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
2023
Global, regional, and national estimates of tuberculosis incidence and case detection among incarcerated individuals from 2000 to 2019: a systematic analysis
Martinez L, Warren J, Harries A, Croda J, Espinal M, Olarte R, Avedillo P, Lienhardt C, Bhatia V, Liu Q, Chakaya J, Denholm J, Lin Y, Kawatsu L, Zhu L, Horsburgh C, Cohen T, Andrews J. Global, regional, and national estimates of tuberculosis incidence and case detection among incarcerated individuals from 2000 to 2019: a systematic analysis. The Lancet Public Health 2023, 8: e511-e519. PMID: 37393090, PMCID: PMC10323309, DOI: 10.1016/s2468-2667(23)00097-x.Peer-Reviewed Original ResearchConceptsTuberculosis incidenceCase detection ratioIncidence rateCase detectionHigh tuberculosis incidence ratesGlobal tuberculosis control effortsIncident tuberculosis casesTuberculosis incidence rateIncarcerated individualsTuberculosis control effortsTuberculosis case detectionTuberculosis casesNotification ratesNational incidenceTuberculosis notificationsGlobal incidenceHigh riskPrevalence estimatesNational estimatesWHO regionsIncidenceStudy periodMeta-regression frameworkTuberculosisNational Institute
2022
Neighbourhood 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 ResearchConceptsCase 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 tuberculosisSpatially 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
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 prevalenceDisparities in access to diagnosis and care in Blantyre, Malawi, identified through enhanced tuberculosis surveillance and spatial analysis
MacPherson P, Khundi M, Nliwasa M, Choko AT, Phiri VK, Webb EL, Dodd PJ, Cohen T, Harris R, Corbett EL. Disparities in access to diagnosis and care in Blantyre, Malawi, identified through enhanced tuberculosis surveillance and spatial analysis. BMC Medicine 2019, 17: 21. PMID: 30691470, PMCID: PMC6350280, DOI: 10.1186/s12916-019-1260-6.Peer-Reviewed Original ResearchConceptsTB case notification ratesCase notification ratesCommunity health workersNotification ratesTB casesLow case detectionSingle sputum sampleInverse care lawArea-level factorsTB registrationTB clinicTB patientsClinical characteristicsTB diagnosisTuberculosis casesResultsIn totalTB surveillanceCase detectionModifiable predictorsSputum samplesHealth workersTB officersTB microscopyAdjusted modelTuberculosis surveillance
2015
The prospective evaluation of the TB strain typing service in England: a mixed methods study
Mears J, Vynnycky E, Lord J, Borgdorff MW, Cohen T, Crisp D, Innes JA, Lilley M, Maguire H, McHugh TD, Woltmann G, Abubakar I, Sonnenberg P. The prospective evaluation of the TB strain typing service in England: a mixed methods study. Thorax 2015, 71: thoraxjnl-2014-206480. PMID: 25882538, DOI: 10.1136/thoraxjnl-2014-206480.Peer-Reviewed Original ResearchConceptsDiagnostic delayTB incidenceTB notification ratesProportion of infectionsMycobacterium tuberculosis diagnosisFalse-positive diagnosesCost-effectiveness analysisMixed-methods evaluationStrain typingTB programsProspective evaluationNotification ratesInfection increasesTuberculosis diagnosisPositive diagnosisPublic health dataComplex interventionsIncidenceMixed-methods studyRoutine laboratoryDiagnosisHealth dataCluster investigationsTypingMethods study
2013
Evaluation of the Tuberculosis Strain Typing Service (TB-STS) in England
Mears J, Vynnycky E, Lord J, Borgdorff M, Cohen T, Abubakar I, Sonnenberg P, group O. Evaluation of the Tuberculosis Strain Typing Service (TB-STS) in England. The Lancet 2013, 382: s73. DOI: 10.1016/s0140-6736(13)62498-8.Peer-Reviewed Original ResearchTuberculosis incidenceProportion of infectionsDiagnostic delayBase-case assumptionsLatent infectionPulmonary tuberculosis casesTuberculosis control effortsHigh-incidence settingsMycobacterium tuberculosis isolatesCluster investigationsTuberculosis notification ratesPost-implementation dataComplex public health interventionsPopulation-level interventionsPublic health interventionsMIRU-VNTR typingTuberculosis infectionTuberculosis casesPreventive treatmentPublic health outcomesNotification ratesTuberculosis isolatesSenior Research FellowshipDeterministic compartmental modelProportion of individuals