scholarly journals Quantitative Microbial Risk Assessment for Workers Exposed to Bioaerosol in Wastewater Treatment Plants Aimed at the Choice and Setup of Safety Measures

2018 ◽  
Vol 15 (7) ◽  
pp. 1490 ◽  
Author(s):  
Annalaura Carducci ◽  
Gabriele Donzelli ◽  
Lorenzo Cioni ◽  
Ileana Federigi ◽  
Roberto Lombardi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sensitivity Analysis ◽  
Wastewater Treatment ◽  
Health Risk ◽  
Average Risk ◽  
Quantitative Microbial Risk Assessment ◽  
Exposure Limits ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Impact

Biological risk assessment in occupational settings currently is based on either qualitative or semiquantitative analysis. In this study, a quantitative microbial risk assessment (QMRA) has been applied to estimate the human adenovirus (HAdV) health risk due to bioaerosol exposure in a wastewater treatment plant (WWTP). A stochastic QMRA model was developed considering HAdV as the index pathogen, using its concentrations in different areas and published dose–response relationship for inhalation. A sensitivity analysis was employed to examine the impact of input parameters on health risk. The QMRA estimated a higher average risk in sewage influent and biological oxidation tanks (15.64% and 12.73% for an exposure of 3 min). Sensitivity analysis indicated HAdV concentration as a predominant factor in the estimated risk. QMRA results were used to calculate the exposure limits considering four different risk levels (one illness case per 100, 1.000, 10.000, and 100.000 workers): for 3 min exposures, we obtained 565, 170, 54, and 6 GC/m3 of HAdV. We also calculated the maximum time of exposure for each level for different areas. Our findings can be useful to better define the effectiveness of control measures, which would thus reduce the virus concentration or the exposure time.

scholarly journals Quantitative Health Risk Assessment of Wastewater Treatment Plant Worker Exposed to Staphylococcus Aureus Bioaerosol During Warm and Cold Periods: Disease Burden and Sensitivity Analysis

2021 ◽  
Author(s):  
Jia-xin Ma ◽  
Bei-bei Cui ◽  
Man-li Liu ◽  
Jie Yuan ◽  
Cheng Yan
Keyword(s):  
Risk Assessment ◽  
Staphylococcus Aureus ◽  
Sensitivity Analysis ◽  
Wastewater Treatment ◽  
Health Risk ◽  
Disease Burden ◽  
Quantitative Estimation ◽  
Ingestion Rate ◽  
Treatment Plant ◽  
Quantitative Microbial Risk Assessment

Abstract Biological treatment in wastewater treatment plants (WWTPs) releases high amounts of bioaerosols carrying a variety of pathogens. Quantitative microbial risk assessment (QMRA) is a framework prevalently intended for the quantitative estimation of health risks for occupational exposure scenarios (e.g. in WWTPs). However, the quantitative contributions of health-risk-estimate inputted variable parameters remain ambiguous. Therefore, this research aimed to study the disease burden of workers exposed to Staphylococcus aureus bioaerosol during warm and cold periods and to strictly quantify the contributions of the inputted parameters of disease burden by sensitivity analysis based on Monte Carlo simulation. The results showed that the disease health risk burden in the warm period was higher than in the cold period, disease health risk burden in the rotating-disc aeration mode was regularly higher than in the microporous aeration mode. The disease health risk burden of the workers with personal protective equipment (PPE) almost all satisfied the WHO benchmark (≤10E-6 DALYs pppy), and was consistently lower by one or two orders of magnitude than the workers without PPE in both warm and cold periods. Referring to the sensitivity analysis, exposure concentration and aerosol ingestion rate were the most and second predominant factor for the estimated risk in all exposure scenarios, respectively. The sensitivity of the removal fraction by employing PPE ranked third in the contribution to disease health risk burden. In addition, no remarkable differences were revealed in the sensitivity percentage ratio between warm and cold periods. This research can deepen the understanding of the QMRA framework and promote the development of sensitivity analysis, especially under various meteorological conditions (warm and cold periods).

scholarly journals Quantitative microbial risk assessment of SARS-CoV-2 for workers in wastewater treatment plants

2021 ◽  
Vol 754 ◽  
pp. 142163 ◽  
Author(s):  
Rafael Newton Zaneti ◽  
Viviane Girardi ◽  
Fernando Rosado Spilki ◽  
Kristina Mena ◽  
Ana Paula Campos Westphalen ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Wastewater Treatment ◽  
Wastewater Treatment Plants ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk

scholarly journals Sapovirus in Wastewater Treatment Plants in Tunisia: Prevalence, Removal, and Genetic Characterization

2018 ◽  
Vol 84 (6) ◽  
pp. e02093-17 ◽  
Author(s):  
Miguel F. Varela ◽  
Imen Ouardani ◽  
Tsuyoshi Kato ◽  
Syunsuke Kadoya ◽  
Mahjoub Aouni ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Wastewater Treatment ◽  
Bayesian Estimation ◽  
Quantitative Pcr ◽  
Censored Data ◽  
Wastewater Treatment Plants ◽  
Quantitative Microbial Risk Assessment ◽  
Content Type ◽  
Microbial Risk Assessment ◽  
Microbial Risk

ABSTRACTSapovirus(SaV), from theCaliciviridaefamily, is a genus of enteric viruses that cause acute gastroenteritis. SaV is shed at high concentrations with feces into wastewater, which is usually discharged into aquatic environments or reused for irrigation without efficient treatments. This study analyzed the incidence of human SaV in four wastewater treatment plants from Tunisia during a period of 13 months (December 2009 to December 2010). Detection and quantification were carried out using reverse transcription-quantitative PCR (RT-qPCR) methods, obtaining a prevalence of 39.9% (87/218). Sixty-one positive samples were detected in untreated water and 26 positive samples in processed water. The Dekhila plant presented the highest contamination levels, with a 63.0% prevalence. A dominance of genotype I.2 was observed on 15 of the 24 positive samples that were genetically characterized. By a Bayesian estimation algorithm, the SaV density in wastewater was estimated using left-censored data sets. The mean value of log SaV concentration in untreated wastewater ranged between 2.7 and 4.5 logs. A virus removal efficiency of 0.2 log was calculated for the Dekhila plant as the log ratio posterior distributions between untreated and treated wastewater. Multiple quantitative values obtained in this study must be available in quantitative microbial risk assessment in Tunisia as parameter values reflecting local conditions.IMPORTANCEHuman sapovirus (SaV) is becoming more prevalent worldwide and organisms in this genus are recognized as emerging pathogens associated with human gastroenteritis. The present study describes novel findings on the prevalence, seasonality, and genotype distribution of SaV in Tunisia and Northern Africa. In addition, a statistical approximation using Bayesian estimation of the posterior predictive distribution (“left-censored” data) was employed to solve methodological problems related with the limit of quantification of the quantitative PCR (qPCR). This approach would be helpful for the future development of quantitative microbial risk assessment procedures for wastewater.

Multiple-Strain Approach and Probabilistic Modeling of Consumer Habits in Quantitative Microbial Risk Assessment: A Quantitative Assessment of Exposure to Staphylococcal Enterotoxin A in Raw Milk

2016 ◽  
Vol 79 (3) ◽  
pp. 432-441 ◽  
Author(s):  
MATTEO CROTTA ◽  
RITA RIZZI ◽  
GIORGIO VARISCO ◽  
PAOLO DAMINELLI ◽  
ELENA COSCIANI CUNICO ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Consumer Behavior ◽  
Raw Milk ◽  
Staphylococcal Enterotoxin ◽  
Quantitative Microbial Risk Assessment ◽  
Staphylococcal Enterotoxin A ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
Household Level ◽  
The Impact

ABSTRACT Quantitative microbial risk assessment (QMRA) models are extensively applied to inform management of a broad range of food safety risks. Inevitably, QMRA modeling involves an element of simplification of the biological process of interest. Two features that are frequently simplified or disregarded are the pathogenicity of multiple strains of a single pathogen and consumer behavior at the household level. In this study, we developed a QMRA model with a multiple-strain approach and a consumer phase module (CPM) based on uncertainty distributions fitted from field data. We modeled exposure to staphylococcal enterotoxin A in raw milk in Lombardy; a specific enterotoxin production module was thus included. The model is adaptable and could be used to assess the risk related to other pathogens in raw milk as well as other staphylococcal enterotoxins. The multiple-strain approach, implemented as a multinomial process, allowed the inclusion of variability and uncertainty with regard to pathogenicity at the bacterial level. Data from 301 questionnaires submitted to raw milk consumers were used to obtain uncertainty distributions for the CPM. The distributions were modeled to be easily updatable with further data or evidence. The sources of uncertainty due to the multiple-strain approach and the CPM were identified, and their impact on the output was assessed by comparing specific scenarios to the baseline. When the distributions reflecting the uncertainty in consumer behavior were fixed to the 95th percentile, the risk of exposure increased up to 160 times. This reflects the importance of taking into consideration the diversity of consumers' habits at the household level and the impact that the lack of knowledge about variables in the CPM can have on the final QMRA estimates. The multiple-strain approach lends itself to use in other food matrices besides raw milk and allows the model to better capture the complexity of the real world and to be capable of geographical specificity.

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