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dc.contributor.advisorNuermberger, Eric
dc.creatorKendall, Emily A
dc.date.accessioned2019-04-15T04:21:11Z
dc.date.created2018-08
dc.date.issued2018-06-14
dc.date.submittedAugust 2018
dc.identifier.urihttp://jhir.library.jhu.edu/handle/1774.2/61101
dc.description.abstractStatement of the Problem: Approximately ten million people develop tuberculosis (TB) each year, and this global incidence is declining at a rate of only 2% annually. New diagnostic assays and treatment regimens could improve TB control in high-burden settings, but decisions about whether and how to use these tools often involve multiple competing considerations. For example, the new Xpert MTB/RIF Ultra assay improves sensitivity for TB diagnosis but at the cost of lower specificity. New TB treatment regimens that shorten treatment duration too aggressively could reduce treatment efficacy. A shorter regimen for multidrug-resistant (MDR) TB may increase treatment access, but the non-inferiority of its treatment efficacy remains uncertain. Given such trade-offs, international and country-level decision-makers need to anticipate how new tools are likely to affect various local patient populations and epidemics. Methods: In this dissertation, dynamic transmission models of TB epidemics are used to (1) project the impact on MDR-TB incidence in Southeast Asia of a new 9-month treatment regimen, and (2) to compare the dependence of novel regimens’ impact on regimen characteristics such as efficacy, duration, tolerability, and barrier to resistance. In addition, a Markov model is used to simulate clinical outcomes (unnecessary treatments, deaths averted) of adopting the Xpert MTB/RIF Ultra cartridge, in several hypothetical settings emblematic of global TB epidemiology and in a specific study community in urban Uganda. Results: The 9-month MDR-TB regimen could lower MDR-TB incidence by 23% (95% uncertainty range 10–38%), but this projection depended on raising both treatment effectiveness and treatment availability and on limiting detrimental effects of second-line drug resistance. For novel regimens for both rifampin-susceptible and rifampin-resistant TB, treatment efficacy was the most critical of the regimen characteristics modeled and was responsible for approximately half of a regimen’s maximal epidemiologic impact. The clinical impact of switching to the Xpert MTB/RIF Ultra cartridge varied widely between settings but was most favorable in clinical contexts with high prevalence of both TB and HIV, such as in sub-Saharan Africa. Conclusions: These mathematical models provide useful, context-specific guidance for deciding whether and how to implement new TB treatment regimens or diagnostic tools.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherJohns Hopkins University
dc.subjecttuberculosis
dc.subjectmathematical modeling
dc.subjectdiagnosis
dc.subjecttreatment
dc.subjectnovel drugs and regimens
dc.subjecttransmission
dc.subjectepidemiology
dc.subjectdrug resistance, guideline development
dc.subjectclinical decision-making
dc.subjectpopulation-level impact
dc.titleMathematical modeling to guide programmatic decisions about the use of new tuberculosis drugs, regimens, and diagnostics
dc.typeThesis
thesis.degree.disciplineClinical Investigation
thesis.degree.grantorJohns Hopkins University
thesis.degree.grantorBloomberg School of Public Health
thesis.degree.levelDoctoral
thesis.degree.namePh.D.
dc.date.updated2019-04-15T04:21:11Z
dc.type.materialtext
thesis.degree.departmentMedicine
local.embargo.lift2019-08-01
local.embargo.terms2019-08-01
dc.contributor.committeeMemberGhanem, Khalil
dc.contributor.committeeMemberFlexner, Charles
dc.contributor.committeeMemberDowdy, David
dc.publisher.countryUSA
dc.creator.orcid0000-0002-0083-422X


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