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Linking individual natural history to population outcomes in tuberculosis

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dc.contributor.author Salvatore, Phillip P.
dc.contributor.author Proano, Alvaro
dc.contributor.author Kendall, Emily A.
dc.contributor.author Gilman, Robert H.
dc.contributor.author Dowdy, David W.
dc.date.accessioned 2018-12-01T00:04:14Z
dc.date.available 2018-12-01T00:04:14Z
dc.date.issued 2018
dc.identifier.uri https://hdl.handle.net/20.500.12866/4243
dc.description.abstract Background. Substantial individual heterogeneity exists in the clinical manifestations and duration of active tuberculosis. We sought to link the individual-level characteristics of tuberculosis disease to observed population-level outcomes. Methods. We developed an individual-based, stochastic model of tuberculosis disease in a hypothetical cohort of patients with smear-positive tuberculosis. We conceptualized the disease process as consisting of 2 states-progression and recovery-including transitions between the 2. We then used a Bayesian process to calibrate the model to clinical data from the prechemotherapy era, thus identifying the rates of progression and recovery (and probabilities of transition) consistent with observed population-level clinical outcomes. Results. Observed outcomes are consistent with slow rates of disease progression (median doubling time: 84 days, 95% uncertainty range 62-104) and a low, but nonzero, probability of transition from disease progression to recovery (median 16% per year, 95% uncertainty range 11%-21%). Other individual-level dynamics were less influential in determining observed outcomes. Conclusions. This simplified model identifies individual-level dynamics-including a long doubling time and low probability of immune recovery-that recapitulate population-level clinical outcomes of untreated tuberculosis patients. This framework may facilitate better understanding of the population-level impact of interventions acting at the individual host level. en_US
dc.language.iso eng
dc.publisher Oxford University Press
dc.relation.ispartof urn:issn:1537-6613
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject adult en_US
dc.subject Bayes theorem en_US
dc.subject calibration en_US
dc.subject cohort analysis en_US
dc.subject controlled study en_US
dc.subject disease association en_US
dc.subject disease course en_US
dc.subject disease progression en_US
dc.subject Disease progression en_US
dc.subject disease transition en_US
dc.subject female en_US
dc.subject human en_US
dc.subject immunocompetence en_US
dc.subject intermethod comparison en_US
dc.subject major clinical study en_US
dc.subject male en_US
dc.subject mathematical models en_US
dc.subject Mathematical models en_US
dc.subject medical history en_US
dc.subject natural history en_US
dc.subject Natural history en_US
dc.subject outcome assessment en_US
dc.subject priority journal en_US
dc.subject process development en_US
dc.subject spontaneous remission en_US
dc.subject Spontaneous remission en_US
dc.subject stochastic model en_US
dc.subject tuberculosis en_US
dc.subject Tuberculosis en_US
dc.title Linking individual natural history to population outcomes in tuberculosis en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1093/infdis/jix555
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.02.00 es_PE
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.08

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