2022
A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities
Chitwood M, Alves L, Bartholomay P, Couto R, Sanchez M, Castro M, Cohen T, Menzies N. A spatial-mechanistic model to estimate subnational tuberculosis burden with routinely collected data: An application in Brazilian municipalities. PLOS Global Public Health 2022, 2: e0000725. PMID: 36962578, PMCID: PMC10021638, DOI: 10.1371/journal.pgph.0000725.Peer-Reviewed Original ResearchPerson/yearTB incidenceCase notificationBurden estimatesIncident TB casesTB case notificationTB control strategiesDisease burden estimatesIncident TBUntreated TBTB casesTuberculosis burdenDisease burdenIncidence rateCase detectionRoutine dataDeath recordsMortality dataIncidenceSubnational estimatesDisease control resourcesBurdenHigh needTBFraction of individuals
2013
Disease Mapping with Spatially Uncertain Data
Manjourides J, Cohen T, Jeffery C, Pagano M. Disease Mapping with Spatially Uncertain Data. Online Journal Of Public Health Informatics 2013, 5 PMCID: PMC3692831, DOI: 10.5210/ojphi.v5i1.4380.Peer-Reviewed Original ResearchNew TB casesDrug sensitivity testingTB casesProgrammatic dataHigh TB burdenDrug-resistant casesTB burdenIncident casesResistant casesUnderlying burdenHigh riskRoutine dataDisease acquisitionInverse probabilityTransmission hotspotsSensitivity testingNon-random sampleRiskLocation of casesReduced testingDiseaseRepresentative sampleUnadjusted dataDRTBUntested cases