Linking Individual Natural History to Population Outcomes in Tuberculosis.
Ontology highlight
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.
SUBMITTER: Salvatore PP
PROVIDER: S-EPMC5853266 | biostudies-literature | 2017 Dec
REPOSITORIES: biostudies-literature
Publications
Linking Individual Natural History to Population Outcomes in Tuberculosis.
Salvatore Phillip P PP Proaño Alvaro A Kendall Emily A EA Gilman Robert H RH Dowdy David W DW
The Journal of infectious diseases 20171201 1
<h4>Background</h4>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.<h4>Methods</h4>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-i ...[more]
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