2024
Predictors of unsuccessful tuberculosis treatment outcomes in Brazil: an analysis of 259,484 patient records
Ryuk D, Pelissari D, Alves K, Oliveira P, Castro M, Cohen T, Sanchez M, Menzies N. Predictors of unsuccessful tuberculosis treatment outcomes in Brazil: an analysis of 259,484 patient records. BMC Infectious Diseases 2024, 24: 531. PMID: 38802744, PMCID: PMC11129366, DOI: 10.1186/s12879-024-09417-7.Peer-Reviewed Original ResearchConceptsTreatment outcomesFactors associated with unsuccessful treatment outcomesHigher risk of poor treatment outcomeTB treatmentRisk of poor treatment outcomesUnsuccessful treatmentEffectiveness of TB treatmentAssociated with unsuccessful treatmentUnsuccessful treatment outcomesTuberculosis treatment outcomesDrug-susceptible TBHealth system levelMultivariate logistic regression modelService-related factorsTB drug resistanceComorbid health conditionsHealth-related behaviorsCategorizing treatment outcomesPatient-level factorsClinical examination resultsNational Disease Notification SystemPoor treatment outcomesDisease notification systemHIV infectionLogistic regression modelsDisparities in Tuberculosis Incidence by Race and Ethnicity Among the U.S.-Born Population in the United States, 2011 to 2021 : An Analysis of National Disease Registry Data.
Li Y, Regan M, Swartwood N, Barham T, Beeler Asay G, Cohen T, Hill A, Horsburgh C, Khan A, Marks S, Myles R, Salomon J, Self J, Menzies N. Disparities in Tuberculosis Incidence by Race and Ethnicity Among the U.S.-Born Population in the United States, 2011 to 2021 : An Analysis of National Disease Registry Data. Annals Of Internal Medicine 2024, 177: 418-427. PMID: 38560914, DOI: 10.7326/m23-2975.Peer-Reviewed Original ResearchConceptsIncidence rate ratiosNon-Hispanic white personsTB incidence rateRate ratiosIncidence rateTB incidenceSocial determinants of healthRelated disparitiesWhite personsHealth equity goalsU.S.-born populationAbsolute disparityDeterminants of healthTB registry dataRacial/ethnic minority populationsCenters for Disease Control and PreventionDisease Control and PreventionIncidence rate differenceTB casesYoung personControl and PreventionState of residenceAI/AN personsSocial determinantsRacial/ethnic disparitiesIdentifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model
Lan Y, Crudu V, Ciobanu N, Codreanu A, Chitwood M, Sobkowiak B, Warren J, Cohen T. Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model. EBioMedicine 2024, 102: 105085. PMID: 38531172, PMCID: PMC10987885, DOI: 10.1016/j.ebiom.2024.105085.Peer-Reviewed Original ResearchConceptsPatterns of spatial aggregationMtb strainsMDR-TBLogistic regression modelsGenome Epidemiology StudySpecific strainsMultidrug-resistant tuberculosisTreated TB casesNational Institute of AllergyMDR phenotypeRegression modelsM. tuberculosisInstitute of AllergyMultinomial logistic regression modelUS National Institutes of HealthNational Institutes of HealthMDR diseasePublic health concernAssociated with local transmissionIncident TBInstitutes of HealthMtbResistant tuberculosisStrainDiagnosing TBRacial 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 ResearchMeSH KeywordsEthnicityFemaleHealthcare DisparitiesHumansMaleRacial GroupsTreatment OutcomeTuberculosisUnited StatesConceptsNational 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
Spatially-targeted tuberculosis screening has limited impact beyond household contact tracing in Lima, Peru: A model-based analysis
Havumaki J, Warren J, Zelner J, Menzies N, Calderon R, Contreras C, Lecca L, Becerra M, Murray M, Cohen T. Spatially-targeted tuberculosis screening has limited impact beyond household contact tracing in Lima, Peru: A model-based analysis. PLOS ONE 2023, 18: e0293519. PMID: 37903091, PMCID: PMC10615320, DOI: 10.1371/journal.pone.0293519.Peer-Reviewed Original ResearchGlobal burden of disease due to rifampicin-resistant tuberculosis: a mathematical modeling analysis
Menzies N, Allwood B, Dean A, Dodd P, Houben R, James L, Knight G, Meghji J, Nguyen L, Rachow A, Schumacher S, Mirzayev F, Cohen T. Global burden of disease due to rifampicin-resistant tuberculosis: a mathematical modeling analysis. Nature Communications 2023, 14: 6182. PMID: 37794037, PMCID: PMC10550952, DOI: 10.1038/s41467-023-41937-9.Peer-Reviewed Original ResearchConceptsDisability-adjusted life yearsRifampicin-resistant tuberculosisRR-TBGlobal burdenSubstantial short-term morbidityRifampicin-susceptible tuberculosisShort-term morbidityOverall disease burdenLong-term health impactsPost-treatment careTB survivorsDisease burdenTreatment outcomesTuberculosis survivorsCase detectionLife yearsRifampicin resistanceTuberculosisHealth impactsBurdenHealth expenditureDiseaseSurvivorsMathematical modeling analysisFormer Soviet Union countriesTabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States
Swartwood N, Testa C, Cohen T, Marks S, Hill A, Beeler Asay G, Cochran J, Cranston K, Randall L, Tibbs A, Horsburgh C, Salomon J, Menzies N. Tabby2: a user-friendly web tool for forecasting state-level TB outcomes in the United States. BMC Medicine 2023, 21: 331. PMID: 37649031, PMCID: PMC10469407, DOI: 10.1186/s12916-023-02785-y.Peer-Reviewed Original ResearchConceptsLatent tuberculosis infectionTB outcomesDistrict of ColumbiaTreatment of LTBIIncremental cost-effectiveness ratioTB incidence rateTuberculosis disease burdenQuality-adjusted life yearsCost-effectiveness ratioPublic health agenciesTB casesTB preventionTB incidenceTuberculosis infectionTB epidemiologyDisease burdenIncidence rateService utilizationAdditional interventionsIncidence projectionsLife yearsDemographic dataSocietal perspectiveHealth agenciesPrevention approachesGlobal, 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 InstituteTransmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics
Dodd P, Shaweno D, Ku C, Glaziou P, Pretorius C, Hayes R, MacPherson P, Cohen T, Ayles H. Transmission modeling to infer tuberculosis incidence prevalence and mortality in settings with generalized HIV epidemics. Nature Communications 2023, 14: 1639. PMID: 36964130, PMCID: PMC10037365, DOI: 10.1038/s41467-023-37314-1.Peer-Reviewed Original ResearchConceptsHigh HIV prevalence settingsEstimation of burdenHIV prevalence settingsGeneralized HIV epidemicsTB transmission modelAntiretroviral therapyTB infectionTB incidenceHIV prevalenceTB prevalencePrevalence settingsTB epidemicHIV epidemicHigh burdenBurden estimatesNotification dataAnnual riskSingle pathogenIntervention impactTherapy effectsTuberculosisPrevalenceEpidemicBurdenAfrican countriesDevelopment 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 ResearchMeSH KeywordsAdolescentAlgorithmsChildHumansRetrospective StudiesTriageTuberculosisTuberculosis, PulmonaryUnited StatesConceptsTreatment 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 expertsEstimated rates of progression to tuberculosis disease for persons infected with Mycobacterium tuberculosis in the United States
Ekramnia M, Li Y, Haddad M, Marks S, Kammerer J, Swartwood N, Cohen T, Miller J, Horsburgh C, Salomon J, Menzies N. Estimated rates of progression to tuberculosis disease for persons infected with Mycobacterium tuberculosis in the United States. Epidemiology 2023, 35: 164-173. PMID: 38290139, PMCID: PMC10832387, DOI: 10.1097/ede.0000000000001707.Peer-Reviewed Original ResearchConceptsInterferon-gamma release assayNational Health and Nutrition Examination SurveyHealth and Nutrition Examination SurveyUS-born statusNational TB Surveillance SystemReactivation TBNutrition Examination SurveyInterferon-gammaIGRA sensitivityTB surveillance systemProgression to tuberculosis diseaseNationally representative dataEnd-stage renal diseaseReactivation rateAmerican Community SurveyExamination SurveyPerson yearsRace-ethnicityUS populationTB ratesTB incidenceCommunity SurveyRepresentative dataSurveillance systemRelease assay
2022
Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis
Smith J, Cohen T, Dowdy D, Shrestha S, Gandhi NR, Hill AN. Quantifying Mycobacterium tuberculosis Transmission Dynamics Across Global Settings: A Systematic Analysis. American Journal Of Epidemiology 2022, 192: 133-145. PMID: 36227246, PMCID: PMC10144641, DOI: 10.1093/aje/kwac181.Peer-Reviewed Original ResearchMeSH KeywordsHumansMycobacterium tuberculosisTuberculosisTuberculosis, Multidrug-ResistantWhole Genome SequencingConceptsTB transmissionOngoing TB transmissionMinority of casesTuberculosis transmission dynamicsTB controlTuberculosis transmissionSecondary casesSources of heterogeneityInclusion criteriaSurveillance studyTransmission clustersInitial searchTransmission dynamicsWhole-genome sequencingPopulation levelSettingRe-evaluating the health impact and cost-effectiveness of tuberculosis preventive treatment for modern HIV cohorts on antiretroviral therapy: a modelling analysis using data from Tanzania
Zhu J, Lyatuu G, Sudfeld CR, Kiravu A, Sando D, Machumi L, Minde J, Chisonjela F, Cohen T, Menzies NA. Re-evaluating the health impact and cost-effectiveness of tuberculosis preventive treatment for modern HIV cohorts on antiretroviral therapy: a modelling analysis using data from Tanzania. The Lancet Global Health 2022, 10: e1646-e1654. PMID: 36240830, PMCID: PMC9553191, DOI: 10.1016/s2214-109x(22)00372-2.Peer-Reviewed Original ResearchMeSH KeywordsAntitubercular AgentsCD4 Lymphocyte CountCost-Benefit AnalysisHIV InfectionsHumansIsoniazidTanzaniaTuberculosisConceptsIsoniazid preventive therapyCD4 cell countAntiretroviral therapyCell countART cohortAverage CD4 cell countHigher CD4 cell countsLarge HIV treatment programHealth impactsTuberculosis preventive treatmentHIV treatment programsLifetime costsIncremental lifetime costLifetime health benefitsCourse of infectionGreater health gainsLong-term healthART initiationTreat guidelinesHIV cohortPreventive therapyTuberculosis riskUS National InstitutesHIV programsSubgroup analysisNational survey in South Africa reveals high tuberculosis prevalence among previously treated people
Marx FM, Hesseling AC, Martinson N, Theron G, Cohen T. National survey in South Africa reveals high tuberculosis prevalence among previously treated people. The Lancet Infectious Diseases 2022, 22: 1273. PMID: 36029778, DOI: 10.1016/s1473-3099(22)00494-7.Peer-Reviewed Original ResearchExcess 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 menNeighbourhood prevalence-to-notification ratios for adult bacteriologically-confirmed tuberculosis reveals hotspots of underdiagnosis in Blantyre, Malawi
Khundi M, Carpenter JR, Corbett EL, Feasey HRA, Soko RN, Nliwasa M, Twabi H, Chiume L, Burke RM, Horton KC, Dodd PJ, Cohen T, MacPherson P. Neighbourhood prevalence-to-notification ratios for adult bacteriologically-confirmed tuberculosis reveals hotspots of underdiagnosis in Blantyre, Malawi. PLOS ONE 2022, 17: e0268749. PMID: 35605004, PMCID: PMC9126376, DOI: 10.1371/journal.pone.0268749.Peer-Reviewed Original ResearchMeSH KeywordsAdultBayes TheoremHumansMalawiMass ScreeningMycobacterium tuberculosisPrevalenceSputumTuberculosisConceptsCase notification ratesPrevalence surveyNotification ratioNeighbourhood prevalenceTB case notification ratesXpert MTB/RIFCase-finding interventionsTrue disease burdenChest X-ray screeningTB prevalence surveyTB surveillance systemMTB/RIFDiagnosis of tuberculosisSputum smear microscopyTB clinicTB patientsRespiratory infectionsTB prevalenceDisease burdenNotification ratesSmear microscopyX-ray screeningTuberculosisPrevalenceUrban tuberculosisA crowd of BashTheBug volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates
Fowler P, Wright C, Spiers H, Zhu T, Baeten E, Hoosdally S, Cruz A, Roohi A, Kouchaki S, Walker T, Peto T, Miller G, Lintott C, Clifton D, Crook D, Walker A, Barilar I, Battaglia S, Borroni E, Brandao A, Brankin A, Cabibbe A, Carter J, Cirillo D, Claxton P, Clifton D, Cohen T, Coronel J, Crook D, Earle S, Escuyer V, Ferrazoli L, Fowler P, Gao G, Gardy J, Gharbia S, Ghisi K, Ghodousi A, Cruz A, Grazian C, Guthrie J, He W, Hoffmann H, Hoosdally S, Hunt M, Iqbal Z, Ismail N, Jarrett L, Joseph L, Jou R, Kambli P, Knaggs J, Koch A, Kohlerschmidt D, Kouchaki S, Lachapelle A, Lalvani A, Lapierre S, Laurenson I, Letcher B, Lin W, Liu C, Liu D, Malone K, Mandal A, Matias D, Meintjes G, Mendes F, Merker M, Mihalic M, Millard J, Miotto P, Mistry N, Moore D, Dreyer V, Chetty D, Musser K, Ngcamu D, Nhung H, Grandjean L, Nilgiriwala K, Nimmo C, Okozi N, Oliveira R, Omar S, Paton N, Peto T, Pinhata J, Plesnik S, Puyen Z, Rabodoarivelo M, Rakotosamimanana N, Rancoita P, Rathod P, Robinson E, Rodger G, Rodrigues C, Rodwell T, Roohi A, Santos-Lazaro D, Shah S, Kohl T, Smith G, Solano W, Spitaleri A, Supply P, Steyn A, Surve U, Tahseen S, Thuong N, Thwaites G, Todt K, Trovato A, Utpatel C, Van Rie A, Vijay S, Walker T, Walker A, Warren R, Werngren J, Groenheit R, Wijkander M, Wilkinson R, Wilson D, Wintringer P, Xiao Y, Yang Y, Yanlin Z, Yao S, Zhu B, Niemann S, O'Donnell M. A crowd of BashTheBug volunteers reproducibly and accurately measure the minimum inhibitory concentrations of 13 antitubercular drugs from photographs of 96-well broth microdilution plates. ELife 2022, 11: e75046. PMID: 35588296, PMCID: PMC9286738, DOI: 10.7554/elife.75046.Peer-Reviewed Original ResearchMeSH KeywordsAntitubercular AgentsHumansMicrobial Sensitivity TestsMycobacterium tuberculosisTuberculosisVolunteersConceptsMinimum inhibitory concentrationIncreasing prevalence of resistanceBroth microdilution platesAntibiotic susceptibility testingPrevalence of resistanceInhibitory concentrationPanel of antibioticsClinical samplesSusceptibility testingMicrodilution platesDilution platingTreatment outcomesIncreased prevalenceAntitubercular drugsAntibioticsInhibited growthDrugCitizen science platformRespiratory diseaseLaboratory scientistsVolunteersPre-determined concentrationsPhylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis
Yang C, Sobkowiak B, Naidu V, Codreanu A, Ciobanu N, Gunasekera KS, Chitwood MH, Alexandru S, Bivol S, Russi M, Havumaki J, Cudahy P, Fosburgh H, Allender CJ, Centner H, Engelthaler DM, Menzies NA, Warren JL, Crudu V, Colijn C, Cohen T. Phylogeography and transmission of M. tuberculosis in Moldova: A prospective genomic analysis. PLOS Medicine 2022, 19: e1003933. PMID: 35192619, PMCID: PMC8903246, DOI: 10.1371/journal.pmed.1003933.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisDrug-resistant M. tuberculosisM. tuberculosis strainsPutative transmission clustersM. tuberculosisTransmission clustersMultidrug-resistant M. tuberculosis strainsTuberculosis strainsMultiple M. tuberculosis strainsCulture-positive TB casesLocal transmissionMDR-TB epidemicDrug-susceptible tuberculosisDrug resistance mutationsDrug resistance profilesUrgency of interventionTB casesDemographic dataNew casesTuberculosisInadequate treatmentNatural historyResistance mutationsBeijing lineageMycobacterium tuberculosisSpatially targeted digital chest radiography to reduce tuberculosis in high-burden settings: A study of adaptive decision making
de Villiers AK, Dye C, Yaesoubi R, Cohen T, Marx FM. Spatially targeted digital chest radiography to reduce tuberculosis in high-burden settings: A study of adaptive decision making. Epidemics 2022, 38: 100540. PMID: 35093849, PMCID: PMC8983993, DOI: 10.1016/j.epidem.2022.100540.Peer-Reviewed Original ResearchConceptsHigh-burden settingsTB casesTB prevalenceChest radiographyAdditional TB casesCase-finding yieldTB prevalence estimatesHigh-burden populationsCommunity-randomized trialNumber of screeningsTB controlXpert UltraScreening roundNotification ratesPrevalence estimatesTuberculosisPrevalenceDigital chest radiographyScreeningTrialsInterventionRadiography
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