DSpace Repository

Linking individual natural history to population outcomes in tuberculosis

Show simple item record

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


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record

info:eu-repo/semantics/restrictedAccess Except where otherwise noted, this item's license is described as info:eu-repo/semantics/restrictedAccess

Search DSpace


Browse

My Account

Statistics