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 trendsServices
2022
Spatially 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
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 case
2020
Comparative 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
Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil
Mabud TS, de Lourdes Delgado Alves M, Ko AI, Basu S, Walter KS, Cohen T, Mathema B, Colijn C, Lemos E, Croda J, Andrews JR. Evaluating strategies for control of tuberculosis in prisons and prevention of spillover into communities: An observational and modeling study from Brazil. PLOS Medicine 2019, 16: e1002737. PMID: 30677013, PMCID: PMC6345418, DOI: 10.1371/journal.pmed.1002737.Peer-Reviewed Original ResearchConceptsIncidence of TBPrison-based interventionsTB incidenceGeneral populationTB casesCox proportional hazards modelNew TB casesControl of tuberculosisProportional hazards modelPaucity of dataTime of incarcerationTB burdenTB screeningTB riskTB transmissionTB ratesTB epidemicAdministrative databasesCommunity incidenceTuberculosis epidemicHazards modelTB databaseIncidenceEpidemiological contextIntervention
2018
ADAPTIVE DECISION‐MAKING DURING EPIDEMICS
Yaesoubi R, Cohen T. ADAPTIVE DECISION‐MAKING DURING EPIDEMICS. 2018, 59-79. DOI: 10.1002/9781118960158.ch3.ChaptersIntegrated analytical frameworkPolicy makersEconomic costsTransmission-reducing interventionsAnalytical frameworkSubstantial healthPopulation healthNovel viral strainsDecisionsResource constraintsAvailability of resourcesEmploymentAvailable interventionsMakersInfluenza epidemicsDifficult decisionsViral strainsInfectious diseasesCostEpidemicInterventionDecision pointsEpidemic dataHealth
2016
Cost-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 dataInterventionIdentifying cost‐effective dynamic policies to control epidemics
Yaesoubi R, Cohen T. Identifying cost‐effective dynamic policies to control epidemics. Statistics In Medicine 2016, 35: 5189-5209. PMID: 27449759, PMCID: PMC5096998, DOI: 10.1002/sim.7047.Peer-Reviewed Original ResearchConceptsNet health benefitHighest net health benefitHealth benefitsTransmission-reducing interventionsDynamic policiesNovel viral pathogensCurrent interventionsHealth policyMathematical decision modelViral pathogensMonetary outcomesPolicy makersInterventionPolicyDecision modelStatic policyEpidemicEpidemic dataVaccinationVaccinePerformance measuresHigh 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 TownIndividualsReinfectionPrevalenceIncidenceDiseaseSetting
2014
Prospective evaluation of a complex public health intervention: lessons from an initial and follow-up cross-sectional survey of the tuberculosis strain typing service in England
Mears J, Abubakar I, Crisp D, Maguire H, Innes JA, Lilley M, Lord J, Cohen T, Borgdorff MW, Vynnycky E, McHugh TD, Sonnenberg P. Prospective evaluation of a complex public health intervention: lessons from an initial and follow-up cross-sectional survey of the tuberculosis strain typing service in England. BMC Public Health 2014, 14: 1023. PMID: 25273511, PMCID: PMC4194411, DOI: 10.1186/1471-2458-14-1023.Peer-Reviewed Original ResearchMeSH KeywordsAttitude of Health PersonnelBacterial Typing TechniquesClinical CompetenceCost-Benefit AnalysisCross-Sectional StudiesEnglandFemaleFollow-Up StudiesHealth ServicesHumansMaleMolecular EpidemiologyMycobacteriumPopulation SurveillanceProgram EvaluationProspective StudiesPublic HealthSurveys and QuestionnairesTuberculosisConceptsPublic health interventionsComplex public health interventionsCross-sectional surveyHealth interventionsNational public health interventionsStrain typingPublic health staffRepeated cross-sectional surveySignificant increaseMIRU-VNTR typingProportion of respondentsTB patientsSelf-rated knowledgeTB controlProspective evaluationMixed-method evaluationHealth staffProspective identificationMajority of respondentsService users' perceptionsMethodsAn onlineInterventionTypingFuture evaluationProfessional groupsGeographical heterogeneity of multidrug-resistant tuberculosis in Georgia, January 2009 to June 2011.
Jenkins HE, Gegia M, Furin J, Kalandadze I, Nanava U, Chakhaia T, Cohen T. Geographical heterogeneity of multidrug-resistant tuberculosis in Georgia, January 2009 to June 2011. Eurosurveillance 2014, 19 PMID: 24679722, PMCID: PMC4090679, DOI: 10.2807/1560-7917.es2014.19.11.20743.Peer-Reviewed Original ResearchConceptsMultidrug-resistant TBMDR-TB risk factorsTB casesRisk factorsMDR-TB incidenceMDR-TB riskMDR-TB transmissionMDR-TB casesMultidrug-resistant tuberculosisTreatment-naïve individualsMDR-TB burdenTuberculosis casesHigh riskTargeted interventionsSurveillance dataGeographical heterogeneityRegression modellingInterventionRiskRural areasCasesTuberculosisIncidencePercentage
2013
Community-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis
Mills HL, Cohen T, Colijn C. Community-Wide Isoniazid Preventive Therapy Drives Drug-Resistant Tuberculosis: A Model-Based Analysis. Science Translational Medicine 2013, 5: 180ra49. PMID: 23576815, PMCID: PMC3714172, DOI: 10.1126/scitranslmed.3005260.Peer-Reviewed Original ResearchConceptsDrug-resistant TBIPT interventionDrug-sensitive infectionsIsoniazid-resistant TBHIV/TBRisk of progressionHigh HIV prevalenceDrug-resistant diseaseIsoniazid-resistant Mycobacterium tuberculosisSymptom-free individualsSignificant elevated riskDrug-resistant strainsWorld Health OrganizationActive TBTB controlResistant tuberculosisHIV prevalenceTuberculosis controlIPT programElevated riskHost immunityMycobacterium tuberculosisHealth OrganizationSelective suppressionIntervention
2012
The 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
Dynamic Health Policies for Controlling the Spread of Emerging Infections: Influenza as an Example
Yaesoubi R, Cohen T. Dynamic Health Policies for Controlling the Spread of Emerging Infections: Influenza as an Example. PLOS ONE 2011, 6: e24043. PMID: 21915279, PMCID: PMC3167826, DOI: 10.1371/journal.pone.0024043.Peer-Reviewed Original ResearchConceptsHealth policyTransmission-reducing interventionsOverall population healthType of interventionAntiviral drugsNovel infectious pathogensOverall healthEmerging InfectionsInfectious pathogensMask useCurrent interventionsCourse of epidemicsPopulation healthInterventionEpidemicPublic healthVaccineInfluenzaHealthDisease spreadSocial distancingCurrent informationInfection
2009
Mathematical models of the epidemiology and control of drug-resistant TB
Cohen T, Dye C, Colijn C, Williams B, Murray M. Mathematical models of the epidemiology and control of drug-resistant TB. Expert Review Of Respiratory Medicine 2009, 3: 67-79. PMID: 20477283, DOI: 10.1586/17476348.3.1.67.Peer-Reviewed Original ResearchDrug-resistant TBDrug resistanceMultiple drug-resistant Mycobacterium tuberculosisDrug-resistant Mycobacterium tuberculosisDrug-resistant M. tuberculosisCombination chemotherapyTB controlM. tuberculosisMycobacterium tuberculosisAntibiotic resistanceRecent reportsTuberculosisEpidemiologyTBExtrinsic determinantsInterventionCost effectivenessReproductive capacityChemotherapyControlPrevalence
2008
Mathematical Modeling of Tuberculosis Transmission Dynamics
Cohen T, Colijn C, Murray M. Mathematical Modeling of Tuberculosis Transmission Dynamics. 2008, 227-243. DOI: 10.1002/9783527611614.ch44.Peer-Reviewed Original ResearchMathematical modelBehavior of epidemicsSimple mathematical modelEpidemic modelMathematical modelingTuberculosis transmission dynamicsTuberculosis dynamicsDynamic modelNatural courseTB epidemicDynamicsNatural historyInfectious diseasesTransmission dynamicsMycobacterium tuberculosisDiseaseModelQuantitative insightsKey parametersInterventionEpidemicImportant toolComplicating factorsPotential effectsModeling