Cross-Contamination During Food Preparation: A Mechanistic Model Applied to Chicken-Borne Campylobacter

We develop a model for bacterial cross-contamination during food preparation in the domestic kitchen and apply this to the case of Campylobacter-contaminated chicken breast. Building blocks of the model are the routines performed during food preparation, with their associated probabilities of bacterial transfer between food items and kitchen utensils. The model is used in a quantitative microbiological risk assessment (QMRA) of Campylobacter in the Netherlands. Using parameter values from the literature and performing elementary sensitivity analyses, we show that cross-contamination can contribute significantly to the risk of Campylobacter infection and find that cleaning frequency of kitchen utensils and thoroughness of rinsing of raw food items after preparation has more impact on cross-contamination than previously emphasized. Furthermore, we argue that especially more behavioral data on hygiene during food preparation is needed for a comprehensive Campylobacter risk assessment.     

A Poultry-Processing Model for Quantitative Microbiological Risk Assessment

A poultry-processing model for a quantitative microbiological risk assessment (QMRA) of campylobacter is presented, which can also be applied to other QMRAs involving poultry processing. The same basic model is applied in each consecutive stage of industrial processing. It describes the effects of inactivation and removal of the bacteria, and the dynamics of cross-contamination in terms of the transfer of campylobacter from the intestines to the carcass surface and the environment, from the carcasses to the environment, and from the environment to the carcasses. From the model it can be derived that, in general, the effect of inactivation and removal is dominant for those carcasses with high initial bacterial loads, and cross-contamination is dominant for those with low initial levels. In other QMRA poultry-processing models, the input-output relationship between the numbers of bacteria on the carcasses is usually assumed to be linear on a logarithmic scale. By including some basic mechanistics, it is shown that this may not be realistic. As nonlinear behavior may affect the predicted effects of risk mitigations; this finding is relevant for risk management. Good knowledge of the variability of bacterial loads on poultry entering the process is important. The common practice in microbiology to only present geometric mean of bacterial counts is insufficient: arithmetic mean are more suitable, in particular, to describe the effect of cross-contamination. The effects of logistic slaughter (scheduled processing) as a risk mitigation strategy are predicted to be small. Some additional complications in applying microbiological data obtained in processing plants are discussed.     

Harnessing the Theoretical Foundations of the Exponential and Beta‐Poisson Dose‐Response Models to Quantify Parameter Uncertainty Using Markov Chain Monte Carlo

Dose‐response models are the essential link between exposure assessment and computed risk values in quantitative microbial risk assessment, yet the uncertainty that is inherent to computed risks because the dose‐response model parameters are estimated using limited epidemiological data is rarely quantified. Second‐order risk characterization approaches incorporating uncertainty in dose‐response model parameters can provide more complete information to decisionmakers by separating variability and uncertainty to quantify the uncertainty in computed risks. Therefore, the objective of this work is to develop procedures to sample from posterior distributions describing uncertainty in the parameters of exponential and beta‐Poisson dose‐response models using Bayes's theorem and Markov Chain Monte Carlo (in OpenBUGS). The theoretical origins of the beta‐Poisson dose‐response model are used to identify a decomposed version of the model that enables Bayesian analysis without the need to evaluate Kummer confluent hypergeometric functions. Herein, it is also established that the beta distribution in the beta‐Poisson dose‐response model cannot address variation among individual pathogens, criteria to validate use of the conventional approximation to the beta‐Poisson model are proposed, and simple algorithms to evaluate actual beta‐Poisson probabilities of infection are investigated. The developed MCMC procedures are applied to analysis of a case study data set, and it is demonstrated that an important region of the posterior distribution of the beta‐Poisson dose‐response model parameters is attributable to the absence of low‐dose data. This region includes beta‐Poisson models for which the conventional approximation is especially invalid and in which many beta distributions have an extreme shape with questionable plausibility.     

A Model of Hygiene Practices and Consumption Patterns in the Consumer Phase

A mathematical model is presented, which addresses individual hygiene practices during food preparation and consumption patterns in private homes. Further, the model links food preparers and consumers based on their relationship to household types. For different age and gender groups, the model estimates (i) the probability of ingesting a meal where precautions have not been taken to avoid the transfer of microorganisms from raw food to final meal (a risk meal), exemplified by the event that the cutting board was not washed during food preparation, and (ii) the probability of ingesting a risk meal in a private home, where chicken was the prepared food item (a chicken risk meal). Chicken was included in the model, as chickens are believed to be the major source of human exposure to the foodborne pathogen Campylobacter. Monte Carlo simulations showed that the probability of ingesting a risk meal was highest for young males (aged 18-29 years) and lowest for the elderly above 60 years of age. Children aged 0-4 years had a higher probability of ingesting a risk meal than children aged 5-17 years. This difference between age and gender groups was ascribed to the variations in the hygiene levels of food preparers. By including the probability of ingesting a chicken meal at home, simulations revealed that all age groups, except the group above 60 years of age, had approximately the same probability of ingesting a chicken risk meal, the probability of females being slightly higher than that of males. The simulated results show that the probability of ingesting a chicken risk meal at home does not only depend on the hygiene practices of the persons preparing the food, but also on the consumption patterns of consumers, and the relationship between people preparing and ingesting food. This finding supports the need of including information on consumer behavior and preparation hygiene in the consumer phase of exposure assessments.     

Source Attribution of Food-Borne Zoonoses in New Zealand: A Modified Hald Model

A Bayesian approach was developed by Hald et al .^{( 1 )} to estimate the contribution of different food sources to the burden of human salmonellosis in Denmark. This article describes the development of several modifications that can be used to adapt the model to different countries and pathogens. Our modified Hald model has several advantages over the original approach, which include the introduction of uncertainty in the estimates of source prevalence and an improved strategy for identifiability. We have applied our modified model to the two major food-borne zoonoses in New Zealand, namely, campylobacteriosis and salmonellosis. Major challenges were the data quality for salmonellosis and the inclusion of environmental sources of campylobacteriosis. We conclude that by modifying the Hald model we have improved its identifiability, made it more applicable to countries with less intensive surveillance, and feasible for other pathogens, in particular with respect to the inclusion of nonfood sources. The wider application and better understanding of this approach is of particular importance due to the value of the model for decision making and risk management.     

Demonstrating the Benefits of Predictive Bayesian Dose–Response Relationships Using Six Exposure Studies of Cryptosporidium parvum

A conventional dose–response function can be refitted as additional data become available. A predictive dose–response function in contrast does not require a curve-fitting step, only additional data and presents the unconditional probabilities of illness, reflecting the level of information it contains. In contrast, the predictive Bayesian dose–response function becomes progressively less conservative as more information is included. This investigation evaluated the potential for using predictive Bayesian methods to develop a dose–response for human infection that improves on existing models, to show how predictive Bayesian statistical methods can utilize additional data, and expand the Bayesian methods for a broad audience including those concerned about an oversimplification of dose–response curve use in quantitative microbial risk assessment (QMRA). This study used a dose–response relationship incorporating six separate data sets for Cryptosporidium parvum. A Pareto II distribution with known priors was applied to one of the six data sets to calibrate the model, while the others were used for subsequent updating. While epidemiological principles indicate that local variations, host susceptibility, and organism strain virulence may vary, the six data sets all appear to be well characterized using the Bayesian approach. The adaptable model was applied to an existing data set for Campylobacter jejuni for model validation purposes, which yielded results that demonstrate the ability to analyze a dose–response function with limited data using and update those relationships with new data. An analysis of the goodness of fit compared to the beta-Poisson methods also demonstrated correlation between the predictive Bayesian model and the data.     

The BSE Risk of Processing Meat and Bone Meal in Nonruminant Feed: A Quantitative Assessment for the Netherlands

The total ban on use of meat and bone meal (MBM) in livestock feed has been very successful in reducing bovine spongiform encephalopathy (BSE) spread, but also implies a waste of high-quality proteins resulting in economic and ecological loss. Now that the BSE epidemic is fading out, a partial lifting of the MBM ban might be considered. The objective of this study was to assess the BSE risk for the Netherlands if MBM derived from animals fit for human consumption, i.e., category 3 MBM, would be used in nonruminant feed. A stochastic simulation model was constructed that calculates (1) the probability that infectivity of undetected BSE-infected cows ends up with calves and (2) the quantity of infectivity ( Q_inf ) consumed by calves in case of such an incident. Three pathways were considered via which infectivity can reach cattle: (1) cross-contamination in the feed mill, (2) cross-contamination on the primary farm, and (3) pasture contamination. Model calculations indicate that the overall probability that infectivity ends up with calves is 3.2%. In most such incidents the Q_inf is extremely small (median = 6.5 × 10⁻¹² ID₅₀; mean = 1.8 × 10⁻⁴ ID₅₀), corresponding to an average probability of 1.3 × 10⁻⁴ that an incident results in ≥1 new BSE infections. Cross-contamination in the feed mill is the most risky pathway. Combining model results with Dutch BSE prevalence estimates for the coming years, it can be concluded that the BSE risk of using category 3 MBM derived from Dutch cattle in nonruminant feed is very low.     

Dose Response for Infectivity of Several Strains of Campylobacter jejuni in Chickens

Although some major risk studies have been done for Campylobacter jejuni, its dose response is not well characterized. Only a single human study is available, providing dose-response information for only a single isolate. As substantial heterogeneity in infectivity has been acknowledged for other pathogens, it remains unknown how well this single study represents the dose-response relation for this pathogen. As future human challenge studies with Campylobacter are unlikely, we have to find other means of studying its infectivity. Several dose-response studies have been done using chickens as host organisms. These studies may be used to obtain quantitative information on the variation in infectivity among different isolates of this pathogen. A hierarchical Bayesian model is well suited to describe heterogeneity, and we demonstrate how the beta-Poisson model of microbial infection may be adapted to allow for within- and between-isolate variation. Isolates tested in chickens can be categorized into two distinct groups: lab-adapted and fresh isolates, and we show how the hierarchical dose-response model can be used to quantitatively describe their differences. Fresh isolates show higher colonization potential and less within-isolate variation than lab isolates. The results indicate that Campylobacter jejuni is highly infectious in chickens. Different isolates show great variation in infectivity, especially between lab and fresh isolates, indicating that human clinical (volunteer) studies on infectivity must be interpreted cautiously.     

Quantitative Risk Assessment of Norovirus Transmission in Food Establishments: Evaluating the Impact of Intervention Strategies and Food Employee Behavior on the Risk Associated with Norovirus in Foods

We developed a quantitative risk assessment model using a discrete event framework to quantify and study the risk associated with norovirus transmission to consumers through food contaminated by infected food employees in a retail food setting. This study focused on the impact of ill food workers experiencing symptoms of diarrhea and vomiting and potential control measures for the transmission of norovirus to foods. The model examined the behavior of food employees regarding exclusion from work while ill and after symptom resolution and preventive measures limiting food contamination during preparation. The mean numbers of infected customers estimated for 21 scenarios were compared to the estimate for a baseline scenario representing current practices. Results show that prevention strategies examined could not prevent norovirus transmission to food when a symptomatic employee was present in the food establishment. Compliance with exclusion from work of symptomatic food employees is thus critical, with an estimated range of 75–226% of the baseline mean for full to no compliance, respectively. Results also suggest that efficient handwashing, handwashing frequency associated with gloving compliance, and elimination of contact between hands, faucets, and door handles in restrooms reduced the mean number of infected customers to 58%, 62%, and 75% of the baseline, respectively. This study provides quantitative data to evaluate the relative efficacy of policy and practices at retail to reduce norovirus illnesses and provides new insights into the interactions and interplay of prevention strategies and compliance in reducing transmission of foodborne norovirus.     

Kitchen Hygiene in the Spotlight: How Cooking Shows Influence Viewers’ Hygiene Practices

Poor hygiene when handling food is a major cause of foodborne illness. To investigate whether hygiene practices visible in television cooking shows influence viewers’ kitchen hygiene, a study on the adoption of demonstrated hygiene behavior was conducted under controlled, experimental conditions. In a study ostensibly on cooking by following recipes participants (n = 65) were randomly assigned to one of three conditions, in which they watched a cooking video that differed only with regard to the hygiene behavior of the chef. In condition 1, the chef engaged in poor hygiene practices while preparing the dish, in condition 2 the chef's hygiene behavior was exemplary and in condition 3, the chef's hygiene behavior was not visible (control condition). After watching the video, participants were instructed to cook the recipe individually in the fully equipped laboratory kitchen. Cooking sessions were videotaped and experimenters blind to condition coded hygiene lapses committed by participants. The level of kitchen hygiene displayed in the cooking video significantly affected hygiene practices of participants cooking the recipe. Participants who had watched the cooking video with correct hygiene practices committed significantly fewer hygiene lapses than those who had watched the video with poor hygiene practices. From a risk communication perspective, TV cooking shows are well placed to convey knowledge of essential hygiene practices during food preparation to a broad audience. To facilitate behavioral change toward safer food‐handling practices among viewers, visibly performing correct hygiene practices in cooking shows is a promising strategy.     

Classic Dose‐Response and Time Postinoculation Models for Leptospira

Leptospirosis is a preeminent zoonotic disease concentrated in tropical areas, and prevalent in both industrialized and rural settings. Dose‐response models were generated from 22 data sets reported in 10 different studies. All of the selected studies used rodent subjects, primarily hamsters, with the predominant endpoint as mortality with the challenge strain administered intraperitoneally. Dose‐response models based on a single evaluation postinfection displayed median lethal dose (LD₅₀) estimates that ranged between 1 and 10⁷ leptospirae depending upon the strain's virulence and the period elapsed since the initial exposure inoculation. Twelve of the 22 data sets measured the number of affected subjects daily over an extended period, so dose‐response models with time‐dependent parameters were estimated. Pooling between data sets produced seven common dose‐response models and one time‐dependent model. These pooled common models had data sets with different test subject hosts, and between disparate leptospiral strains tested on identical hosts. Comparative modeling was done with parallel tests to test the effects of a single different variable of either strain or test host and quantify the difference by calculating a dose multiplication factor. Statistical pooling implies that the mechanistic processes of leptospirosis can be represented by the same dose‐response model for different experimental infection tests even though they may involve different host species, routes, and leptospiral strains, although the cause of this pathophysiological phenomenon has not yet been identified.     

Animal and Human Dose‐Response Models for Brucella Species

Human Brucellosis is one of the most common zoonotic diseases worldwide. Disease transmission often occurs through the handling of domestic livestock, as well as ingestion of unpasteurized milk and cheese, but can have enhanced infectivity if aerosolized. Because there is no human vaccine available, rising concerns about the threat of Brucellosis to human health and its inclusion in the Center for Disease Control's Category B Bioterrorism/Select Agent List make a better understanding of the dose‐response relationship of this microbe necessary. Through an extensive peer‐reviewed literature search, candidate dose‐response data were appraised so as to surpass certain standards for quality. The statistical programming language, “R,” was used to compute the maximum likelihood estimation to fit two models, the exponential and the approximate beta‐Poisson (widely used for quantitative risk assessment) to dose‐response data. Dose‐response models were generated for prevalent species of Brucella: Br. suis, Br. melitensis, and Br. abortus. Dose‐response models were created for aerosolized Br. suis exposure to guinea pigs from pooled studies. A parallel model for guinea pigs inoculated through both aerosol and subcutaneous routes with Br. melitensis showed that the median infectious dose corresponded to a 30 colony‐forming units (CFU) dose of Br. suis, much less than the N₅₀ dose of about 94 CFU for Br. melitensis organisms. When Br. melitensis was tested subcutaneously on mice, the N₅₀ dose was higher, 1,840 CFU. A dose‐response model was constructed from pooled data for mice, rhesus macaques, and humans inoculated through three routes (subcutaneously/aerosol/intradermally) with Br. melitensis.     

Quantitative microbiological risk assessment of nontyphoidal Salmonella in ground pork in households in Chengdu,China

Foodborne disease caused by nontyphoidal Salmonella (NTS) is one of the most important food safety issues worldwide. The objectives of this study were to carry out microbial monitoring on the prevalence of NTS in commercial ground pork, investigate consumption patterns, and conduct a quantitative microbiological risk assessment (QMRA) that considers cross-contamination to determine the risk caused by consuming ground pork and ready-to-eat food contaminated during food handling in the kitchen in Chengdu, China. The food pathway of ground pork was simplified and assumed to be several units according to the actual situation and our survey data, which were collected from our research or references and substituted into the QMRA model for simulation. The results showed that the prevalence of NTS in ground pork purchased in Chengdu was 69.64% (95% confidence interval [CI], 60.2–78.0), with a mean contamination level of −0.164 log CFU/g. After general cooking, NTS in ground pork could be eliminated (contamination level of zero). The estimated probability of causing salmonellosis per day was 9.43E-06 (95% CI: 8.82E-06–1.00E-05), while the estimated salmonellosis cases per million people per year were 3442 (95% CI: 3218–3666). According to the sensitivity analysis, the occurrence of cross-contamination was the most important factor affecting the probability of salmonellosis. To reduce the risk of salmonellosis caused by NTS through ground pork consumption, reasonable hygiene prevention and control measures should be adopted during food preparation to reduce cross-contamination. This study provides valuable information for household cooking and food safety management in China.     

An Ecological Model for Quantitative Risk Assessment for Schistosomiasis: The Case of a Patchy Environment in the Coastal Tropical Area of Northeastern Brazil

We developed a stochastic model for quantitative risk assessment for the Schistosoma mansoni (SM) parasite, which causes an endemic disease of public concern. The model provides answers in a useful format for public health decisions, uses data and expert opinion, and can be applied to any landscape where the snail Biomphalaria glabrata is the main intermediate host (South and Central America, the Caribbean, and Africa). It incorporates several realistic and case‐specific features: stage‐structured parasite populations, periodic praziquantel (PZQ) drug treatment for humans, density dependence, extreme events (prolonged rainfall), site‐specific sanitation quality, environmental stochasticity, monthly rainfall variation, uncertainty in parameters, and spatial dynamics. We parameterize the model through a real‐world application in the district of Porto de Galinhas (PG), one of the main touristic destinations in Brazil, where previous studies identified four parasite populations within the metapopulation. The results provide a good approximation of the dynamics of the system and are in agreement with our field observations, i.e., the lack of basic infrastructure (sanitation level and health programs) makes PG a suitable habitat for the persistence and growth of a parasite metapopulation. We quantify the risk of SM metapopulation explosion and quasi‐extinction and the time to metapopulation explosion and quasi‐extinction. We evaluate the sensitivity of the results under varying scenarios of future periodic PZQ treatment (based on the Brazilian Ministry of Health's plan) and sanitation quality. We conclude that the plan might be useful to slow SM metapopulation growth but not to control it. Additional investments in better sanitation are necessary.     

A Linear Model for Managing the Risk of Antimicrobial Resistance Originating in Food Animals

A linear population risk model used by the U.S. Food and Drug Administration (FDA) Center for Veterinary Medicine (CVM) estimates the risk of human cases of campylobacteriosis caused by fluoroquinolone-resistant Campylobacter. Among the cases of campylobacteriosis attributed to domestically produced chicken, the fluoroquinolone resistance is assumed to result from the use of fluoroquinolones in poultry in the United States. Properties of the linear population risk model are contrasted with those of a farm-to-fork model commonly used for microbial risk assessments. The utility of the linear population model for the purpose for which it was used by CVM is discussed.     

Food Safety in the Domestic Environment: The Effect of Consumer Risk Information on Human Disease Risks

The improvement of food safety in the domestic environment requires a transdisciplinary approach, involving interaction between both the social and natural sciences. This approach is applied in a study on risks associated with Campylobacter on broiler meat. First, some web-based information interventions were designed and tested on participant motivation and intentions to cook more safely. Based on these self-reported measures, the intervention supported by the emotion "disgust" was selected as the most promising information intervention. Its effect on microbial cross-contamination was tested by recruiting a set of participants who prepared a salad with chicken breast fillet carrying a known amount of tracer bacteria. The amount of tracer that could be recovered from the salad revealed the transfer and survival of Campylobacter and was used as a measure of hygiene. This was introduced into an existing risk model on Campylobacter in the Netherlands to assess the effect of the information intervention both at the level of exposure and the level of human disease risk. We showed that the information intervention supported by the emotion "disgust" alone had no measurable effect on the health risk. However, when a behavioral cue was embedded within the instruction for the salad preparation, the risk decreased sharply. It is shown that a transdisciplinary approach, involving research on risk perception, microbiology, and risk assessment, is successful in evaluating the efficacy of an information intervention in terms of human health risks. The approach offers a novel tool for science-based risk management in the area of food safety.     

A Risk Assessment Model for Campylobacter in Broiler Meat

A quantitative microbiological risk assessment model describes the transmission of Campylobacter through the broiler meat production chain and at home, from entering the processing plant until consumption of a chicken breast fillet meal. The exposure model is linked to a dose-response model to allow estimation of the incidence of human campylobacteriosis. The ultimate objective of the model is to serve as a tool to assess the effects of interventions to reduce campylobacteriosis in the Netherlands. The model describes some basic mechanistics of processing, including the nonlinear effects of cross-contamination between carcasses and their leaking feces. Model input is based on the output of an accompanying farm model and Dutch count data of Campylobacters on the birds' exterior and in the feces. When processing data are lacking, expert judgment is used for model parameter estimation. The model shows that to accurately assess of the effects of interventions, numbers of Campylobacter have to be explicitly incorporated in the model in addition to the prevalence of contamination. Also, as count data usually vary by several orders of magnitude, variability in numbers within and especially between flocks has to be accounted for. Flocks with high concentrations of Campylobacter in the feces that leak from the carcasses during industrial processing seem to have a dominant impact on the human incidence. The uncertainty in the final risk estimate is large, due to a large uncertainty at several stages of the chain. Among others, more quantitative count data at several stages of the production chain are needed to decrease this uncertainty. However, this uncertainty is smaller when relative risks of interventions are calculated with the model. Hence, the model can be effectively used by risk management in deciding on strategies to reduce human campylobacteriosis.     

Comparison of Risk Predicted by Multiple Norovirus Dose–Response Models and Implications for Quantitative Microbial Risk Assessment

The application of quantitative microbial risk assessments (QMRAs) to understand and mitigate risks associated with norovirus is increasingly common as there is a high frequency of outbreaks worldwide. A key component of QMRA is the dose–response analysis, which is the mathematical characterization of the association between dose and outcome. For Norovirus, multiple dose–response models are available that assume either a disaggregated or an aggregated intake dose. This work reviewed the dose–response models currently used in QMRA, and compared predicted risks from waterborne exposures (recreational and drinking) using all available dose–response models. The results found that the majority of published QMRAs of norovirus use the ₁F₁ hypergeometric dose–response model with α = 0.04, β = 0.055. This dose–response model predicted relatively high risk estimates compared to other dose–response models for doses in the range of 1–1,000 genomic equivalent copies. The difference in predicted risk among dose–response models was largest for small doses, which has implications for drinking water QMRAs where the concentration of norovirus is low. Based on the review, a set of best practices was proposed to encourage the careful consideration and reporting of important assumptions in the selection and use of dose–response models in QMRA of norovirus. Finally, in the absence of one best norovirus dose–response model, multiple models should be used to provide a range of predicted outcomes for probability of infection.     

Annual Burden of Occupationally‐Acquired Influenza Infections in Hospitals and Emergency Departments in the United States

Infections among health‐care personnel (HCP) occur as a result of providing care to patients with infectious diseases, but surveillance is limited to a few diseases. The objective of this study is to determine the annual number of influenza infections acquired by HCP as a result of occupational exposures to influenza patients in hospitals and emergency departments (EDs) in the United States. A risk analysis approach was taken. A compartmental model was used to estimate the influenza dose received in a single exposure, and a dose–response function applied to calculate the probability of infection. A three‐step algorithm tabulated the total number of influenza infections based on: the total number of occupational exposures (tabulated in previous work), the total number of HCP with occupational exposures, and the probability of infection in an occupational exposure. Estimated influenza infections were highly dependent upon the dose–response function. Given current compliance with infection control precautions, we estimated 151,300 and 34,150 influenza infections annually with two dose–response functions (annual incidence proportions of 9.3% and 2.1%, respectively). Greater reductions in infectious were achieved by full compliance with vaccination and IC precautions than with patient isolation. The burden of occupationally‐acquired influenza among HCP in hospitals and EDs in the United States is not trivial, and can be reduced through improved compliance with vaccination and preventive measures, including engineering and administrative controls.     

Comparison of the Cancer Risk of Methylene Chloride Predicted from Animal Bioassay Data with the Epidemiologic Evidence

Methylene chloride has been shown to be a lung and liver carcinogen in the mouse; yet, the current epidemiologic data show no adverse health effects associated with chronic exposure to this compound. Hearne et al. have compared the results of a large mortality study on occupational exposure to methylene chloride to the human risk predictions based on the rodent bioassay to point out the inconsistency between the animal toxicologic and human epidemiologic data. The maximum number of lung and liver cancers predicted due to methylene chloride exposure based on the rodent bioassay data was 24 compared to 14 deaths from these cancers actually observed in the Hearne et al. epidemiology study. We assess the minimum risk detectable by the human study in order to calculate the upperbound potency of methylene chloride and compare it to the potency derived from the bioassay data. Results from the epidemiology study imply an upperbound potency of 1.5 x 10(-2) per ppm, compared to 1.4 x 10(-2) per ppm calculated using the most conservative analysis of the animal data. We conclude that the negative epidemiology study of Hearne et al. is not sufficiently powerful to show that the risk is inconsistent with the human risk estimated by modeling the rodent bioassay data. Specifically, the doses to which the workers were exposed, the population studied, and the latency period were not adequate to determine that the risks are outside the bounds of the risk estimates predicted by low-dose modeling of the animal data.