Outbreak ‐Based Giardia Dose–Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis

AbstractGiardia is a zoonotic gastrointestinal parasite responsible for a substantial global public health burden, and quantitative microbial risk assessment (QMRA) is often used to forecast and manage this burden. QMRA requires dose –response models to extrapolate available dose–response data, but the existing model forGiardia ignores valuable dose –response information, particularly data from several well‐documented waterborne outbreaks of giardiasis. The current study updatesGiardia dose –response modeling by synthesizing all available data from outbreaks and experimental studies using a Bayesian random effects dose–response model. For outbreaks, mean doses (D) and the degree of spatial and temporal aggregation among cysts were estimated using exposure assessment implemented via two ‐dimensional Monte Carlo simulation, while potential overreporting of outbreak cases was handled using published overreporting factors and censored binomial regression. Parameter estimation was by Markov chain Monte Carlo simulation and indicated that a typical exponential dose–response paramete r forGiardia isr = 1.6 × 10−2 [3.7 × 10−3, 6.2 × 10−2] (posterior median [95% credible interval]), while a typical morbidity ratio ism = 3.8 × 10−1 [2.3 × 10−1, 5.5 × 10−1]. Corresponding (logistic ‐scale) variance components wereσr = 5.2 × 10−1 [1.1 × 10−1, 9.6 × 10−1] andσm = 9.3 × 10−1 [7.0 × 10−2, 2.8 × 100], indicating substantial variation in t...
Source: Risk Analysis - Category: International Medicine & Public Health Authors: Tags: Original Research Article Source Type: research