2025
Quantifying disruptions to tuberculosis case detection in Brazilian states during the COVID-19 pandemic
Chitwood M, Menzies N, Bartholomay P, Pelissari D, de Barros Silva Júnior J, Harada L, Johansen F, Maciel E, Castro M, Sanchez M, Warren J, Cohen T. Quantifying disruptions to tuberculosis case detection in Brazilian states during the COVID-19 pandemic. International Journal Of Epidemiology 2025, 54: dyaf146. PMID: 40838691, DOI: 10.1093/ije/dyaf146.Peer-Reviewed Original ResearchMeSH KeywordsBayes TheoremBrazilCOVID-19Disease NotificationFemaleHumansIncidenceMalePandemicsSARS-CoV-2TuberculosisConceptsPre-pandemic levelsTB casesCase detectionCOVID-19 pandemicBrazilian healthcare systemTB notification ratesTB case detectionHealth system disruptionsTuberculosis case detectionCase detection rateMortality dataHealthcare systemIncident TBMeta-regression frameworkTB incidenceNotification ratesSymptomatic TBCase notificationCOVID-19TB controlTB diagnosisBrazilian statesPandemicCareIndividualsChanges in incarceration and tuberculosis notifications from prisons during the COVID-19 pandemic in Europe and the Americas: a time-series analysis of national surveillance data
Zheng A, Faust L, Harries A, Avedillo P, Akodu M, Galvan M, Barreto-Duarte B, Andrade B, Ugarte-Gil C, Garcia-Basteiro A, Espinal M, Warren J, Martinez L. Changes in incarceration and tuberculosis notifications from prisons during the COVID-19 pandemic in Europe and the Americas: a time-series analysis of national surveillance data. The Lancet Public Health 2025, 10: e285-e294. PMID: 40175010, PMCID: PMC11962358, DOI: 10.1016/s2468-2667(24)00325-6.Peer-Reviewed Original ResearchMeSH KeywordsAmericasCOVID-19Disease NotificationEuropeHumansIncarcerationPandemicsPrisonersPrisonsTuberculosisConceptsPrison populationCOVID-19 pandemicPrisonIncarcerationTuberculosis notificationsPan American Health OrganizationNotificationCOVID-19WHO EuropeEuropePandemic yearCountriesAffected peoplePandemicTime series analysisAmericaWorld regionsAnalysis of national surveillance dataHealth OrganizationCOVID-19 pandemic yearPeople
2024
Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model
Lan Y, Crudu V, Ciobanu N, Codreanu A, Chitwood M, Sobkowiak B, Warren J, Cohen T. Identifying local foci of tuberculosis transmission in Moldova using a spatial multinomial logistic regression model. EBioMedicine 2024, 102: 105085. PMID: 38531172, PMCID: PMC10987885, DOI: 10.1016/j.ebiom.2024.105085.Peer-Reviewed Original ResearchConceptsPatterns of spatial aggregationMTB strainsMDR-TBLogistic regression modelsGenome Epidemiology StudySpecific strainsMultidrug-resistant tuberculosisTreated TB casesNational Institute of AllergyMDR phenotypeRegression modelsM. tuberculosisInstitute of AllergyMultinomial logistic regression modelUS National Institutes of HealthNational Institutes of HealthMDR diseasePublic health concernAssociated with local transmissionIncident TBInstitutes of HealthMtbResistant tuberculosisStrainDiagnosing TB
2023
Spatially-targeted tuberculosis screening has limited impact beyond household contact tracing in Lima, Peru: A model-based analysis
Havumaki J, Warren J, Zelner J, Menzies N, Calderon R, Contreras C, Lecca L, Becerra M, Murray M, Cohen T. Spatially-targeted tuberculosis screening has limited impact beyond household contact tracing in Lima, Peru: A model-based analysis. PLOS ONE 2023, 18: e0293519. PMID: 37903091, PMCID: PMC10615320, DOI: 10.1371/journal.pone.0293519.Peer-Reviewed Original ResearchGlobal, 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 InstituteDevelopment 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 ResearchMeSH KeywordsAdolescentAlgorithmsChildHumansRetrospective StudiesTriageTuberculosisTuberculosis, PulmonaryUnited StatesConceptsTreatment 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
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