6 resultados para QMRA


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Modern statistical models and computational methods can now incorporate uncertainty of the parameters used in Quantitative Microbial Risk Assessments (QMRA). Many QMRAs use Monte Carlo methods, but work from fixed estimates for means, variances and other parameters. We illustrate the ease of estimating all parameters contemporaneously with the risk assessment, incorporating all the parameter uncertainty arising from the experiments from which these parameters are estimated. A Bayesian approach is adopted, using Markov Chain Monte Carlo Gibbs sampling (MCMC) via the freely available software, WinBUGS. The method and its ease of implementation are illustrated by a case study that involves incorporating three disparate datasets into an MCMC framework. The probabilities of infection when the uncertainty associated with parameter estimation is incorporated into a QMRA are shown to be considerably more variable over various dose ranges than the analogous probabilities obtained when constants from the literature are simply ‘plugged’ in as is done in most QMRAs. Neglecting these sources of uncertainty may lead to erroneous decisions for public health and risk management.

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Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to pathogens from potable and non-potable uses of roof-harvested rainwater in South East Queensland (SEQ). A total of 84 rainwater samples were analysed for the presence of faecal indicators (using culture based methods) and zoonotic bacterial and protozoan pathogens using binary and quantitative PCR (qPCR). The concentrations of Salmonella invA, and Giardia lamblia β-giradin genes ranged from 65-380 genomic units/1000 mL and 9-57 genomic units/1000 mL of water, respectively. After converting gene copies to cell/cyst number, the risk of infection from G. lamblia and Salmonella spp. associated with the use of rainwater for bi-weekly garden hosing was calculated to be below the threshold value of 1 extra infection per 10,000 persons per year. However, the estimated risk of infection from drinking the rainwater daily was 44-250 (for G. lamblia) and 85-520 (for Salmonella spp.) infections per 10,000 persons per year. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically discussed. Nevertheless, it would seem prudent to disinfect rainwater for potable use.

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A total of 214 rainwater samples from 82 tanks were collected in urban Southeast Queensland (SEQ) in Australia and analysed for the zoonotic bacterial and protozoan pathogen using real-time binary PCR and quantitative PCR (qPCR). Quantitative Microbial Risk Assessment (QMRA) analysis was used to quantify the risk of infection associated with the exposure to potential pathogens from potable and non-potable uses of roof-harvested rainwater. Of the 214 samples tested, 10.7%, 9.8%, and 5.6%, and 0.4% samples were positive for Salmonella invA, Giardia lamblia β-giardin , Legionella pneumophila mip, and Campylobacter jejuni mapA genes. Cryptosporidium parvum could not be detected. The estimated numbers of viable Salmonella spp., G. lamblia β-giradin, and L. pneumophila genes ranged from 1.6 × 101 to 9.5 × 101 cells, 1.4 × 10-1 to 9.0 × 10-1 cysts, and 1.5 × 101 to 4.3 × 101 per 1000 ml of water, respectively. Six risk scenarios were considered from exposure to Salmonella spp., G. lamblia and L. pneumophila. For Salmonella spp., and G. lamblia, these scenarios were: (1) liquid ingestion due to drinking of rainwater on a daily basis (2) accidental liquid ingestion due to garden hosing twice a week (3) aerosol ingestion due to showering on a daily basis, and (4) aerosol ingestion due to hosing twice a week. For L. pneumophila, these scenarios were: (5) aerosol inhalation due to showering on a daily basis, and (6) aerosol inhalation due to hosing twice a week. The risk of infection from Salmonella spp., G. lamblia, and L. pneumophila associated with the use of rainwater for showering and garden hosing was calculated to be well below the threshold value of one extra infection per 10,000 persons per year in urban SEQ. However, the risk of infection from ingesting Salmonella spp. and G. lamblia via drinking exceeds this threshold value, and indicates that if undisinfected rainwater were ingested by drinking, then the gastrointestinal diseases of Salmonellosis and Giardiasis is expected to range from 5.0 × 100 to 2.8 × 101 (Salmonellosis) and 1.0 × 101 to 6.4 × 101 (Giardiasis) cases per 10,000 persons per year, respectively. Since this health risk seems higher than that expected from the reported incidences of gastroenteritis, the assumptions used to estimate these infection risks are critically examined. Nonetheless, it would seem prudent to disinfect rainwater for potable use.

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Reuse of treated sewage effluent for the irrigation of horticultural crops is being propounded and practiced as a means of alleviating pressure on freshwater resources. Concerns have been raised. however, as to the risk to human health, primarily disease, associated with this practice. Quantitative Microbial Risk Assessment (QMRA) is a useful tool for estimating this risk. We describe how QMRA works and the current state of knowledge of the components of QMRA models for the horticultural reuse scenario.

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The use of reclaimed wastewater for irrigation of horticultural crops is commonplace in many parts of the world and is likely to increase. Concerns about risks to human health arising from such practice, especially with respect to infection with microbial pathogens, are common. Several factors need to be considered when attempting to quantify the risk posed to a population, such as the concentration of pathogens in the source water, water treatment efficiency, the volume of water coming into contact with the crop, and the die-off rate of pathogens in the environment. Another factor, which has received relatively less attention, is the amount of food consumed. Plainly, higher consumption rates place one at greater risk of becoming infected. The amount of vegetables consumed is known to vary among ethic groups. We use Quantitative Microbial Risk Assessment Modelling (QMRA) to see if certain ethnic groups are exposed to higher risks by virtue of their consumption behaviour. The results suggest that despite the disparities in consumption rates by different ethnic groups they generally all faced comparable levels of risks. We conclude by suggesting that QMRA should be used to assess the relative levels of risk faced by groups based on divisions other than ethnicity, such as those with compromised immune systems.

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