2023
Transmission 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 countries
2022
National 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 ResearchNeighbourhood 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 tuberculosis
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 tuberculosisTuberculosisMoldovaIncidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis
Cords O, Martinez L, Warren JL, O’Marr J, Walter KS, Cohen T, Zheng J, Ko AI, Croda J, Andrews JR. Incidence and prevalence of tuberculosis in incarcerated populations: a systematic review and meta-analysis. The Lancet Public Health 2021, 6: e300-e308. PMID: 33765455, PMCID: PMC8168455, DOI: 10.1016/s2468-2667(21)00025-6.Peer-Reviewed Original ResearchConceptsPrevalence of tuberculosisIncidence of tuberculosisM tuberculosis infectionIncidence rate ratiosTuberculosis infectionGeneral populationSystematic reviewSouth-East Asia RegionIncarcerated populationsPopulation-level incidenceMycobacterium tuberculosis infectionRate ratioTuberculosis Control ProgrammeLILACS electronic databasesWHO Eastern Mediterranean RegionWHO South-East Asia RegionWeb of KnowledgeCohort studyUS National InstitutesSubgroup analysisPooled estimatesHigh riskElectronic databasesPreventive interventionsTuberculosis
2020
Smoking and HIV associated with subclinical tuberculosis: analysis of a population-based prevalence survey
Gunasekera K, Cohen T, Gao W, Ayles H, Godfrey-Faussett P, Claassens M. Smoking and HIV associated with subclinical tuberculosis: analysis of a population-based prevalence survey. The International Journal Of Tuberculosis And Lung Disease 2020, 24: 340-346. PMID: 32228765, DOI: 10.5588/ijtld.19.0387.Peer-Reviewed Original ResearchConceptsActive TBPrevalence surveyPopulation-based prevalence surveyCurrent tobacco smokingTypical symptomsHIV-positive statusTuberculosis prevalence surveyPrevalence survey dataSubclinical tuberculosisPositive TBCrude prevalenceTobacco smokingEpidemiological burdenPrevalent casesReduction TrialSubclinical TBMedical variablesSecondary analysisEstimate associationsSouth African communitySymptomsHIVSmokingTuberculosisDiseaseComparative Modeling of Tuberculosis Epidemiology and Policy Outcomes in California
Menzies NA, Parriott A, Shrestha S, Dowdy DW, Cohen T, Salomon JA, Marks SM, Hill AN, Winston CA, Asay GR, Barry P, Readhead A, Flood J, Kahn JG, Shete PB. Comparative Modeling of Tuberculosis Epidemiology and Policy Outcomes in California. American Journal Of Respiratory And Critical Care Medicine 2020, 201: 356-365. PMID: 31626560, PMCID: PMC7464931, DOI: 10.1164/rccm.201907-1289oc.Peer-Reviewed Original ResearchConceptsTB incidenceTB casesAdditional interventionsTuberculosis epidemiologyPublic health prioritizationTreatment of LTBIInfection control interventionsPotential intervention effectsLTBI testingTB servicesLTBI diagnosisLTBI prevalenceAverage annual declineEpidemiologic projectionsSustained reductionTreatment interventionsControl interventionsTB determinantsDefinitive dataIntervention effectsAnnual declineLocal transmissionIncidenceLTBIIntervention
2019
Notification of relapse and other previously treated tuberculosis in the 52 health districts of South Africa
Marx F, Cohen T, Lombard C, Hesseling A, Dlamini S, Beyers N, Naidoo P. Notification of relapse and other previously treated tuberculosis in the 52 health districts of South Africa. The International Journal Of Tuberculosis And Lung Disease 2019, 23: 891-899. PMID: 31533878, DOI: 10.5588/ijtld.18.0609.Peer-Reviewed Original ResearchConceptsSouth African health districtTB casesCase notification ratesHealth districtTB burdenNotification ratesHigh case notification ratesHIV co-infection rateHuman immunodeficiency virus (HIV) prevalenceTB case notification ratesAntenatal HIV prevalenceSecondary preventive therapyDrug-susceptible tuberculosisNew TB casesCo-infection rateTreatment history informationPreventive therapyMultivariable analysisHIV prevalenceSouth African districtPatient categoriesRelapseTuberculosisTreatment monitoringVirus prevalence
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 resultsMortalityTuberculosis 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
Polyclonal Pulmonary Tuberculosis Infections and Risk for Multidrug Resistance, Lima, Peru - Volume 23, Number 11—November 2017 - Emerging Infectious Diseases journal - CDC
Nathavitharana RR, Shi CX, Chindelevitch L, Calderon R, Zhang Z, Galea JT, Contreras C, Yataco R, Lecca L, Becerra MC, Murray MB, Cohen T. Polyclonal Pulmonary Tuberculosis Infections and Risk for Multidrug Resistance, Lima, Peru - Volume 23, Number 11—November 2017 - Emerging Infectious Diseases journal - CDC. Emerging Infectious Diseases 2017, 23: 1887-1890. PMID: 29048297, PMCID: PMC5652442, DOI: 10.3201/eid2311.170077.Peer-Reviewed Original ResearchConceptsTreatment of tuberculosisHost Mycobacterium tuberculosis diversityMultidrug-resistant TBInfectious Diseases journal - CDCPulmonary TB patientsPulmonary tuberculosis infectionTB patientsTuberculosis infectionPolyclonal infectionsSimple infectionMultidrug resistanceInfectionPatientsTuberculosisPrevalenceDiagnosis
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 implementationSettingRegimensPrevalenceHigh burden of prevalent tuberculosis among previously treated people in Southern Africa suggests potential for targeted control interventions
Marx FM, Floyd S, Ayles H, Godfrey-Faussett P, Beyers N, Cohen T. High burden of prevalent tuberculosis among previously treated people in Southern Africa suggests potential for targeted control interventions. European Respiratory Journal 2016, 48: 1227-1230. PMID: 27390274, PMCID: PMC5512114, DOI: 10.1183/13993003.00716-2016.Peer-Reviewed Original ResearchConceptsHigh-burden settingsHigh TB prevalenceRecurrent tuberculosisExogenous reinfectionPrevalent tuberculosisTB prevalenceSuccessful treatmentHigh burdenImportant underlying mechanismHigh riskHigh incidenceControl interventionsTargeted interventionsTuberculosisUnderlying mechanismOne-thirdInterventionBurdenCape TownIndividualsReinfectionPrevalenceIncidenceDiseaseSettingUse 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 settingsLevels
2015
The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis
Knight GM, Colijn C, Shrestha S, Fofana M, Cobelens F, White RG, Dowdy DW, Cohen T. The Distribution of Fitness Costs of Resistance-Conferring Mutations Is a Key Determinant for the Future Burden of Drug-Resistant Tuberculosis: A Model-Based Analysis. Clinical Infectious Diseases 2015, 61: s147-s154. PMID: 26409276, PMCID: PMC4583567, DOI: 10.1093/cid/civ579.Peer-Reviewed Original ResearchHIV burden in men who have sex with men: a prospective cohort study 2007–2012
Jia Z, Huang X, Wu H, Zhang T, Li N, Ding P, Sun Y, Liu Z, Wei F, Zhang H, Jiao Y, Ji Y, Zhang Y, Guo C, Li W, Mou D, Xia W, Li Z, Chen D, Yan H, Chen X, Zhao J, Meyers K, Cohen T, Mayer K, Salomon JA, Lu Z, Dye C. HIV burden in men who have sex with men: a prospective cohort study 2007–2012. Scientific Reports 2015, 5: 11205. PMID: 26135810, PMCID: PMC5393284, DOI: 10.1038/srep11205.Peer-Reviewed Original ResearchConceptsHIV infectionHIV-negative MSMProspective cohort studyHIV incidence ratesIntensive preventive interventionIncident HIVCohort studyHIV burdenHIV incidenceIncident casesRisk factorsIncidence rateEarly treatmentPrevalent casesChinese MSMHIVPreventive interventionsInfectionMSMFollowPerfect complianceMenEnrollmentSyphilisCohortHow could preventive therapy affect the prevalence of drug resistance? Causes and consequences
Kunkel A, Colijn C, Lipsitch M, Cohen T. How could preventive therapy affect the prevalence of drug resistance? Causes and consequences. Philosophical Transactions Of The Royal Society B Biological Sciences 2015, 370: 20140306. PMID: 25918446, PMCID: PMC4424438, DOI: 10.1098/rstb.2014.0306.Peer-Reviewed Original ResearchConceptsPreventative therapyDrug resistanceDrug-sensitive pathogensProphylactic antimicrobial therapyLong-term prevalenceSmall pilot studyActive diseaseOverall prevalenceAntimicrobial therapyPrevalencePilot studyTherapyPopulation-level changesPotential population-level effectsDirect effectLevel of coveragePopulation-level effectsHIVTuberculosisMalariaDiseaseCare
2014
Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection
Plazzotta G, Cohen T, Colijn C. Magnitude and sources of bias in the detection of mixed strain M. tuberculosis infection. Journal Of Theoretical Biology 2014, 368: 67-73. PMID: 25553967, PMCID: PMC7011203, DOI: 10.1016/j.jtbi.2014.12.009.Peer-Reviewed Original ResearchConceptsMixed infectionsM. tuberculosis infectionIncidence of TBOutcome of treatmentPopulation-level interventionsFraction of casesTuberculosis infectionMinority strainsActual prevalenceInfected individualsInfectionStudy designMycobacterium tuberculosisPrevalenceSputumTuberculosisDistinct strainsDifferent strainsSources of biasPrevious studiesPatientsSpecific reasonsIncidenceIndividualsAge-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 riskHow can mathematical models advance tuberculosis control in high HIV prevalence settings?
Houben RM, Dowdy DW, Vassall A, Cohen T, Nicol MP, Granich RM, Shea JE, Eckhoff P, Dye C, Kimerling ME, White RG, . How can mathematical models advance tuberculosis control in high HIV prevalence settings? The International Journal Of Tuberculosis And Lung Disease 2014, 18: 509-514. PMID: 24903784, PMCID: PMC4436821, DOI: 10.5588/ijtld.13.0773.Peer-Reviewed Original ResearchConceptsHigh HIV prevalence settingsHIV prevalence settingsTB-HIVTuberculosis controlPrevalence settingsHigh human immunodeficiency virus (HIV) prevalenceHuman immunodeficiency virus (HIV) prevalenceTB ModellingHealth policy makersDifficult diagnosisDisease progressionHigh riskHigh mortalityHealth systemNatural progressionVirus prevalencePublic healthProgressionMortalityPrevalenceSettingAnalysis ConsortiumDiagnosisExpert discussion