2023
Development 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
2021
Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns
Havumaki J, Cohen T, Zhai C, Miller JC, Guikema SD, Eisenberg MC, Zelner J. Protective impacts of household-based tuberculosis contact tracing are robust across endemic incidence levels and community contact patterns. PLOS Computational Biology 2021, 17: e1008713. PMID: 33556077, PMCID: PMC7895355, DOI: 10.1371/journal.pcbi.1008713.Peer-Reviewed Original ResearchConceptsTuberculosis burdenCommunity transmissionGlobal tuberculosis control targetsSustained community transmissionHigh-incidence settingsHigh disease burdenTuberculosis contact tracingLow tuberculosis burdenHousehold contactsHousehold transmissionDisease burdenVaried incidenceContact patternsIncidence levelsProtective impactEpidemiological settingsInfected individualsNew casesProtective benefitsContact tracingCommunity contactsSuch interventionsInterventionBurdenProactive caseDevelopment 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
Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences
Walter KS, Colijn C, Cohen T, Mathema B, Liu Q, Bowers J, Engelthaler DM, Narechania A, Lemmer D, Croda J, Andrews JR. Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences. Microbial Genomics 2020, 6: mgen000418. PMID: 32735210, PMCID: PMC7641424, DOI: 10.1099/mgen.0.000418.Peer-Reviewed Original ResearchYield, Efficiency, and Costs of Mass Screening Algorithms for Tuberculosis in Brazilian Prisons
da Silva Santos A, de Oliveira R, Lemos EF, Lima F, Cohen T, Cords O, Martinez L, Gonçalves C, Ko A, Andrews JR, Croda J. Yield, Efficiency, and Costs of Mass Screening Algorithms for Tuberculosis in Brazilian Prisons. Clinical Infectious Diseases 2020, 72: 771-777. PMID: 32064514, PMCID: PMC7935388, DOI: 10.1093/cid/ciaa135.Peer-Reviewed Original ResearchConceptsXpert MTB/RIFMTB/RIFChest radiographySputum Xpert MTB/RIFHigh TB burden countriesFourth-generation assaysScreening algorithmTB burden countriesSputum testingTB casesTB screeningBurden countriesProspective studySputum testSymptom assessmentChest radiographsScreening testPositivity thresholdMass screeningTuberculosisMore casesDiagnostic algorithmDiagnostic testsMajor causeScreening strategy
2018
Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models
Zimmer C, Leuba SI, Cohen T, Yaesoubi R. Accurate quantification of uncertainty in epidemic parameter estimates and predictions using stochastic compartmental models. Statistical Methods In Medical Research 2018, 28: 3591-3608. PMID: 30428780, PMCID: PMC6517086, DOI: 10.1177/0962280218805780.Peer-Reviewed Original ResearchConceptsFilter degeneracyParameter estimatesPosterior distributionStochastic transmission-dynamic modelParameter posterior distributionsEpidemic compartmental modelKey epidemic parametersStochastic compartmental modelStochastic systemsPrediction intervalsCompartmental modelMultiple shootingArt calibration methodsEpidemic parametersDegeneracyDynamic modelInfluenza modelMSS approachLong-term predictionTransmission dynamic modelSimulation experimentsCalibration methodUncertaintyEstimatesCompetitive performance
2016
ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections
Chindelevitch L, Colijn C, Moodley P, Wilson D, Cohen T. ClassTR: Classifying Within-Host Heterogeneity Based on Tandem Repeats with Application to Mycobacterium tuberculosis Infections. PLOS Computational Biology 2016, 12: e1004475. PMID: 26829497, PMCID: PMC4734664, DOI: 10.1371/journal.pcbi.1004475.Peer-Reviewed Original Research
2014
Assessment of the patient, health system, and population effects of Xpert MTB/RIF and alternative diagnostics for tuberculosis in Tanzania: an integrated modelling approach
Langley I, Lin HH, Egwaga S, Doulla B, Ku CC, Murray M, Cohen T, Squire SB. Assessment of the patient, health system, and population effects of Xpert MTB/RIF and alternative diagnostics for tuberculosis in Tanzania: an integrated modelling approach. The Lancet Global Health 2014, 2: e581-e591. PMID: 25304634, DOI: 10.1016/s2214-109x(14)70291-8.Peer-Reviewed Original ResearchConceptsIncremental cost-effectiveness ratioHigh incremental costIncremental costLED fluorescence microscopyCost-effectiveness ratioPay thresholdsFull rolloutContext of TanzaniaCost-effective optionHealth policy formulationPolicy formulationDifferent diagnostic optionsIntegrated modelling approachModelling approachAdditional costHealth systemCostAlternative diagnosticsIntegrated modelXpert MTB/RIFPopulation effectsMTB/RIFPresumptive tuberculosis casesWillingnessUse of Xpert
2012
Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data
Manjourides J, Lin HH, Shin S, Jeffery C, Contreras C, Santa Cruz J, Jave O, Yagui M, Asencios L, Pagano M, Cohen T. Identifying multidrug resistant tuberculosis transmission hotspots using routinely collected data. Tuberculosis 2012, 92: 273-279. PMID: 22401962, PMCID: PMC3323731, DOI: 10.1016/j.tube.2012.02.003.Peer-Reviewed Original ResearchConceptsDrug sensitivity testTransmission hotspotsRetreatment casesDrug-resistant tuberculosis epidemicRisk of MDRTime of diagnosisDrug-resistant diseaseTB casesResistant diseaseTuberculosis epidemicHigh riskUntreated casesProgrammatic dataMDRTBRiskMDRHigh levelsTargeted investigationGeographic areasCasesDiseaseDiagnosisSensitivity testsThe dynamics of sexual contact networks: Effects on disease spread and control
Robinson K, Cohen T, Colijn C. The dynamics of sexual contact networks: Effects on disease spread and control. Theoretical Population Biology 2012, 81: 89-96. PMID: 22248701, PMCID: PMC3328800, DOI: 10.1016/j.tpb.2011.12.009.Peer-Reviewed Original ResearchConceptsDuration of infectiousnessHigh-activity individualsBehavioral interventionsBehavioral risk factorsControl of STDsHigh-risk individualsDifferent risk groupsWidespread screening programsHigh-risk subpopulationsPopulation-wide interventionsSexual network structureIndividual-level riskRisk factorsRisk groupsScreening programRisk subpopulationsGreater relative decreaseDynamics of transmissionSexual contactSexual partnershipsBiomedical interventionsInfectiousnessLonger durationComparable benefitsIntervention
2011
Epidemiologic Inference From the Distribution of Tuberculosis Cases in Households in Lima, Peru
Brooks-Pollock E, Becerra MC, Goldstein E, Cohen T, Murray MB. Epidemiologic Inference From the Distribution of Tuberculosis Cases in Households in Lima, Peru. The Journal Of Infectious Diseases 2011, 203: 1582-1589. PMID: 21592987, PMCID: PMC3096792, DOI: 10.1093/infdis/jir162.Peer-Reviewed Original ResearchConceptsHousehold contactsCommunity transmissionHousehold casesPrevious TB infectionNew TB casesHigh-incidence settingsHousehold risk factorsClustering of casesDistribution of casesMajority of casesRisk of diseaseTB infectionActive tuberculosisTB casesCase patientsProtective immunityTuberculosis casesHousehold transmissionRisk factorsNumber of casesHousehold exposureNatural historyTuberculosisCross-sectional dataImmunity