research
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 hotspotsCost-effectiveness of post-treatment follow-up examinations and secondary prevention of tuberculosis in a high-incidence setting: a model-based analysis
Marx FM, Cohen T, Menzies NA, Salomon JA, Theron G, Yaesoubi R. Cost-effectiveness of post-treatment follow-up examinations and secondary prevention of tuberculosis in a high-incidence setting: a model-based analysis. The Lancet Global Health 2020, 8: e1223-e1233. PMID: 32827484, PMCID: PMC7549318, DOI: 10.1016/s2214-109x(20)30227-8.Peer-Reviewed Original ResearchConceptsIsoniazid preventive therapySecondary preventive therapyHigh-incidence settingsPost-treatment followPreventive therapyTuberculosis controlTuberculosis incidenceTreatment completionTuberculosis case findingOverall disease burdenHigh tuberculosis incidenceTuberculosis-endemic settingHigh-incidence communityFirst yearHealth system costsRecurrent tuberculosisSecondary preventionAnnual followTuberculosis treatmentDisease burdenHigh riskCase findingSingle followSuburban Cape TownPreventive interventions
2018
Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings
Cudahy PGT, Andrews JR, Bilinski A, Dowdy DW, Mathema B, Menzies NA, Salomon JA, Shrestha S, Cohen T. Spatially targeted screening to reduce tuberculosis transmission in high-incidence settings. The Lancet Infectious Diseases 2018, 19: e89-e95. PMID: 30554997, PMCID: PMC6401264, DOI: 10.1016/s1473-3099(18)30443-2.Peer-Reviewed Original ResearchConceptsTuberculosis incidenceLow tuberculosis incidence settingsActive case-finding strategyHigh tuberculosis (TB) incidence countriesCase-finding strategyTuberculosis control strategiesHigh-incidence settingsInfectious causesIncidence settingsIncidence countriesTuberculosis transmissionTreatment outcomesActive screeningOnward transmissionSystematic reviewInfectious individualsInfectious periodTuberculosisIncidenceDeathCauseProximal causeHIVMixed resultsMortalityProgression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions
Menzies NA, Wolf E, Connors D, Bellerose M, Sbarra AN, Cohen T, Hill AN, Yaesoubi R, Galer K, White PJ, Abubakar I, Salomon JA. Progression from latent infection to active disease in dynamic tuberculosis transmission models: a systematic review of the validity of modelling assumptions. The Lancet Infectious Diseases 2018, 18: e228-e238. PMID: 29653698, PMCID: PMC6070419, DOI: 10.1016/s1473-3099(18)30134-8.Peer-Reviewed Original ResearchConceptsTuberculosis transmission modelActive diseaseCumulative incidenceRisk factorsSystematic reviewNatural historyFeatures of epidemiologyDisease natural historyIndividual risk factorsTuberculosis natural historyEarliest available dateWeb of ScienceAnnual incidenceCochrane LibraryTuberculosis incidenceInclusion criteriaFuture tuberculosisLatent infectionInitial infectionIncidenceSubstantial proportionPopulation groupsAvailable dateInfectionDiseaseTuberculosis 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
2016
Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: a combined analysis of 11 mathematical models
Houben RMGJ, Menzies NA, Sumner T, Huynh GH, Arinaminpathy N, Goldhaber-Fiebert JD, Lin HH, Wu CY, Mandal S, Pandey S, Suen SC, Bendavid E, Azman AS, Dowdy DW, Bacaër N, Rhines AS, Feldman MW, Handel A, Whalen CC, Chang ST, Wagner BG, Eckhoff PA, Trauer JM, Denholm JT, McBryde ES, Cohen T, Salomon JA, Pretorius C, Lalli M, Eaton JW, Boccia D, Hosseini M, Gomez GB, Sahu S, Daniels C, Ditiu L, Chin DP, Wang L, Chadha VK, Rade K, Dewan P, Hippner P, Charalambous S, Grant AD, Churchyard G, Pillay Y, Mametja LD, Kimerling ME, Vassall A, White RG. Feasibility of achieving the 2025 WHO global tuberculosis targets in South Africa, China, and India: a combined analysis of 11 mathematical models. The Lancet Global Health 2016, 4: e806-e815. PMID: 27720688, PMCID: PMC6375908, DOI: 10.1016/s2214-109x(16)30199-1.Peer-Reviewed Original ResearchConceptsEnd TB Strategy targetsPreventive therapyTuberculosis incidenceContinuous isoniazid preventive therapyGlobal tuberculosis targetsIsoniazid preventive therapySymptoms of tuberculosisActive case findingNational Tuberculosis ProgrammeEnd TB StrategyHigh-burden countriesAntiretroviral therapyLatent tuberculosisStrategy targetsTuberculosis burdenTuberculosis careTuberculosis ProgrammeTB StrategyTuberculosis transmissionHealth centersAdditional interventionsTuberculosis interventionsCase findingTuberculosis epidemiologyEpidemiological impactCost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models
Menzies NA, Gomez GB, Bozzani F, Chatterjee S, Foster N, Baena IG, Laurence YV, Qiang S, Siroka A, Sweeney S, Verguet S, Arinaminpathy N, Azman AS, Bendavid E, Chang ST, Cohen T, Denholm JT, Dowdy DW, Eckhoff PA, Goldhaber-Fiebert JD, Handel A, Huynh GH, Lalli M, Lin HH, Mandal S, McBryde ES, Pandey S, Salomon JA, Suen SC, Sumner T, Trauer JM, Wagner BG, Whalen CC, Wu CY, Boccia D, Chadha VK, Charalambous S, Chin DP, Churchyard G, Daniels C, Dewan P, Ditiu L, Eaton JW, Grant AD, Hippner P, Hosseini M, Mametja D, Pretorius C, Pillay Y, Rade K, Sahu S, Wang L, Houben RMGJ, Kimerling ME, White RG, Vassall A. Cost-effectiveness and resource implications of aggressive action on tuberculosis in China, India, and South Africa: a combined analysis of nine models. The Lancet Global Health 2016, 4: e816-e826. PMID: 27720689, PMCID: PMC5527122, DOI: 10.1016/s2214-109x(16)30265-0.Peer-Reviewed Original ResearchMeSH KeywordsChinaCost-Benefit AnalysisDelivery of Health CareForecastingGoalsHealth Care CostsHealth ExpendituresHealth PolicyHealth ResourcesHealth Services AccessibilityHealth Services Needs and DemandHumansIndiaModels, TheoreticalPatient Acceptance of Health CareQuality-Adjusted Life YearsSouth AfricaTuberculosisConceptsPatient-incurred costsTuberculosis servicesConventional cost-effectiveness thresholdsHigh-burden countriesEnd TB StrategySubstantial health gainsNet cost savingsResource implicationsCost-effectiveness thresholdMost intervention approachesTB StrategyTuberculosis incidenceMost interventionsSocietal perspectiveHealth gainsIntervention mixMelinda Gates FoundationSubstantial healthHealth effectsCurrent practiceExpansion of accessIntervention approachesEmpirical cost dataCost dataIntervention
2015
Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis
Chindelevitch L, Menzies NA, Pretorius C, Stover J, Salomon JA, Cohen T. Evaluating the potential impact of enhancing HIV treatment and tuberculosis control programmes on the burden of tuberculosis. Journal Of The Royal Society Interface 2015, 12: 20150146. PMID: 25878131, PMCID: PMC4424692, DOI: 10.1098/rsif.2015.0146.Peer-Reviewed Original ResearchConceptsAntiretroviral therapyTB incidenceTB burdenBurden of tuberculosisTuberculosis Control ProgrammePotential epidemiological impactART eligibilityMortality benefitTB programsHIV treatmentTB prevalenceTuberculosis incidenceEpidemiological impactART useProgram improvementHIVTreatment effectivenessIncidenceMortalityGreater reductionBurdenTBSaharan AfricaControl programsEligibility
2014
Incidence of multidrug-resistant tuberculosis disease in children: systematic review and global estimates
Jenkins HE, Tolman AW, Yuen CM, Parr JB, Keshavjee S, Pérez-Vélez CM, Pagano M, Becerra MC, Cohen T. Incidence of multidrug-resistant tuberculosis disease in children: systematic review and global estimates. The Lancet 2014, 383: 1572-1579. PMID: 24671080, PMCID: PMC4094366, DOI: 10.1016/s0140-6736(14)60195-1.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisMultidrug-resistant tuberculosis diseaseTreatment-naive adultsMultidrug-resistant diseaseTuberculosis diseaseTuberculosis incidenceGlobal incidenceSystematic reviewCases of tuberculosisHarvard Medical SchoolGlobal tuberculosis incidenceGlobal annual incidenceTuberculosis riskAnnual incidencePatient groupUS National InstitutesWomen's HospitalInclusion criteriaInternal medicineNew diagnostic instrumentDisease riskTuberculosisIncidenceDiseaseHealth equity
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 individuals