2023
Spatial Modeling of Mycobacterium Tuberculosis Transmission with Dyadic Genetic Relatedness Data
Warren J, Chitwood M, Sobkowiak B, Colijn C, Cohen T. Spatial Modeling of Mycobacterium Tuberculosis Transmission with Dyadic Genetic Relatedness Data. Biometrics 2023, 79: 3650-3663. PMID: 36745619, PMCID: PMC10404301, DOI: 10.1111/biom.13836.Peer-Reviewed Original Research
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 ResearchConceptsTB transmissionOngoing TB transmissionMinority of casesTuberculosis transmission dynamicsTB controlTuberculosis transmissionSecondary casesSources of heterogeneityInclusion criteriaSurveillance studyTransmission clustersInitial searchTransmission dynamicsWhole-genome sequencingPopulation levelSetting
2018
Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis
Yang C, Lu L, Warren JL, Wu J, Jiang Q, Zuo T, Gan M, Liu M, Liu Q, DeRiemer K, Hong J, Shen X, Colijn C, Guo X, Gao Q, Cohen T. Internal migration and transmission dynamics of tuberculosis in Shanghai, China: an epidemiological, spatial, genomic analysis. The Lancet Infectious Diseases 2018, 18: 788-795. PMID: 29681517, PMCID: PMC6035060, DOI: 10.1016/s1473-3099(18)30218-4.Peer-Reviewed Original ResearchMeSH KeywordsAdultAgedAged, 80 and overChinaDisease Transmission, InfectiousFemaleGenotypeHumansMaleMiddle AgedMinisatellite RepeatsMolecular EpidemiologyMycobacterium tuberculosisPolymorphism, Single NucleotideRural PopulationSpatial AnalysisTransients and MigrantsTuberculosisUrban PopulationWhole Genome SequencingConceptsM tuberculosisEpidemiological dataSingle nucleotide polymorphismsCulture-positive Mycobacterium tuberculosis isolatesCulture-positive tuberculosisPopulation-based studyMycobacterium tuberculosis isolatesTransmission dynamicsTime of infectionDynamics of tuberculosisTuberculosis controlUS National InstitutesTuberculosis isolatesMore effective interventionsProximity of residenceRecent transmissionPatient's homeTuberculosisLocal transmission dynamicsEffective interventionsLocal transmissionLocal incidenceNational InstituteVNTR patternsWhole-genome sequencing
2016
The transmission of Mycobacterium tuberculosis in high burden settings
Yates TA, Khan PY, Knight GM, Taylor JG, McHugh TD, Lipman M, White RG, Cohen T, Cobelens FG, Wood R, Moore DA, Abubakar I. The transmission of Mycobacterium tuberculosis in high burden settings. The Lancet Infectious Diseases 2016, 16: 227-238. PMID: 26867464, DOI: 10.1016/s1473-3099(15)00499-5.Peer-Reviewed Original ResearchConceptsHigh-burden settingsBurden settingsTuberculosis infection controlMycobacterium tuberculosis transmissionEffects of HIVHealth care workersDrug-resistant strainsAntiretroviral therapyPerson transmissionTuberculosis transmissionInfection controlTransmission riskAirborne transmissionMycobacterium tuberculosisWells-Riley equationPresent research prioritiesTransmission dynamicsResearch prioritiesHIVEffective strategyTherapyTuberculosisSettingTrials
2015
Data for action: collection and use of local data to end tuberculosis
Theron G, Jenkins HE, Cobelens F, Abubakar I, Khan AJ, Cohen T, Dowdy DW. Data for action: collection and use of local data to end tuberculosis. The Lancet 2015, 386: 2324-2333. PMID: 26515676, PMCID: PMC4708262, DOI: 10.1016/s0140-6736(15)00321-9.Peer-Reviewed Original Research
2011
A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools [State of the art series. Operational research. Number 8 in the series]
Lin HH, Langley I, Mwenda R, Doulla B, Egwaga S, Millington KA, Mann GH, Murray M, Squire SB, Cohen T. A modelling framework to support the selection and implementation of new tuberculosis diagnostic tools [State of the art series. Operational research. Number 8 in the series]. The International Journal Of Tuberculosis And Lung Disease 2011, 15: 996-1004. PMID: 21740663, DOI: 10.5588/ijtld.11.0062.Peer-Reviewed Original ResearchConceptsDiagnostic strategiesHealth systemTB transmission dynamicsDiagnosis of tuberculosisHealth system requirementsDiagnostic toolHealth system componentsPolicy makersNew diagnostic strategiesHealth care infrastructureNovel diagnostic toolPatient outcomesDifferent epidemiologyJoint modelling frameworkModelling frameworkTest characteristicsCare infrastructureTransmission dynamicsRational choiceTuberculosisTechnological innovationStrategy decisionsDifficult decisionsMakersRecent introductionGeneralized Markov models of infectious disease spread: A novel framework for developing dynamic health policies
Yaesoubi R, Cohen T. Generalized Markov models of infectious disease spread: A novel framework for developing dynamic health policies. European Journal Of Operational Research 2011, 215: 679-687. PMID: 21966083, PMCID: PMC3182455, DOI: 10.1016/j.ejor.2011.07.016.Peer-Reviewed Original ResearchMathematical modelDynamic optimization techniquesGeneralized Markov modelClass of modelsState space sizeMarkov chain modelInfectious disease spreadOptimization techniquesDiscrete-time Markov chain modelComputation timeHost transmission dynamicsChain modelInfectious diseasesSpace sizeHost natural historyMarkov modelHealth policyPrevious modelsPublic health interventionsTransmission dynamicsClassModelReal-time selectionDisease spreadHealth interventions
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
2003
Transmission Dynamics and Control of Severe Acute Respiratory Syndrome
Lipsitch M, Cohen T, Cooper B, Robins JM, Ma S, James L, Gopalakrishna G, Chew SK, Tan CC, Samore MH, Fisman D, Murray M. Transmission Dynamics and Control of Severe Acute Respiratory Syndrome. Science 2003, 300: 1966-1970. PMID: 12766207, PMCID: PMC2760158, DOI: 10.1126/science.1086616.Peer-Reviewed Original ResearchConceptsSevere acute respiratory syndromeAcute respiratory syndromeRespiratory syndromePublic health effortsDetailed epidemiologic dataSingle infectious caseEpidemiologic dataSecondary casesAbsence of interventionInfectious casesEpidemic curveTransmission dynamicsSyndromeReproductive numberControl measuresIllnessIllnesses of humansMonths