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...
Source: Risk Analysis - Category: International Medicine & Public Health Authors: Tags: Original Research Article Source Type: research

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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 Bayesi...
Source: Risk Analysis - Category: International Medicine & Public Health Authors: Tags: Original Research Article Source Type: research
Authors: Ma DW, Lee MR, Hong SH, Cho SH, Lee SE Abstract Cryptosporidium parvum and Giardia duodenalis are the main diarrhea-causing parasitic pathogens; however, their prevalence in Korea is unknown. Here, we conducted a survey to determine the prevalence and genotype distribution of these 2 pathogens causing acute diarrhea in 8,571 patients hospitalized in 17 Regional Institute of Health Environment sites in Korea, during 2013-2016. C. parvum and G. duodenalis were detected and genotyped by nested PCR, and the isolate were molecularly characterized by sequencing the glycoprotein 60 (Gp60) and β-giardin genes...
Source: Korean Journal of Parasitology - Category: Parasitology Tags: Korean J Parasitol Source Type: research
Abstract Foodborne zoonotic pathogens are a serious public health issue and result in significant global economic losses. Despite their importance to public health, epidemiological data on foodborne diseases including giardiasis caused by the enteric parasite, Giardia duodenalis, are lacking. This parasite is estimated to cause ∼28.2 million cases of diarrhoea each year due to contamination of food, but very few foodborne outbreaks have been documented due to the limitations of current detection as well as surveillance methods. The current method for the recovery of Giardia cysts from food matrices using immun...
Source: International Journal for Parasitology - Category: Parasitology Authors: Tags: Int J Parasitol Source Type: research
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Source: Infection, Genetics and Evolution - Category: Genetics & Stem Cells Authors: Tags: Infect Genet Evol Source Type: research
Author Affiliations open 1Public Health Institute, Oakland, California, USA 2Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA 3Instituto de Microbiologia, Colegio de Ciencias Biologicas y Ambientales, Universidad San Francisco de Quito, Quito, Ecuador 4Department of Epidemiology and Biostatistics, Michigan State University, East Lansing, Michigan, USA 5Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, Michigan, USA 6Department of Veterinary and Biomedical Sciences, University of Minnesota, St. Paul, Minnesota, USA PDF Version (176 KB) Abstract ...
Source: EHP Research - Category: Environmental Health Authors: Tags: Brief Communication Source Type: research
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