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Quantitative Microbial sentence examples within risk assessment model

risk assessment model

The purpose of this study was to develop a retail-to-consumption quantitative microbial risk assessment model that could be used to estimate the differences in risk of salmonellosis acquired from the consumption of conventionally and alternatively produced broiler meat in the United States annually.

Assessing the Risk of Salmonellosis from Consumption of Conventionally and Alternatively Produced Broiler Meat Prepared In-Home in the United States

risk assessment model

We explicitly incorporated decision theory into a quantitative microbial risk assessment model.

Linking Decision Theory and Quantitative Microbial Risk Assessment: Tradeoffs Between Compliance and Efficacy for Waterborne Disease Interventions.

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Quantitative Microbial sentence examples within health risks associated

health risks associated

We also discuss approaches for assessing and mitigating health risks associated with stormwater, including a summary of existing quantitative microbial risk assessment (QMRA) models for potable and non-potable reuse of stormwater.

A review on microbial contaminants in stormwater runoff and outfalls: Potential health risks and mitigation strategies

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Quantitative Microbial sentence examples within Reverse Quantitative Microbial

Reverse Quantitative Microbial

Then, the reverse quantitative microbial risk assessment (QMRA) provides a quantitative framework for the estimation of acceptable exposure time to protect people from excessive exposure and then manage their health risk.

Estimating acceptable exposure time for bioaerosols emission in a wastewater treatment plant by reverse quantitative microbial risk assessment based on various risk benchmarks

Reverse Quantitative Microbial

coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements.

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Quantitative Microbial sentence examples within Published Quantitative Microbial

Published Quantitative Microbial

Over a wide range of meteorological conditions, water samples were collected and analyzed for fecal indicator bacteria (FIB, used for water quality management) and previously published quantitative microbial source tracking (qMST) markers.

Integrating culture and molecular quantification of microbial contaminants into a predictive modeling framework in a low-lying, tidally-influenced coastal watershed.

Published Quantitative Microbial

We compared risks from de facto reuse, indirect potable reuse (IPR), and direct potable reuse (DPR) scenarios using a previously published Quantitative Microbial Risk Assessment methodology and literature review results.

Comparison of Predicted Microbiological Human Health Risks Associated with de facto, Indirect, and Direct Potable Water Reuse.

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Quantitative Microbial sentence examples within Inform Quantitative Microbial

Inform Quantitative Microbial

jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat.

The transmission dynamics of Campylobacter jejuni among broilers in semi-commercial farms in Jordan

Inform Quantitative Microbial

Results of this study can be used to inform quantitative microbial risk assessment (QMRA) models aimed at defining the relationship between surface contamination, pathogen exposure and the probability of disease that contributes to high healthcare costs, absenteeism, presenteeism, and loss of productivity in the workplace.

Impact of a hygiene intervention on virus spread in an office building.

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Quantitative Microbial sentence examples within Use Quantitative Microbial

Use Quantitative Microbial

We aimed to use quantitative microbial risk assessment to evaluate household laundering practices (e.

Quantifying Pathogen Infection Risks from Household Laundry Practices.

Use Quantitative Microbial

This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies.

A Case Study Evaluating the Risk of Infection from Middle Eastern Respiratory Syndrome Coronavirus (MERS‐CoV) in a Hospital Setting Through Bioaerosols

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Quantitative Microbial sentence examples within quantitative microbial risk

quantitative microbial risk

Quantitative microbial risk assessment for the exposure of urban residents to Cryptosporidium and Giardia was also performed.

Exposure parameters and health risk of Cryptosporidium and Giardia in the recreational water activities for urban residents in China

quantitative microbial risk

To better understand the potential risks, Quantitative Microbial Risk Assessment (QMRA) was performed for three population groups in Kampala, Uganda: wastewater and faecal sludge treatment plant workers; farmers using faecal sludge; and consumers of faecal sludge-fertilised vegetables.

Assessing the microbial risk of faecal sludge use in Ugandan agriculture by comparing field and theoretical model output.

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Quantitative Microbial sentence examples within quantitative microbial source

quantitative microbial source

Over a wide range of meteorological conditions, water samples were collected and analyzed for fecal indicator bacteria (FIB, used for water quality management) and previously published quantitative microbial source tracking (qMST) markers.

Integrating culture and molecular quantification of microbial contaminants into a predictive modeling framework in a low-lying, tidally-influenced coastal watershed.

quantitative microbial source

The faecal water contamination had both anthropogenic and zoogenic origins identified through quantitative microbial source tracking applying host‐specific Bacteroidales 16S rRNA genetic markers.

Aquatic microbial diversity associated with faecal pollution of Norwegian waterbodies characterized by 16S rRNA gene amplicon deep sequencing

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Quantitative Microbial sentence examples within quantitative microbial gene

quantitative microbial gene

Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes.

A robust metatranscriptomic technology for population-scale studies of diet, gut microbiome, and human health

quantitative microbial gene

Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes.

A Robust Metatranscriptomic Technology for Population-Scale Studies of Diet, Gut Microbiome, and Human Health

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Quantitative Microbial sentence examples within quantitative microbial test

quantitative microbial test

Based on quantitative microbial tests, Bacillus cereus was detected in three farms and Staphylococcus aureus was detected in only one farm.

Bacterial Quality, Prevalence of Pathogens, and Molecular Characterization of Biofilm-Producing Staphylococcus aureus from Korean Dairy Farm Environments

quantitative microbial test

The quantitative microbial tests were done by dilution plate technique.

Microbial Contamination of Handmade Sauce Used by Street Food Vendors in Jashore, Bangladesh

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10.1264/jsme2.ME19088

In contrast to the common assumption during quantitative microbial/risk assessments (QMRAs) that all environmental strains are pathogenic, the present results revealed that Campylobacter within the Yarra River estuary had very low virulence potential.

Campylobacter in an Urban Estuary: Public Health Insights from Occurrence, HeLa Cytotoxicity, and Caco-2 Attachment Cum Invasion

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Quantitative Microbial
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What is/are Quantitative Microbial?

Quantitative Microbial - In contrast to the common assumption during quantitative microbial/risk assessments (QMRAs) that all environmental strains are pathogenic, the present results revealed that Campylobacter within the Yarra River estuary had very low virulence potential. [1]

risk assessment model

The purpose of this study was to develop a retail-to-consumption quantitative microbial risk assessment model that could be used to estimate the differences in risk of salmonellosis acquired from the consumption of conventionally and alternatively produced broiler meat in the United States annually. [1] We explicitly incorporated decision theory into a quantitative microbial risk assessment model. [2] A quantitative microbial risk assessment model FFLLoRA (Frozen Food Listeria Lot Risk Assessment) was developed to assess the lot-level listeriosis risk due to LM contamination in frozen vegetables consumed as a ready-to-eat food. [3] The provision of the model in a standardized data format will allow an easy incorporation of the developed model into a complete quantitative microbial risk assessment model that will greatly help to estimate the risk of consumer exposure to MRSA through the consumption of contaminated food. [4] A screening-level, point estimate quantitative microbial risk assessment model was developed to evaluate worst-case scenarios across an array of exposure pathways in five case study locations. [5] A quantitative microbial risk assessment model was conducted to estimate (i) the health risks associated with consumption of rotavirus (RV)-contaminated fresh produce with different surface properties (endive and kale) and (ii) how risks changed when using peracetic acid (PAA) or a surfactant-based sanitizer. [6] jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat. [7] A probabilistic, evidence-based, quantitative microbial risk assessment model was developed to investigate public health risks associated with Campylobacter spp. [8] A quantitative microbial risk assessment model (QMRA) was developed and porcine cysticercosis prevalence data, the percentage of home slaughtered pigs, meat inspection sensitivity, the cyst distribution in pork and pork consumption in five European countries, Bulgaria, Germany, Poland, Romania and Spain, were included as variables in the model. [9]

health risks associated

We also discuss approaches for assessing and mitigating health risks associated with stormwater, including a summary of existing quantitative microbial risk assessment (QMRA) models for potable and non-potable reuse of stormwater. [1]

Reverse Quantitative Microbial

Then, the reverse quantitative microbial risk assessment (QMRA) provides a quantitative framework for the estimation of acceptable exposure time to protect people from excessive exposure and then manage their health risk. [1] coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. [2] A reverse quantitative microbial risk assessment (QMRA) framework and quantitative polymerase chain reaction data for norovirus genogroup I in subsurface drinking water supplies were used herein to evaluate treatment needs for such water supplies. [3] To determine these concentrations, a reverse quantitative microbial risk assessment (QMRA) was conducted. [4]

Published Quantitative Microbial

Over a wide range of meteorological conditions, water samples were collected and analyzed for fecal indicator bacteria (FIB, used for water quality management) and previously published quantitative microbial source tracking (qMST) markers. [1] We compared risks from de facto reuse, indirect potable reuse (IPR), and direct potable reuse (DPR) scenarios using a previously published Quantitative Microbial Risk Assessment methodology and literature review results. [2]

Inform Quantitative Microbial

jejuni infection in broiler production systems commonly found in Jordan and the Middle-East and could be used to inform Quantitative Microbial Risk Assessment models aimed to assess the risk of human exposure/infection to campylobacter through consumption of poultry meat. [1] Results of this study can be used to inform quantitative microbial risk assessment (QMRA) models aimed at defining the relationship between surface contamination, pathogen exposure and the probability of disease that contributes to high healthcare costs, absenteeism, presenteeism, and loss of productivity in the workplace. [2]

Use Quantitative Microbial

We aimed to use quantitative microbial risk assessment to evaluate household laundering practices (e. [1] This study uses Quantitative Microbial Risk Assessment to develop a generalizable model that can assist with interpreting reported outbreak data or predict risk of infection with or without the recommended strategies. [2]

quantitative microbial risk

Quantitative microbial risk assessment for the exposure of urban residents to Cryptosporidium and Giardia was also performed. [1] To better understand the potential risks, Quantitative Microbial Risk Assessment (QMRA) was performed for three population groups in Kampala, Uganda: wastewater and faecal sludge treatment plant workers; farmers using faecal sludge; and consumers of faecal sludge-fertilised vegetables. [2] Methods: This study used data from a year-long countywide pathogen occurrence study as inputs into a quantitative microbial risk assessment (QMRA) to predict the total cases of acute gastrointestinal illness (AGI) caused by private well contamination in the county. [3] aureus) were estimated using quantitative microbial risk assessment (QMRA). [4] A quantitative microbial risk assessment (QMRA) model was developed to investigate the health risk associated with Salmonella contamination in yellow-feathered broiler chicken supply chain in China extending from the farm to home consumption. [5] Quantitative microbial risk assessment (QMRA) is a systematic framework for predicting this risk in either infection, illness or death. [6] coli (ETEC) from drinking water in that region using Quantitative Microbial Risk Assessment (QMRA). [7] Since microbial strains vary in their growth and activation patterns in food materials, it is important to accurately predict these patterns for quantitative microbial risk assessment. [8] The present work has been oriented to the qualitative and quantitative assessments of the aftermath effects of 2014 flood tragedy on the organic, inorganic and microbial contaminants in the floodwater, with a particular emphasis on their relative health risks and microbial infectious hazards to the flood-affected population, using average daily dose, hazard quotient, hazard index (HI), cancer risk (CR) and quantitative microbial risk assessment. [9] Interpretation We identified remaining gaps in the evidence base including a need for broad characterization of enteric pathogens in bioaerosols beyond bacterial genera, a need for greater sampling in locations of high enteric disease risk, and a need for quantitative estimation of microbial and nucleic acid densities that may be applied to fate and transport models and in quantitative microbial risk assessment. [10] 0 Python), a probabilistic-deterministic model that combines virus fate and transport modelling in the river with quantitative microbial risk assessment (QMRA). [11] A team of researchers estimated the risk of hepatitis A infection transmission through water sources using a quantitative microbial risk assessment (QMRA) model across primary schools in Sindh, Pakistan [5]. [12] In this study, we examined Canada's first NSP at Borden Park, Edmonton, Canada, to address the following three questions: (1) Given normal faecal shedding rates by bathers, what is the total log reduction (TLR) theoretically needed to meet the EPA benchmark? (2) what is the in-situ performance of the NSP based on spiking suitable microbial surrogates (MS2 coliphage, Enterococcus faecalis, and Saccharomyces cerevisiae [Baker's yeast])? and (3) how much time is required to reach acceptable bather risk levels under different representative volume-turnover rates? A reverse-quantitative microbial risk assessment (QMRA) revealed that of the four reference pathogens selected (Norovirus, Campylobacter, Cryptosporidium, and Giardia), only Norovirus was estimated to exceed the risk benchmark at the 50th, 75th, and 95th percentiles, while Campylobacter was the only other reference pathogen to exceed at the 95th percentile. [13] The estimated risk of infection from touching a contaminated surface was low (less than 5 in 10,000) by quantitative microbial risk assessment, suggesting fomites play a minimal role in SARS-CoV-2 community transmission. [14] A Quantitative Microbial Risk Assessment (QMRA) framework was applied to assess 312 drinking water supply systems across regional New South Wales (NSW). [15] Quantitative microbial risk assessment (QMRA) is a method that uses mathematical modelling to estimate the risk of infection when exposure to pathogens happens and was used in this study to assess the health risks. [16] This study proposes a modified methodology for semi-quantitative microbial risk assessment (SQMRA) based on the risk matrix presented in the World Health Organization (WHO) Sanitation Safety Planning manual adding the variable ranking for probability of infection in the estimations of risk scores, which composes the risk matrix. [17] Additionally, we emphasized the potential of applying the quantitative microbial risk assessment to guide drinking water treatment to mitigate the viral exposure risks, especially when the unregulated novel viral pathogens are of concern. [18] Then, a strict quantitative microbial risk assessment (QMRA) was performed on several exposure scenarios associated with occupational health risks of temporary entrants (researchers, visitors, and inspectors) and staffs (field engineer and laboratory technician). [19] The risk that may arise from exposure to virus-contaminated aerosols of wastewater was estimated by developing a quantitative microbial risk analysis (QMRA) method. [20] Using a quantitative microbial risk model, we evaluated the individual and combined effect of farm-based hand hygiene and worker furlough practices on the maximum risk of norovirus infection from three produce commodities (open leaf lettuce, vine tomatoes, and raspberries). [21] METHODS A quantitative microbial risk assessment employing 2D Monte Carlo with parameters extracted from literature was used to estimate norovirus infection from multiple fomite contact scenarios that were defined by: norovirus source (patient vomit/ diarrhoea), location (bathroom/ patient room), and target outcome (ESW/ secondary illness). [22] A quantitative microbial risk assessment (QMRA) approach was applied for risk estimation using dose-response models (DRM) of different surrogate coronaviruses (SARS-CoV-1, MERS-CoV) and the virus responsible for most infectious respiratory illnesses (i. [23] Current evidence on human health risks is largely inferential and based on qualitative data, but comprehensive statistics based on quantitative microbial risk assessment (QMRA) are still lacking. [24] The objective of this study was to conduct QMRA (quantitative microbial risk assessment) of Clostridium perfringens through soy sauce consumption. [25] Here, we use the Quantitative Microbial Risk Assessment framework to examine the risks of community transmission of SARS-CoV-2 through surfaces and to evaluate the effectiveness of hand and surface disinfection as potential interventions. [26] Data from these virus transfer events, and subsequent transfer rate distributions, provide information which can be used to refine quantitative microbial risk assessments. [27] This study carried out a quantitative microbial risk assessment to estimate the health risks associated with Legionella through inhalation of aerosols from showering using water from cisterns after the hurricanes. [28] In addition, this review identifies best practices and explores monitoring targets for studying ARB and ARGs in recycled water to guide future work and identifies key research needs aimed at better supporting quantitative microbial risk assessment focused on recycled water and antibiotic resistance. [29] A Quantitative Microbial Risk Assessment (QMRA) was then conducted to estimate the annual infection risks of HAdV40/41 for non-potable water reuse purposes using predicted concentrations from crAssphage and HPyVs. [30] This step was followed by a quantitative microbial risk assessment (QMRA) model for pathogenic E. [31] It can be useful for describing the variability of the Bacillus cereus Group in Quantitative Microbial Risk Assessment (QMRA). [32] We aimed to assess the risks of Cryptosporidium and Giardia infections associated with drinking water for local residents, based on a quantitative microbial risk assessment, in three densely populated regions of China. [33] Farm-to-fork quantitative microbial risk assessments (QMRA) typically start with a preliminary estimate of initial concentration (Cinitial) of microorganism loading at farm level, consisting of an initial estimate of prevalence (P) and the resulting pathogen levels in animal faeces. [34] Human noroviruses are a leading cause of food- and water-borne disease, which has led to an interest in quantifying norovirus health risks using quantitative microbial risk assessment (QMRA). [35] From a quantitative microbial risk assessment standpoint, the mechanistic basis of the 2C DRM enables transparent modeling of dose-response of antibiotic-resistant SA that has not been possible before. [36] Quantitative microbial risk assessment for the ingestion of lettuce irrigated with untreated and treated WW was estimated. [37] The risk assessment was also carried out based on a semi-quantitative risk matrix approach and as a quantitative microbial risk assessment. [38] We use transient, second-order accurate computational fluid dynamics (CFD) simulations and quantitative microbial risk assessment to estimate aerosol concentrations and the associated risk and assess strategies to mitigate exposure in two distinct concert venues. [39] Then, the reverse quantitative microbial risk assessment (QMRA) provides a quantitative framework for the estimation of acceptable exposure time to protect people from excessive exposure and then manage their health risk. [40] Performing stochastic quantitative microbial risk assessment using soil ingestion parameters from an LMIC setting for children 12–23 months old, we estimated that the median annual infection risk by G. [41] We reviewed outbreaks, management guidance, and exposure studies and used these data to parameterize a quantitative microbial risk assessment (QMRA) model for L. [42] , wastewater-based epidemiology and quantitative microbial risk assessment, for virus surveillance in wastewater are systematically analyzed. [43] Australia) was assessed using a Quantitative Microbial Risk Assessment (QMRA) approach. [44] An understanding of their occurrence and transport in the environment is essential for accurate quantitative microbial risk assessment. [45] Quantitative microbial risk assessment (QMRA), which quantifies pathogen-related health risks across exposure routes, can be informative; however, the utility of QMRA for decision-making is often undermined by data gaps. [46] Findings will inform future quantitative microbial risk assessments associated with private well water use by providing spatially and demographically specific estimates of well water consumption. [47] The current investigation outlines the utilization of quantitative microbial risk assessment (QMRA) to assist Effluent Treatment Plant (ETP) management to determine the best-possible reuse of treated wastewater from 11 ETPs in Delhi. [48] perfringens reduction data were entered into a quantitative microbial risk assessment (QMRA) model to estimate daily infection risks associated with exposures to Cryptosporidium via consumption of treated drinking water. [49] However, quantitative microbial risk analysis (QMRA) showed that the potential infection risks in tap water were still below WHO (10−3) and even EPA (10−4) benchmarks. [50]

quantitative microbial source

Over a wide range of meteorological conditions, water samples were collected and analyzed for fecal indicator bacteria (FIB, used for water quality management) and previously published quantitative microbial source tracking (qMST) markers. [1] The faecal water contamination had both anthropogenic and zoogenic origins identified through quantitative microbial source tracking applying host‐specific Bacteroidales 16S rRNA genetic markers. [2] Water from the affected pool was analysed using quantitative microbial source tracking (QMST) applying host-specific Bacteroidales 16S rRNA genetic markers. [3]

quantitative microbial gene

Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. [1] Viomega includes sample collection, ambient temperature sample preservation, total RNA extraction, physical removal of ribosomal RNAs (rRNAs), preparation of directional Illumina libraries, Illumina sequencing, taxonomic classification based on a database of >110,000 microbial genomes, and quantitative microbial gene expression analysis using a database of ~100 million microbial genes. [2]

quantitative microbial test

Based on quantitative microbial tests, Bacillus cereus was detected in three farms and Staphylococcus aureus was detected in only one farm. [1] The quantitative microbial tests were done by dilution plate technique. [2]