2024
The impact of COVID-19 national lockdowns on drug-resistant tuberculosis in KwaZulu-Natal, South Africa: A spatial analysis
Harrington K, Gandhi N, Shah N, Naidoo K, Auld S, Andrews J, Brust J, Lutchminarain K, Coe M, Willis F, Campbell A, Cohen T, Jenness S, Waller L, Investigators O. The impact of COVID-19 national lockdowns on drug-resistant tuberculosis in KwaZulu-Natal, South Africa: A spatial analysis. Annals Of Epidemiology 2024, 97: 44-51. PMID: 39038747, PMCID: PMC11408097, DOI: 10.1016/j.annepidem.2024.07.044.Peer-Reviewed Original ResearchKwaZulu-Natal ProvinceTB diagnosisDrug resistanceBayesian conditional autoregressive modelProspective cohort studyKwaZulu-NatalCOVID-19 national lockdownDrug-resistant tuberculosisRate of diagnosisCOVID-19 mitigation strategiesStatistics South AfricaSpatial analysisSpatial distributionMunicipal characteristicsCohort studyDR-TBNotification ratesTB notificationsSouth AfricaSurface mappingRate of casesRelative-riskCOVID-19Conditional autoregressive modelSpatial correlation
2022
Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods
You S, Chitwood MH, Gunasekera KS, Crudu V, Codreanu A, Ciobanu N, Furin J, Cohen T, Warren JL, Yaesoubi R. Predicting resistance to fluoroquinolones among patients with rifampicin-resistant tuberculosis using machine learning methods. PLOS Digital Health 2022, 1: e0000059. PMID: 36177394, PMCID: PMC9518704, DOI: 10.1371/journal.pdig.0000059.Peer-Reviewed Original ResearchDrug susceptibility testXpert MTB/RIFMachine learning-based modelsLearning-based modelsMachine learning methodsRifampicin-resistant tuberculosisTime of diagnosisRifampin-resistant tuberculosisMTB/RIFNeural network modelLearning methodsNetwork modelMulti-drug resistant tuberculosisNational TB surveillanceDrug-resistant tuberculosisOptimism-corrected areaSelection of antibioticsAnti-TB agentsDistrict-level prevalenceLow-resource settingsPatient characteristicsResistant tuberculosisTB surveillanceAppropriate treatmentDST results
2021
Evolution and emergence of multidrug-resistant Mycobacterium tuberculosis in Chisinau, Moldova
Brown TS, Eldholm V, Brynildsrud O, Osnes M, Levy N, Stimson J, Colijn C, Alexandru S, Noroc E, Ciobanu N, Crudu V, Cohen T, Mathema B. Evolution and emergence of multidrug-resistant Mycobacterium tuberculosis in Chisinau, Moldova. Microbial Genomics 2021, 7: 000620. PMID: 34431762, PMCID: PMC8549355, DOI: 10.1099/mgen.0.000620.Peer-Reviewed Original ResearchConceptsDrug-resistant TB casesMultidrug-resistant Mycobacterium tuberculosisDrug-resistant tuberculosisDrug resistance mutationsPopulation size expansionPublic health practiceSoviet UnionSocial turmoilTB patientsTB casesTB controlRepublic of MoldovaInpatient hospitalizationMigration historyInpatient treatmentEastern EuropeNational guidelinesEpidemiological historyResistance mutationsHealth practicesGenomic surveillance effortsCapital cityMycobacterium tuberculosisTuberculosisMoldova
2018
Trends in C-Reactive Protein, D-Dimer, and Fibrinogen during Therapy for HIV-Associated Multidrug-Resistant Tuberculosis.
Cudahy PGT, Warren JL, Cohen T, Wilson D. Trends in C-Reactive Protein, D-Dimer, and Fibrinogen during Therapy for HIV-Associated Multidrug-Resistant Tuberculosis. American Journal Of Tropical Medicine And Hygiene 2018, 99: 1336-1341. PMID: 30226135, PMCID: PMC6221241, DOI: 10.4269/ajtmh.18-0322.Peer-Reviewed Original ResearchConceptsC-reactive proteinMulti-drug resistant tuberculosisD-dimerMedian C-reactive proteinSerum C-reactive proteinHigher baseline fibrinogenMDR-TB therapyHIV-positive adultsDrug-resistant tuberculosisHIV-positive participantsHigher CRP concentrationsEarly treatment modificationBaseline fibrinogenTreatment initiationResistant tuberculosisCRP concentrationsTreatment modificationTreatment outcomesTreatment responseHigh riskHigh mortalityNormal levelsOlder ageEarly responseFibrinogen
2017
Population implications of the use of bedaquiline in people with extensively drug-resistant tuberculosis: are fears of resistance justified?
Kunkel A, Furin J, Cohen T. Population implications of the use of bedaquiline in people with extensively drug-resistant tuberculosis: are fears of resistance justified? The Lancet Infectious Diseases 2017, 17: e429-e433. PMID: 28533094, DOI: 10.1016/s1473-3099(17)30299-2.Peer-Reviewed Original ResearchConceptsUse of bedaquilineDrug-resistant tuberculosisXDR tuberculosisBedaquiline resistanceCohort study resultsMultidrug-resistant tuberculosisNew combination regimensHigh mortality rateFears of resistanceInfected contactsCombination regimensDrug combinationsPatientsEquivalent outcomesMortality rateAntituberculosis drugsBedaquilineTuberculosisNovel drugsDrug bedaquilineDrugsDiseasePopulation implicationsResistance concernsGreat needA Multistrain Mathematical Model To Investigate the Role of Pyrazinamide in the Emergence of Extensively Drug-Resistant Tuberculosis
Fofana MO, Shrestha S, Knight GM, Cohen T, White RG, Cobelens F, Dowdy DW. A Multistrain Mathematical Model To Investigate the Role of Pyrazinamide in the Emergence of Extensively Drug-Resistant Tuberculosis. Antimicrobial Agents And Chemotherapy 2017, 61: 10.1128/aac.00498-16. PMID: 27956422, PMCID: PMC5328532, DOI: 10.1128/aac.00498-16.Peer-Reviewed Original ResearchMeSH KeywordsAntitubercular AgentsBayes TheoremBiological AvailabilityComputer SimulationDrug Administration ScheduleDrug Resistance, Multiple, BacterialExtensively Drug-Resistant TuberculosisFluoroquinolonesHumansMicrobial Sensitivity TestsModels, StatisticalMycobacterium tuberculosisPyrazinamideRifampinTuberculosis, PulmonaryConceptsCompanion drugsExtensively Drug-Resistant TuberculosisSecond-line treatmentFirst-line treatmentSecond-line regimensDrug-resistant tuberculosisUse of pyrazinamideExtensive drug resistanceDrug resistance dataEmergence of strainsEmergence of mutationsXDR-TBSequential regimensHIV infectionAlternative drugsResistance amplificationPyrazinamide resistanceProlonged treatmentCombination antimicrobialsDrug resistanceInfectious diseasesPrevalenceProportion of simulationsAppropriate useRegimens
2016
Second line drug susceptibility testing to inform the treatment of rifampin-resistant tuberculosis: a quantitative perspective
Kendall EA, Cohen T, Mitnick CD, Dowdy DW. Second line drug susceptibility testing to inform the treatment of rifampin-resistant tuberculosis: a quantitative perspective. International Journal Of Infectious Diseases 2016, 56: 185-189. PMID: 28007660, PMCID: PMC5576040, DOI: 10.1016/j.ijid.2016.12.010.Peer-Reviewed Original ResearchConceptsSecond-line drug susceptibility testingRifampin-resistant tuberculosisDrug susceptibility testingSecond-line drug resistanceDrug resistanceSusceptibility testingHigh-burden settingsSecond-line drugsDrug-resistant tuberculosisEffective regimensTreatment failureTreatment outcomesSmall incremental costEpidemiologic benefitsResistance amplificationPatientsTuberculosisIncremental costMost settingsWidespread implementationSettingRegimensPrevalenceRapid Drug Susceptibility Testing of Drug-Resistant Mycobacterium tuberculosis Isolates Directly from Clinical Samples by Use of Amplicon Sequencing: a Proof-of-Concept Study
Colman RE, Anderson J, Lemmer D, Lehmkuhl E, Georghiou SB, Heaton H, Wiggins K, Gillece JD, Schupp JM, Catanzaro DG, Crudu V, Cohen T, Rodwell TC, Engelthaler DM. Rapid Drug Susceptibility Testing of Drug-Resistant Mycobacterium tuberculosis Isolates Directly from Clinical Samples by Use of Amplicon Sequencing: a Proof-of-Concept Study. Journal Of Clinical Microbiology 2016, 54: 2058-2067. PMID: 27225403, PMCID: PMC4963505, DOI: 10.1128/jcm.00535-16.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overChildChild, PreschoolFemaleGenotyping TechniquesHigh-Throughput Nucleotide SequencingHumansMaleMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisPharmaceutical PreparationsPilot ProjectsSequence Analysis, DNASpecimen HandlingSputumTime FactorsYoung AdultConceptsDrug-resistant tuberculosisPatient sputum samplesDrug resistance profilesSputum samplesDrug-resistant Mycobacterium tuberculosis isolatesPhenotypic drug susceptibility testing resultsDrug susceptibility testing resultsEvidence-based treatment plansResistance profilesMajor global health concernRapid drug susceptibility testingMycobacterium tuberculosis isolatesNext-generation sequencingClinical samplesAmplification of resistanceDrug susceptibility testingTargeted Next-Generation SequencingMycobacterium tuberculosis DNAGlobal health concernSusceptibility testing resultsSame clinical samplePhenotypic DSTInfectious causesTreatment outcomesTuberculosis isolatesUse of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya
Jezmir J, Cohen T, Zignol M, Nyakan E, Hedt-Gauthier BL, Gardner A, Kamle L, Injera W, Carter EJ. Use of Lot Quality Assurance Sampling to Ascertain Levels of Drug Resistant Tuberculosis in Western Kenya. PLOS ONE 2016, 11: e0154142. PMID: 27167381, PMCID: PMC4864281, DOI: 10.1371/journal.pone.0154142.Peer-Reviewed Original ResearchConceptsMDR-TBDrug resistanceResistant tuberculosisLot Quality Assurance Sampling methodologyMulti-drug resistant tuberculosisPositive TB patientsDrug resistance surveillanceDrug-resistant tuberculosisTB drug resistanceRural settingsPoly-resistant strainsTB patientsWestern KenyaLot Quality AssuranceLow prevalencePatientsResistance surveillancePrevalenceTuberculosisLQASSettingLow levelsDifferent geographic settingsUrban settingsLevelsAssessing the utility of Xpert® MTB/RIF as a screening tool for patients admitted to medical wards in South Africa
Heidebrecht CL, Podewils LJ, Pym AS, Cohen T, Mthiyane T, Wilson D. Assessing the utility of Xpert® MTB/RIF as a screening tool for patients admitted to medical wards in South Africa. Scientific Reports 2016, 6: 19391. PMID: 26786396, PMCID: PMC4726405, DOI: 10.1038/srep19391.Peer-Reviewed Original ResearchMeSH KeywordsAdolescentAdultAgedAged, 80 and overCoinfectionDrug Resistance, BacterialFemaleHIV InfectionsHumansMaleMass ScreeningMicrobial Sensitivity TestsMiddle AgedMycobacterium tuberculosisNucleic Acid Amplification TechniquesReproducibility of ResultsRifampinSouth AfricaTuberculosis, Multidrug-ResistantYoung AdultConceptsChest X-rayMTB/RIFMedical wardsScreening toolAdditional TB casesInfection control actionsUtility of GeneXpertTB/HIVConsecutive adult patientsProportion of patientsRifampicin-resistant tuberculosisDrug-resistant tuberculosisLarge public hospitalTB diseaseAdult patientsStandard careTB casesTB screeningMedical admissionsMedical chartsHospital inpatientsSputum specimensGeneXpertPatientsRifampicin resistance
2014
On the spread and control of MDR-TB epidemics: An examination of trends in anti-tuberculosis drug resistance surveillance data
Cohen T, Jenkins HE, Lu C, McLaughlin M, Floyd K, Zignol M. On the spread and control of MDR-TB epidemics: An examination of trends in anti-tuberculosis drug resistance surveillance data. Drug Resistance Updates 2014, 17: 105-123. PMID: 25458783, PMCID: PMC4358299, DOI: 10.1016/j.drup.2014.10.001.Peer-Reviewed Original ResearchConceptsMDR-TBTB casesResistant tuberculosisAbsolute burdenSurveillance dataMDR-TB epidemicDrug-resistant TBMultidrug-resistant tuberculosisDrug-resistant tuberculosisNotified TB casesResistance surveillance dataSufficient surveillance dataWorld Health OrganizationBurden settingsTuberculosis controlUnadjusted analysesSignificant linear trendSurveillance indicatorsRobust surveillance systemHealth OrganizationTuberculosisBurdenSurveillance systemSettingLinear trend
2013
Bayesian 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
2012
Modeling the Dynamic Relationship Between HIV and the Risk of Drug-Resistant Tuberculosis
Sergeev R, Colijn C, Murray M, Cohen T. Modeling the Dynamic Relationship Between HIV and the Risk of Drug-Resistant Tuberculosis. Science Translational Medicine 2012, 4: 135ra67. PMID: 22623743, PMCID: PMC3387814, DOI: 10.1126/scitranslmed.3003815.Peer-Reviewed Original ResearchConceptsMultidrug-resistant TBDrug-resistant tuberculosisDrug-resistant TBHIV-seropositive individualsHIV statusTB patientsLatent Mycobacterium tuberculosis infectionIndividual HIV statusIncident HIV infectionMultidrug-resistant tuberculosisMycobacterium tuberculosis infectionEffects of HIVCross-sectional studyDrug-resistant formsRise of HIVIndividual-level associationsAcquisition of resistanceAverage CD4HIV infectionResistance-conferring mutationsTB controlTuberculosis infectionResistant tuberculosisTB drugsHIV epidemicLinking Surveillance with Action against Drug-Resistant Tuberculosis
Cohen T, Manjourides J, Hedt-Gauthier B. Linking Surveillance with Action against Drug-Resistant Tuberculosis. American Journal Of Respiratory And Critical Care Medicine 2012, 186: 399-401. PMID: 22592806, PMCID: PMC3443807, DOI: 10.1164/rccm.201203-0394pp.Peer-Reviewed Original ResearchConceptsMultidrug-resistant tuberculosisForms of TBDrug-resistant TBManagement of patientsDrug-resistant tuberculosisSecond-line drugsEffective public health responseDrug susceptibility testingPublic health responseQuality-assured treatmentMDRTB treatmentIncident casesHigh burdenProgrammatic dataHealth responseDrug resistanceSusceptibility testingImproved surveillance methodsPopulation subgroupsSurveillance methodsSurveillance activitiesTuberculosisClear roleTreatmentRecent global estimates
2011
Models to understand the population-level impact of mixed strain M. tuberculosis infections
Sergeev R, Colijn C, Cohen T. Models to understand the population-level impact of mixed strain M. tuberculosis infections. Journal Of Theoretical Biology 2011, 280: 88-100. PMID: 21514304, PMCID: PMC3111980, DOI: 10.1016/j.jtbi.2011.04.011.Peer-Reviewed Original ResearchConceptsDrug-resistant strainsMixed strain infectionsStrain infectionDrug-sensitive tuberculosisDrug-resistant tuberculosisM. tuberculosis infectionLower basic reproductive numberDrug-resistant infectionsTuberculosis patientsTuberculosis infectionTreatment successDrug-resistant bacteriaFuture burdenLong-term effectsStrain-specific differencesDrug resistanceInfectionPopulation-level impactTuberculosisM. tuberculosisMixed infectionsMycobacterium tuberculosisBasic reproductive numberCo-infected hostsSmall subpopulation
2010
Development of Extensively Drug-resistant Tuberculosis during Multidrug-resistant Tuberculosis Treatment
Shin SS, Keshavjee S, Gelmanova IY, Atwood S, Franke MF, Mishustin SP, Strelis AK, Andreev YG, Pasechnikov AD, Barnashov A, Tonkel TP, Cohen T. Development of Extensively Drug-resistant Tuberculosis during Multidrug-resistant Tuberculosis Treatment. American Journal Of Respiratory And Critical Care Medicine 2010, 182: 426-432. PMID: 20413630, PMCID: PMC2921603, DOI: 10.1164/rccm.200911-1768oc.Peer-Reviewed Original ResearchConceptsMDR-TB treatmentXDR-TBDrug-resistant tuberculosisMultidrug-resistant (MDR) TBMDR-TB treatment programmeExtensively Drug-Resistant TuberculosisMultidrug-resistant tuberculosis treatmentCox proportional hazards modelDevelopment of XDRMDR-TB therapyTB treatment servicesAmplification of resistanceProportional hazards modelThreefold increaseMDR-TBCavitary lesionsConsecutive patientsAppropriate therapyClinical outcomesTreatment adherenceTuberculosis treatmentInjectable antibioticsTimely initiationPrescribed drugsRetrospective analysis
2009
Extensively Drug‐Resistant Tuberculosis and HIV/AIDS
Murray M, Cohen T. Extensively Drug‐Resistant Tuberculosis and HIV/AIDS. 2009, 253-275. DOI: 10.1002/9783527627905.ch10.Peer-Reviewed Original Research
2008
Are Survey-Based Estimates of the Burden of Drug Resistant TB Too Low? Insight from a Simulation Study
Cohen T, Colijn C, Finklea B, Wright A, Zignol M, Pym A, Murray M. Are Survey-Based Estimates of the Burden of Drug Resistant TB Too Low? Insight from a Simulation Study. PLOS ONE 2008, 3: e2363. PMID: 18523659, PMCID: PMC2408555, DOI: 10.1371/journal.pone.0002363.Peer-Reviewed Original ResearchConceptsResistant tuberculosisIncident casesTotal burdenDrug-resistant TBDrug-resistant tuberculosisSecond-line antibioticsDrug treatment regimensDrug sensitivity testingDrug-resistant strainsBurden of resistanceEmergence of tuberculosisResistant TBTreatment regimensPrevalent casesWorldwide burdenIntroduction of interventionsRoutine surveillanceSurveillance strategiesDrug resistanceTuberculosisLaboratory capacityMycobacterium tuberculosisSensitivity testingTuberculosis modelBurdenChallenges in Estimating the Total Burden of Drug-resistant Tuberculosis
Cohen T, Colijn C, Wright A, Zignol M, Pym A, Murray M. Challenges in Estimating the Total Burden of Drug-resistant Tuberculosis. American Journal Of Respiratory And Critical Care Medicine 2008, 177: 1302-1306. PMID: 18369201, PMCID: PMC2720088, DOI: 10.1164/rccm.200801-175pp.Peer-Reviewed Original ResearchConceptsDrug-resistant tuberculosisDrug resistance surveillanceHIV/TB coinfectionAnti-Tuberculosis Drug Resistance SurveillanceResistance surveillanceSentinel site surveillanceBurden of tuberculosisMultidrug-resistant diseaseMultidrug-resistant tuberculosisTB control programsTB coinfectionTB casesHigh burdenMethodologic obstaclesSurveillance studyNew casesTotal burdenTuberculosisLaboratory capacityBurdenSurveillanceControl programsDiagnostic technologiesRecent recognitionTrue extent
2004
Isoniazid Resistance and the Future of Drug-Resistant Tuberculosis
Cohen T, Becerra MC, Murray MB. Isoniazid Resistance and the Future of Drug-Resistant Tuberculosis. Microbial Drug Resistance 2004, 10: 280-285. PMID: 15650371, PMCID: PMC2652757, DOI: 10.1089/mdr.2004.10.280.Peer-Reviewed Original ResearchConceptsIsoniazid resistanceDrug resistanceDrug-resistant tuberculosisDrug-resistant casesResistance-conferring mutationsFrequency of resistanceMycobacterium tuberculosisAntibiotic resistancePrudent useTuberculosisDeleterious effectsReproductive potentialChromosomal mutationsMutationsSpecific measuresPrevalence