Quantitative Microbial Risk Analysis Research Articles

Estimation of Rotavirus Associated Diarrheal Disease Burden Amongst Primary School Children of Sindh

Introduction: Human Rotavirus Virus (HRV) is amongst the common enteric viral diarrheal diseases that indirectly or directly influence school-going children in low-income countries. Inadequate information exists on the presence of rotavirus, with reference to drinking water supplies of primary schools in Sindh, Pakistan. Aims & Objectives: We estimated the risk of rotavirus-associated diarrhea through drinking water. The study further compared the HRV-associated risk of diarrheal disease by a type of water source. Place and Duration of Study: A cross-sectional survey was conducted in ten representative districts of Sindh from February 2022 to December 2022. The samples for drinking water were collected from primary schools of ten representative districts of Sindh. This study was a part of the WASH Project funded by USAID (USPCASW Seed Grant P-II) Material & Methods: We selected 425 samples of drinking water from primary schools based on pre-defined selection criteria. We used a Quantitative Microbial Risk Analysis using indicator organisms, i.e., E. coli, to predict the possible health risks of rotavirus. Data was entered and analyzed on SPSS version 26. The graphs were developed using Arc GIS version 3. Morbidity and mortality were predicted using the Quantitative Microbial Risk Assessment (QAMRA) model. Results: Our data revealed that the highest daily risk of HRV-associated diarrhea amongst school children was 11 per 10,000 schoolchildren, resulting in 8.4% annual risk, and the minimum risk was estimated to be 1 in 10,000 children. The burden of diseases for rotavirus using the QAMRA model revealed the severity of the diarrhea. Majority of the children presented with mild diarrhea (86%) followed by severe, and the probability of death was less than <1%. The daily risk of HRV infection was highest (estimated to be 7 and 11%) in pupils of Southern Sindh, with an annual risk of 17.4% to 40%. Conclusion: Our study concluded that the children in the primary schools of Sindh were exposed to poor drinking water quality. The surface water source poses the highest risk of HRV-related diarrhea to school children. Thus, it is highly recommended that point-of-use drinking water treatment systems be adopted. The water sanitation and hygiene (WASH) resources are interlinked, so each resource impacts the other; hence, schools urgently need to invest in providing adequate WASH facilities to stop enteric virus transmission through drinking water sources.

A robust scenario analysis approach to water recycling quantitative microbial risk assessment.

The growing need to access recycled water as a source for drinking water supply necessitates management of perceived risks. This study aimed to use quantitative microbial risk analysis (QMRA) to evaluate microbiological risks of indirect water recycling. Scenario analyses of risk probabilities of pathogen infection were conducted to investigate four key quantitative microbial risk assessment model assumptions: treatment process failure, drinking water consumption events per day, inclusion or exclusion of an engineered storage buffer, and treatment process redundancy. Results demonstrated that the proposed water recycling scheme could meet WHO pathogen risk guidelines of ∼10-3 annual risk of infection under 18 simulated scenarios.

Cryptosporidium’s burden of disease attributable to consumption of wastewater-irrigated raw vegetables

Conventional wastewater treatment plants do not effectively remove parasitic protozoa resulting in their presence in wastewater effluent. Therefore, agricultural reuse of wastewater effluent could be a route of Cryptosporidium transmission into the food chain. Samples of secondary wastewater, wastewater-irrigated soil and vegetable samples were collected from an experimental field and analyzed using real-time PCR for quantification of Cryptosporidium oocysts. Quantitative microbial risk analysis (QMRA) was performed to determine the annual disease burden from Cryptosporidium associated with consumption of wastewater-irrigated vegetables. Detection of Clostridium perfringens spores as a potential indicator for the presence of Cryptosporidium was also performed. Cryptosporidium was observed in 64% of the effluent samples ranging from 16 to 162 oocysts L−1, whereas no oocysts were detected in wastewater-irrigated soil and the vegetable samples. The mean annual disease burden for consumption of lettuce (6.6 × 10−5 DALY per person per year (pppy)) was higher than spring onion (3.4 × 10−6 DALY pppy) which both exceeding the WHO guideline of 10−6 DALYs pppy. However, the disease burden was within the acceptable range considering the less stringent level of 10−4 DALY pppy. Clostridium spores were detected in 92% of the effluent samples with no relationship with the presence of Cryptosporidium. The results of this study suggest that agricultural reuse of treated wastewater may not be a major health concern of cryptosporidiosis in a semi-arid region. However, because of the higher risk from lettuce, the choice of an appropriate crop would be needed to completely meet the WHO recommendations for safe reuse of wastewater. The accuracy of the QMRA model could be improved by further investigating the decay rate of oocysts in the same region.

A systematic review and Bayesian meta-analysis about Salmonella spp. prevalence on raw chicken meat

Salmonellosis involving chicken meat is one of the most frequent foodborne diseases registered worldwide. Many studies report the prevalence of Salmonella spp. on chicken meat; however, data are limited or variable. To perform stochastic Quantitative Microbial Risk Analysis, it is essential to input reliable data to estimate the risks, and the Bayesian meta-analysis model allows incorporating the uncertainty of the data into parameters which increases the robustness of the model. In this manuscript, we conduct a systematic review and a logit-normal hierarchical Bayesian meta-analysis model to assess the posterior distribution of Salmonella spp. prevalence of raw chicken meat. The posterior distribution of Salmonella spp. was reported according to carcass processing (whole carcass or cuts); cold status (fresh meat or frozen); place of sampling (retail or slaughterhouse), and geographical region (Brazil, Latin America, North America, Africa, Asia, and Europe). To implement the posterior distribution as uncertainty in stochastic a model, parameters were obtained by linear combination of the posterior distributions of the model. The percentual of variation regarding the heterogeneity between studies is 33.93%. Carcass processing and cold status do not influence Salmonella spp. prevalence. Raw chicken meat collected at slaughterhouses had a 4% higher chance of being positive for Salmonella spp. than those taken at retail. However, this small difference seems to be of minor relevance given the large 95% credible interval around the parameter. The posterior distribution shows lower Salmonella spp. prevalence for Latin America, Brazil, Africa, Europe when compared to North America and Asia. In the sensitivity analysis, the parameters βcold, βsample, and βprocessing were weakly influenced by the priors, however, the relevance of the priors was more evident for the geographic region related parameters. Salmonella Enteritidis was the most widespread serovar identified and only three studies verified the concentration of Salmonella spp. but we were not able to conduct a meta-analysis because the studies omitted the standard deviation.

COVID-19 infection risk from exposure to aerosols of wastewater treatment plants

Fecal shedding of SARS-CoV-2 from COVID-19 patients and presence of the viral RNA in wastewater have extensively been reported. Some wastewater treatment plant (WWTP) processes generate aerosols which have the potential to transmit pathogenic microorganisms and present a health risk for exposed individuals. We analyzed the presence of viral RNA of SARS-CoV-2 in raw wastewater and air samples of WWTPs. The risk that may arise from exposure to virus-contaminated aerosols of wastewater was estimated by developing a quantitative microbial risk analysis (QMRA) method. SARS-CoV-2 was detected in 9 of 24 (37.5%) wastewater samples with a concentration about 104 genomic copies L−1. The viral RNA was also detected in 40% (6/15) of air samples. QMRA analysis showed a relatively high risk of SARS-CoV-2 infection for wastewater workers via exposure to the viral aerosols. The estimated annual infection risk ranged from 1.1 × 10−2 to 2.3 × 10−2 per person per year (PPPY) for wastewater workers which was higher than the reference level recommended by WHO (10−3 pppy). However, due to the lack of data on survival of SARS-CoV-2 in wastewater and its fate in aerosolized state, more research is needed to determine the importance of wastewater in transmission of COVID-19.

Opportunistic pathogens and their health risk in four full-scale drinking water treatment and distribution systems

This study investigated the occurrence of various opportunistic pathogens (OPs) through four drinking water treatment and distribution systems in eastern China. Conventional treatment trains involving coagulation/sedimentation, filtration, and disinfection efficiently removed total coliforms from 1700 to 2300 CFU/L in the influent to undetectable levels in treated and tap water. However, culture-independent qPCR analysis detected Legionella spp., Mycobacterium spp., Mycobacteria avium, Pseudomonas aeruginosa and the amoeba Acanthamoeba spp. in all water samples, reaching maximum tap water concentrations of 5.33, 4.87, 1.63, 3.85, and 4.32 log (gene copies/mL), respectively. Thus, OPs were abundant in tap water despite total coliforms met applicable microbiological standards in China (GB 5749–2006). Occurrence of OPs correlated positively with turbidity and chemical oxygen demand (COD), and negatively with chlorine residual. Turbidity removal by coagulation and COD removal by ozonation (O3) followed by biological activated carbon (BAC) filtration was the treatment train with the highest OPs removal efficiency, and ClO2 was a more effective disinfectant than NaClO. OPs significantly rebounded in the tap water (up to 11-fold for P. aeruginosa and 21-fold for M. avium in tap water). 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. Overall, likely underestimation of the pathogenic risk by culture-dependent quantification of indicator organisms makes it prudent to use molecular approaches to periodically revisit the safety of water distribution systems.

Development of methods to estimate microcystins removal and water treatment resiliency using mechanistic risk modelling

Drinking water treatment processes are capable of removing microcystins but consistent operation of processes optimized for cyanobacterial harmful algal bloom (cHAB) conditions is not fiscally feasible. Therefore, utilities must ready themselves and start the cHAB processes as a reactionary response. Predictive analytics and modelling are impactful tools to prepare water systems for cHABs, but are still in early stages of development. Until those prospective models are completed, a method to determine best actions in advance of a bloom event thus improving system resiliency is needed. In this study, an adaptation of the quantitative microbial risk analysis (QMRA) methodology was applied to develop this method. This method and resulting models were developed around the Toledo (Ohio, USA) water crisis of 2014, but being mechanistic, they are easily adaptable to other systems’ process operations data. Results from this internally validated model demonstrate how rapid action using both powdered activated carbon and measured increases in chlorine dose can mitigate health risks. Our research also demonstrates the importance of modelling the cellular status of the toxins (toxins either in an intact cell or in the water from a lysed cell). Risks were characterized using hazard quotients (HQ) and at the peak of the crisis ranged from a minimum of 0.00244 to a maximum of 2.84 for adults. In simulations where cHAB-specific treatment was used this decreased to 0.00057 and 0.236 respectively. We further outline how this methodology can be used to simulate water system resiliency to likely and aberrant microbial hazard events to plan for the best interventions to protect public health. This method can be used for other hazards expected to be variable in the future, where system prepatory planning is critical to continued public health protection. Considering the water quantity and quality fluctuations occurring and likely to intensify under climate change, this type of computationally supported preparedness is vital to maintaining robust water system resiliency.

Quantitative Assessment of the Number of Escherichia Coli Bacteria and Risk Characterization of Food in Cafeteria of Regional Public Hospital Kendari City

One of the cases of disease originating from food is commonly called foodborne disease which is caused by pathogenic microorganisms or microbes that contaminate food. For this reason, it is necessary to calculate a quantitative microbial risk analysis to see the risk of disease caused by bacteria. This study aims to analyze the quantitative risk of Escherichia coli bacteria in food at the Kendari City Hospital canteen against public health problems. This study used an observational method with a cross sectional approach. This study uses a Quantitative Microbial Risk Assessment (QMRA) approach. The samples in this study were each type of food including rice, vegetables, tofu, chicken and fish as well as tea drinks which were taken by accidental sampling. The results showed that the number of Escherichia coli bacteria in the morning food on the first, second and third day was found in tofu, vegetables, chicken at 3.6 CFU / g and in drinks 3 CFU / ml. The number of Escherichia coli bacteria during the day on the first day was found in vegetables at 6.1 CFU / g, on the second day on vegetables was 9.2 CFU / g, and on the third day in chickens was 14 CFU / g. Characterization of bacterial risk in respondents due to consumption of food in the morning and during the day, shows that Pill = 3.5 x 10-1 which means that food samples positive for Escherichia coli bacteria have a high risk of causing health problems in humans such as diarrhea and disorders other health.

Employing indicator-based geostatistics and quantitative microbial risk analysis to assess the health risks of groundwater use for household demands on the Pingtung Plain, Taiwan.

Because of the limited surface water on the Pingtung Plain, Taiwan, the plain's residents frequently extract groundwater to meet their daily household water demands. The residents may experience gastrointestinal infections due to incidental ingestion of groundwater with fecal pollution. This study used indicator kriging (IK) and quantitative microbial risk analysis (QMRA) to assess the health risks of using groundwater for household cleaning and horticultural irrigation on the Pingtung Plain. First, IK was employed to determine the conditional cumulative distribution function (CCDF) of groundwater Escherichia coli (E. coli). Nonparametric Monte Carlo simulation based on established CCDF was then adopted to characterize the distributions and uncertainty of groundwater E. coli. Finally, QMRA was employed to determine health risks of groundwater use for household cleaning and horticultural irrigation, and the 95th percentiles of the risk distributions were calculated to obtain a representative risk. The study results indicated that the health risks of groundwater use ranged from 3.95 × 10-5 to 2.49 × 10-2 infections/user/year and exceeded the acceptable level, 1 × 10-4 infections/user/year, in most of the aquifers. Accordingly, residents of this plain should not directly extract groundwater for use in daily life.

Quantitative Microbial Risk Analysis for Various Bacterial Exposure Scenarios Involving Greywater Reuse for Irrigation

Greywater reuse can significantly reduce domestic water consumption. While the benefits are promising, risks are still under debate. Using a quantitative microbial risk-assessment model, we assessed the health risks associated with greywater reuse. The pathogens Salmonella enterica, Shigella spp., and Staphylococcus aureus were evaluated due to their possible prevalence in greywater and limited information regarding their potential risk with relation to greywater reuse for irrigation. Various exposure scenarios were investigated. Monte Carlo simulation was used and results were compared to the maximum “acceptable” limit of 10−6 disability-adjusted life years (DALY) set by the World Health Organization. Safe reuse was met for all worst-case exposure scenarios for Staphylococcus aureus, Salmonella enterica and Shigella spp. If their concentrations were kept below 10,000, 50 and 5 cfu/100 mL, respectively. For the best-practice (more realistic) scenarios, safe reuse was met for Staphylococcus aureus if its concentration was kept below 106 cfu/100 mL. Salmonella enterica met the safe reuse requirements if a maximum concentration of 500 cfu/100 mL was maintained and Shigella spp. if a maximum concentration was lower than 5 cfu/100 mL. Based on reported concentrations of these bacteria in greywater, proper treatment and disinfection are recommended.

Characterization of the efficiency and uncertainty of skimmed milk flocculation for the simultaneous concentration and quantification of water-borne viruses, bacteria and protozoa

In this study, the use of skimmed milk flocculation (SMF) to simultaneously concentrate viruses, bacteria and protozoa was evaluated. We selected strains of faecal indicator bacteria and pathogens, such as Escherichia coli and Helicobacter pylori. The viruses selected were adenovirus (HAdV 35), rotavirus (RoV SA-11), the bacteriophage MS2 and bovine viral diarrhoea virus (BVDV). The protozoa tested were Acanthamoeba, Giardia and Cryptosporidium. The mean recoveries with q(RT)PCR were 66% (HAdV 35), 24% (MS2), 28% (RoV SA-11), 15% (BVDV), 60% (E. coli), 30% (H. pylori) and 21% (Acanthamoeba castellanii). When testing the infectivity, the mean recoveries were 59% (HAdV 35), 12% (MS2), 26% (RoV SA-11) and 0.7% (BVDV). The protozoa Giardia lamblia and Cryptosporidium parvum were studied by immunofluorescence with recoveries of 18% and 13%, respectively. Although q(RT)PCR consistently showed higher quantification values (as expected), q(RT)PCR and the infectivity assays showed similar recoveries for HAdV 35 and RoV SA-11. Additionally, we investigated modelling the variability and uncertainty of the recovery with this method to extrapolate the quantification obtained by q(RT)PCR and estimate the real concentration. The 95% prediction intervals of the real concentration of the microorganisms inoculated were calculated using a general non-parametric bootstrap procedure adapted in our context to estimate the technical error of the measurements. SMF shows recoveries with a low variability that permits the use of a mathematical approximation to predict the concentration of the pathogen and indicator with acceptable low intervals. The values of uncertainty may be used for a quantitative microbial risk analysis or diagnostic purposes.

Decay rates of zoonotic pathogens and viral surrogates in soils amended with biosolids and manures and comparison of qPCR and culture derived rates

AimsThe purpose of this study was to establish inactivation decay constants of foodborne pathogens and coliphage in clay and sandy soils for future "downstream" analyses such as quantitative microbial risk analysis and to compare cultivation-dependent and -independent (e.g. qPCR) methods. Methods and resultsSalmonella enterica, Campylobacter jejuni, Listeria monocytogenes, Escherichia coli O157:H7, and Clostridium perfringens, were seeded together with MS2 and ØX174 phages, into three waste matrices (Class B biosolids, swine lagoon effluent, cattle manure), and phosphate buffered saline (PBS) as a control, and applied to two soil types (sandy loam, clay loam) using two management practices (incorporated, surface applied). S. enterica and L. monocytogenes inactivation rates were positively affected (e.g. slower rate) by solid wastes, while C. jejuni was quickly inactivated by day 7 regardless of waste type. The use of qPCR provided more conservative inactivation rates, with qPCR-based rates typically twice as slow as cultivation-based. The effect of soil type and management were less apparent as rates were variably affected. For instance, incorporation of waste negatively impacted (e.g. faster rate) inactivation of Salmonella when measured by qPCR, while the opposite was true when measured by cultivation. Inactivation rates were organism∗waste∗soil∗management dependent since the interactions of these main effects significantly affected most combinations. ConclusionsClass B biosolids and cattle manure most often slowed inactivation when measured by cultivation, but the complex interactions between variables and organism made sweeping conclusions difficult. On the contrary cultivation-independent inactivation rates were negatively affected by solid wastes. Inactivation rates developed by cultivation-dependent and -independent assays needs further scrutiny as interprerations can vary by orders of magnitude depending on the organism∗environment combination. Significance and impact of the studyThis study compares decay rate data based on waste, soil, management and assay type which can be further used in risk assessments.

Co-detection of virulent Escherichia coli genes in surface water sources.

McNemar’s test and the Pearson Chi-square were used to assess the co-detection and observed frequency, respectively, for potentially virulent E. coli genes in river water. Conventional multiplex Polymerase Chain Reaction (PCR) assays confirmed the presence of the aggR gene (69%), ipaH gene (23%) and the stx gene (15%) carried by Enteroaggregative E. coli (EAEC), Enteroinvasive E. coli (EIEC) and Enterohermorrhagic E. coli (EHEC), respectively, in river water samples collected from the Berg River (Paarl, South Africa). Only the aggR gene was present in 23% of samples collected from the Plankenburg River system (Stellenbosch, South Africa). In a comparative study, real-time multiplex PCR assays confirmed the presence of aggR (EAEC) in 69%, stx (EHEC) in 15%, ipaH (EIEC) in 31% and eae (EPEC) in 8% of the river water samples collected from the Berg River. In the Plankenburg River, aggR (EAEC) was detected in 46% of the samples, while eae (EPEC) was present in 15% of the water samples analyzed using real-time multiplex PCR in the Plankenburg River. Pearson Chi-square showed that there was no statistical difference (p > 0.05) between the conventional and real-time multiplex PCRs for the detection of virulent E. coli genes in water samples. However, the McNemar’s test showed some variation in the co-detection of virulent E. coli genes, for example, there was no statistical difference in the misclassification of the discordant results for stx versus ipaH, which implies that the ipaH gene was frequently detected with the stx gene. This study thus highlights the presence of virulent E. coli genes in river water and while early detection is crucial, quantitative microbial risk analysis has to be performed to identify and estimate the risk to human health.

Estimation of norovirus and Ascaris infection risks to urban farmers in developing countries using wastewater for crop irrigation

A quantitative microbial risk analysis-Monte Carlo method was used to estimate norovirus and Ascaris infection risks to urban farmers in developing countries watering their crops with wastewater. For a tolerable additional disease burden of <or=10(-4) DALY loss per person per year (pppy), equivalent to 1 percent of the diarrhoeal disease burden in developing countries, a norovirus reduction of 1-2 log units and an Ascaris egg reduction to 10-100 eggs per litre are required. These are easily achieved by minimal wastewater treatment-for example, a sequential batch-fed three tank/pond system. Hygiene improvement through education and regular deworming are essential complementary inputs to protect the health of urban farmers.

Quantitative Microbial Risk Analysis to evaluate health effects of interventions in the urban water system of Accra, Ghana

A quantitative microbial risk assessment was applied to evaluate the microbial risks of the Accra Urban Water System (AUWS). The exposure assessment was based on the count of indicator organisms in waste water from open roadside drains and in water and sand samples from the beach. The predicted total disease burden generated in a representative catchment of the AUWS (Odaw Catchment) was 36,329 Disability Adjusted Life Years (DALYs) per year, of which 12 and 88% are caused by, respectively, shortcomings in the water supply system and inappropriate sanitation. The DALYs per person per year were above the WHO reference value. The open roadside drain had the highest contribution to the disease burden. Of four possible interventions evaluated for health risk reduction, the highest efficiency in terms of DALYs averted per euro invested would be achieved by providing covers for the open roadside drains.

Estimators of annual probability of infection for quantitative microbial risk assessment

Four estimators of annual infection probability were compared pertinent to Quantitative Microbial Risk Analysis (QMRA). A stochastic model, the Gold Standard, was used as the benchmark. It is a product of independent daily infection probabilities which in turn are based on daily doses. An alternative and commonly-used estimator, here referred to as the Naïve, assumes a single daily infection probability from a single value of daily dose. The typical use of this estimator in stochastic QMRA involves the generation of a distribution of annual infection probabilities, but since each of these is based on a single realisation of the dose distribution, the resultant annual infection probability distribution simply represents a set of inaccurate estimates. While the medians of both distributions were within an order of magnitude for our test scenario, the 95th percentiles, which are sometimes used in QMRA as conservative estimates of risk, differed by around one order of magnitude. The other two estimators examined, the Geometric and Arithmetic, were closely related to the Naïve and use the same equation, and both proved to be poor estimators. Lastly, this paper proposes a simple adjustment to the Gold Standard equation accommodating periodic infection probabilities when the daily infection probabilities are unknown.

Including operational data in QMRA model: development and impact of model inputs

A Monte Carlo model, based on the Quantitative Microbial Risk Analysis approach (QMRA), has been developed to assess the relative risks of infection associated with the presence of Cryptosporidium and Giardia in drinking water. The impact of various approaches for modelling the initial parameters of the model on the final risk assessments is evaluated. The Monte Carlo simulations that we performed showed that the occurrence of parasites in raw water was best described by a mixed distribution: log-Normal for concentrations > detection limit (DL), and a uniform distribution for concentrations < DL. The selection of process performance distributions for modelling the performance of treatment (filtration and ozonation) influences the estimated risks significantly. The mean annual risks for conventional treatment are: 1.97E-03 (removal credit adjusted by log parasite = log spores), 1.58E-05 (log parasite = 1.7 x log spores) or 9.33E-03 (regulatory credits based on the turbidity measurement in filtered water). Using full scale validated SCADA data, the simplified calculation of CT performed at the plant was shown to largely underestimate the risk relative to a more detailed CT calculation, which takes into consideration the downtime and system failure events identified at the plant (1.46E-03 vs. 3.93E-02 for the mean risk).

Wastewater irrigation of salad crops: further evidence for the evaluation of the WHO guidelines

This paper presents the results of an experiment on salad crop irrigation with waste stabilisation pond effluents, conducted in Southeast Brazil. Over about 18 months several trials were carried out using different effluent qualities to irrigate lettuce, kale, arugula, spinach, and green pepper. Equations for predicting the bacterial quality of irrigated crops (E.coli per gram) based on the irrigation water quality (E.coli per 100 mL) were derived for low and high growing crops. The quantitative microbial risk analysis (QMRA) technique, using pathogen-ingestion scenarios based on these field data and on official statistics of vegetables consumption in Brazil, was used to estimate infection risks arising from the consumption of wastewater irrigated crops. It is inferred that irrigation with effluents complying with the WHO guidelines for unrestricted irrigation should result in salad crops acceptable for consumption.

Short Communication: Quantification of the Transmission of Microorganisms to Milk via Dirt Attached to the Exterior of Teats

Pathogens and spoilage microorganisms can be transmitted to milk via dirt (e.g., feces, bedding material, soil, or a combination of these) attached to the exterior of the cows’ teats. To determine the relevance of this pathway and to perform quantitative microbial risk analysis of the microbial contamination of farm tank milk (FTM), it is important to know the amount of dirt transmitted to milk via the exterior of teats. In this study at 11 randomly selected Dutch farms the amount of dirt transmitted to milk via the exterior of teats is determined using spores of mesophilic aerobic bacteria as a marker for transmitted dirt. The amount of transmitted dirt to milk varied among farms from ∼3 to 300mg/L, with an average of 59mg/L. The usefulness of the data for microbial risk analyses is briefly illustrated using the contamination of FTM with spores of butyric acid bacteria as a case study. In a similar way the data can be used to identify measures to control the contamination of FTM with other microorganisms or chemical residues.

Removal and fate of Cryptosporidium parvum, Clostridium perfringens and small-sized centric diatoms ( Stephanodiscus hantzschii) in slow sand filters

The decimal elimination capacity (DEC) of slow sand filtration (SSF) for Cryptosporidium parvum was assessed to enable quantitative microbial risk analysis of a drinking water production plant. A mature pilot plant filter of 2.56 m 2 was loaded with C. parvum oocysts and two other persistent organisms as potential surrogates; spores of Clostridium perfringens (SCP) and the small-sized (4–7 μm) centric diatom (SSCD) Stephanodiscus hantzschii. Highly persistent micro-organisms that are retained in slow sand filters are expected to accumulate and eventually break through the filter bed. To investigate this phenomenon, a dosing period of 100 days was applied with an extended filtrate monitoring period of 150 days using large-volume sampling. Based on the breakthrough curves the DEC of the filter bed for oocysts was high and calculated to be 4.7 log. During the extended filtrate monitoring period the spatial distribution of the retained organisms in the filter bed was determined. These data showed little risk of accumulation of oocysts in mature filters most likely due to predation by zooplankton. The DEC for the two surrogates, SCP and SSCD, was 3.6 and 1.8 log, respectively. On basis of differences in transport behaviour, but mainly because of the high persistence compared to the persistence of oocysts, it was concluded that both spores of sulphite-reducing clostridia (incl. SCP) and SSCD are unsuited for use as surrogates for oocyst removal by slow sand filters. Further research is necessary to elucidate the role of predation in Cryptosporidium removal and the fate of consumed oocysts.