2023
Isolation and Quarantine for Coronavirus Disease 2019 in the United States, 2020–2022
Oeltmann J, Vohra D, Matulewicz H, DeLuca N, Smith J, Couzens C, Lash R, Harvey B, Boyette M, Edwards A, Talboy P, Dubose O, Regan P, Loosier P, Caruso E, Katz D, Taylor M, Moonan P. Isolation and Quarantine for Coronavirus Disease 2019 in the United States, 2020–2022. Clinical Infectious Diseases 2023, 77: 212-219. PMID: 36947142, PMCID: PMC11094624, DOI: 10.1093/cid/ciad163.Peer-Reviewed Original ResearchConceptsCoronavirus disease 2019Case patientsDisease 2019Positive severe acute respiratory syndrome coronavirus 2 test resultAdult case patientsCase investigationCOVID-19Public health programsPublic health workforceHealth programsHealth workforceContact tracingPatientsHealth officialsMost adultsAdultsDaysImpact of contactRepresentative sampleTotalMore adultsPanel SurveyQuarantineDevelopment 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
2022
Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas
Shrestha S, Winglee K, Hill A, Shaw T, Smith J, Kammerer JS, Silk BJ, Marks S, Dowdy D. Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas. Clinical Infectious Diseases 2022, 75: 1433-1441. PMID: 35143641, PMCID: PMC9412192, DOI: 10.1093/cid/ciac121.Peer-Reviewed Original ResearchMeSH KeywordsCaliforniaFloridaGenotypeHumansMycobacterium tuberculosisNew YorkTexasTuberculosisUnited StatesConceptsTB casesTB transmissionKey public health priorityPublic health priorityMechanistic transmission modelsTB incidenceTuberculosis transmissionSecondary casesHealth priorityInfectious casesTransmission clustersDisease controlMean numberR0 estimatesUnited StatesWhole-genome sequencingSame countyGenotype clustersState-level differencesSecondary transmissionCasesIncidence