Original paper
A novel Bayesian geospatial method for estimating tuberculosis incidence reveals many missed TB cases in Ethiopia
Abstract
Reported tuberculosis (TB) incidence globally continues to be heavily influenced by expert opinion of case detection rates and ecological estimates of disease duration. Both approaches are recognised as having substantial variability and inaccuracy, leading to uncertainty in true TB incidence and other such derived statistics. We developed Bayesian binomial mixture geospatial models to estimate TB incidence and case detection rate (CDR) in...
Paper Details
Title
A novel Bayesian geospatial method for estimating tuberculosis incidence reveals many missed TB cases in Ethiopia
Published Date
Oct 2, 2017
Journal
Volume
17
Issue
1
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Notes
History