scholarly journals Quantifying public health risks from exposure to waterborne pathogens during river bathing as a basis for reduction of disease burden

2020 ◽  
Vol 18 (3) ◽  
pp. 292-305
Author(s):  
M. M. Majedul Islam ◽  
Md. Atikul Islam
Keyword(s):  
Public Health ◽  
Health Risk ◽  
Quantitative Microbial Risk Assessment ◽  
Public Health Risk ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Public ◽  
E Coli ◽  
Untreated Sewage ◽  
Three Rivers

Abstract A Quantitative Microbial Risk Assessment (QMRA) technique was applied to assess the public health risk from exposure to infectious microorganisms at bathing areas of three rivers in Bangladesh. The QMRA assessed the probability of illness due to the accidental ingestion of river water impacted by untreated sewage. The simplified QMRA was based on average concentrations of four reference pathogens Escherichia coli (E. coli) O157:H7, Cryptosporidium spp, norovirus and rotavirus relative to indicator bacterium E. coli. Public health risk was estimated as the probability of infection and illness from a single exposure of bathers. The risks of illness were ranged from 7 to 10% for E. coli O157:H7, 13 to 19% for Cryptosporidium, 7 to 10% for norovirus and 12 to 17% for rotavirus. The overall risk of illness at the rivers was slightly higher in children (9–19%) compared to adults (7–16%). The risks of illness in individuals exposed to the river bathing were unacceptably high, exceeding the USEPA acceptable risk of 3–6 illnesses per hundred bathing events. This study gives a basis for reducing the burden of disease in the population by applying appropriate risk management. Findings and methods of this study will be helpful for other countries with similar socio-economic and geographic settings.

Quantitative Microbial Risk Assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes in Leafy Green Vegetables Consumed at Salad Bars

2010 ◽  
Vol 73 (2) ◽  
pp. 274-285 ◽  
Author(s):  
E. FRANZ ◽  
S. O. TROMP ◽  
H. RIJGERSBERG ◽  
H. J. van der FELS-KLERX
Keyword(s):  
Public Health ◽  
Escherichia Coli ◽  
Risk Assessment ◽  
Monte Carlo ◽  
Escherichia Coli O157 ◽  
Quantitative Microbial Risk Assessment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Public ◽  
E Coli

Fresh vegetables are increasingly recognized as a source of foodborne outbreaks in many parts of the world. The purpose of this study was to conduct a quantitative microbial risk assessment for Escherichia coli O157:H7, Salmonella, and Listeria monocytogenes infection from consumption of leafy green vegetables in salad from salad bars in The Netherlands. Pathogen growth was modeled in Aladin (Agro Logistics Analysis and Design Instrument) using time-temperature profiles in the chilled supply chain and one particular restaurant with a salad bar. A second-order Monte Carlo risk assessment model was constructed (using @Risk) to estimate the public health effects. The temperature in the studied cold chain was well controlled below 5°C. Growth of E. coli O157:H7 and Salmonella was minimal (17 and 15%, respectively). Growth of L. monocytogenes was considerably greater (194%). Based on first-order Monte Carlo simulations, the average number of cases per year in The Netherlands associated the consumption leafy greens in salads from salad bars was 166, 187, and 0.3 for E. coli O157:H7, Salmonella, and L. monocytogenes, respectively. The ranges of the average number of annual cases as estimated by second-order Monte Carlo simulation (with prevalence and number of visitors as uncertain variables) were 42 to 551 for E. coli O157:H7, 81 to 281 for Salmonella, and 0.1 to 0.9 for L. monocytogenes. This study included an integration of modeling pathogen growth in the supply chain of fresh leafy vegetables destined for restaurant salad bars using software designed to model and design logistics and modeling the public health effects using probabilistic risk assessment software.

scholarly journals Metagenomic characterization of creek sediment microbial communities from a major agricultural region in Salinas, California

2019 ◽  
Author(s):  
Brittany J. Suttner ◽  
Eric R. Johnston ◽  
Luis H. Orellana ◽  
Luis M. Rodriguez-R ◽  
Janet K. Hatt ◽  
...  
Keyword(s):  
Public Health ◽  
Antibiotic Resistance ◽  
Health Risk ◽  
Microbial Communities ◽  
Resistance Genes ◽  
Antibiotic Resistance Genes ◽  
Agricultural Runoff ◽  
Public Health Risk ◽  
The Public ◽  
E Coli

ABSTRACTLittle is known about the public health risks associated with natural creek sediments that are affected by runoff and fecal pollution from agricultural and livestock practices. For instance, the persistence of foodborne pathogens originating from agricultural activities such as Shiga Toxin-producing E. coli (STEC) in such sediments remains poorly quantified. Towards closing these knowledge gaps, the water-sediment interface of two creeks in the Salinas River Valley was sampled over a nine-month period using metagenomics and traditional culture-based tests for STEC. Our results revealed that these sediment communities are extremely diverse and comparable to the functional and taxonomic diversity observed in soils. With our sequencing effort (~4 Gbp per library), we were unable to detect any pathogenic Escherichia coli in the metagenomes of 11 samples that had tested positive using culture-based methods, apparently due to relatively low pathogen abundance. Further, no significant differences were detected in the abundance of human- or cow-specific gut microbiome sequences compared to upstream, more pristine (control) sites, indicating natural dilution of anthropogenic inputs. Notably, a high baseline level of metagenomic reads encoding antibiotic resistance genes (ARGs) was found in all samples and was significantly higher compared to ARG reads in metagenomes from other environments, suggesting that these communities may be natural reservoirs of ARGs. Overall, our metagenomic results revealed that creek sediments are not a major sink for anthropogenic runoff and the public health risk associated with these sediment microbial communities may be low.IMPORTANCECurrent agricultural and livestock practices contribute to fecal contamination in the environment and the spread of food and water-borne disease and antibiotic resistance genes (ARGs). Traditionally, the level of pollution and risk to public health is assessed by culture-based tests for the intestinal bacterium, E. coli. However, the accuracy of these traditional methods (e.g., low quantification, and false positive signal when PCR-based) and their suitability for sediments remains unclear. We collected sediments for a time series metagenomics study from one of the most highly productive agricultural regions in the U.S. in order to assess how agricultural runoff affects the native microbial communities and if the presence of STEC in sediment samples can be detected directly by sequencing. Our study provided important information on the potential for using metagenomics as a tool for assessment of public health risk in natural environments.

Prevalence and Concentration of Bacterial Pathogens in Raw Produce and Minimally Processed Packaged Salads Produced in and for The Netherlands

2014 ◽  
Vol 77 (3) ◽  
pp. 388-394 ◽  
Author(s):  
LUCAS M. WIJNANDS ◽  
ELLEN H. M. DELFGOU-van ASCH1 ◽  
MARIEKE E. BEEREPOOT-MENSINK ◽  
ALICE van der MEIJ-FLORIJN ◽  
IFE FITZ-JAMES ◽  
...  
Keyword(s):  
Public Health ◽  
The Netherlands ◽  
Health Risk ◽  
Contamination Level ◽  
Minimally Processed ◽  
Public Health Risk ◽  
The Public ◽  
E Coli ◽  
Laboratory Capacity ◽  
Oak Tree

Recent outbreaks with vegetable or fruits as vehicles have raised interest in the characterization of the public health risk due to microbial contamination of these commodities. Because qualitative and quantitative data regarding prevalence and concentration of various microbes are lacking, we conducted a survey to estimate the prevalence and contamination level of raw produce and the resulting minimally processed packaged salads as sold in The Netherlands. A dedicated sampling plan accounted for the amount of processed produce in relation to the amount of products, laboratory capacity, and seasonal influences. Over 1,800 samples of produce and over 1,900 samples of ready-to-eat mixed salads were investigated for Salmonella enterica serovars, Campylobacter spp., Escherichia coli O157, and Listeria monocytogenes. The overall prevalence in raw produce varied between 0.11% for E. coli O157 and L. monocytogenes and 0.38% for Salmonella. Prevalence point estimates for specific produce/pathogen combinations ranged for Salmonella from 0.53% in iceberg lettuce to 5.1% in cucumber. For Campylobacter, this ranged from 0.83% in endive to 2.7% in oak tree lettuce. These data will be used to determine the public health risk posed by the consumption of ready-to-eat mixed salads in The Netherlands.

scholarly journals Health-risk assessment for roof-harvested rainwater via QMRA in Ikorodu area, Lagos, Nigeria

2021 ◽  
Author(s):  
Chukwuemeka Kingsley John ◽  
Jaan H. Pu ◽  
Rodrigo Moruzzi ◽  
Manish Pandey
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Rainwater Harvesting ◽  
Treatment Technique ◽  
Quantitative Microbial Risk Assessment ◽  
Household Water Treatment ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
E Coli ◽  
Risk Of Exposure

Abstract This paper presents a study to assess the roof-harvested rainwater (RHRW) in the Ikorodu area of Lagos state, Nigeria, and recommends guidance to minimise the health risk for its households. The types, design and use of rainwater harvesting systems have been evaluated in the study area to inspect the human risk of exposure to Escherichia coli (E. coli). To achieve these objectives, a detailed survey involving 125 households has been conducted which showed that 25% of them drink RHRW. Quantitative microbial risk assessment (QMRA) analysis has been used to quantify the risk of exposure to harmful E. coli from RHRW utilised as potable water, based on the ingestion of 2 L of rainwater per day per capita. Results have revealed that the maximum E. coli exposure risk from the consumption of RHRW, without application of any household water treatment technique (HHTTs) and with application of alum only, were 100 and 96 respectively, for the estimated number of infection risk per 10,000 exposed households per year. This estimation has been done based on 7% of E. coli as viable and harmful. Conclusively, it is necessary that a form of disinfectant be applied to the RHRW before use.

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.

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