The Economic Efficiency of Sampling Size: The Case of Beef Trim Revisited

A recent paper by Ferrier and Buzby provides a framework for selecting the sample size when testing a lot of beef trim for Escherichia coli O157:H7 that equates the averted costs of recalls and health damages from contaminated meats sold to consumers with the increased costs of testing while allowing for uncertainty about the underlying prevalence of contamination. Ferrier and Buzby conclude that the optimal sample size is larger than the current sample size. However, Ferrier and Buzby's optimization model has a number of errors, and their simulations failed to consider available evidence about the likelihood of the scenarios explored under the model. After correctly modeling microbial prevalence as dependent on portion size and selecting model inputs based on available evidence, the model suggests that the optimal sample size is zero under most plausible scenarios. It does not follow, however, that sampling beef trim for E. coli O157:H7, or food safety sampling more generally, should be abandoned. Sampling is not generally cost effective as a direct consumer safety control measure due to the extremely large sample sizes required to provide a high degree of confidence of detecting very low acceptable defect levels. Food safety verification sampling creates economic incentives for food producing firms to develop, implement, and maintain effective control measures that limit the probability and degree of noncompliance with regulatory limits or private contract specifications.     

Multi‐Exposure Pathway Model to Compare Escherichia coli O157 Risks and Interventions

The relative contributions of exposure pathways associated with cattle‐manure‐borne Escherichia coli O157:H7 on public health have yet to be fully characterized. A stochastic, quantitative microbial risk assessment (QMRA) model was developed to describe a hypothetical cattle farm in order to compare the relative importance of five routes of exposure, including aquatic recreation downstream of the farm, consumption of contaminated ground beef processed with limited interventions, consumption of leafy greens, direct animal contact, and the recreational use of a cattle pasture. To accommodate diverse environmental and hydrological pathways, existing QMRAs were integrated with novel and simplistic climate and field‐level submodels. The model indicated that direct animal contact presents the greatest risk of illness per exposure event during the high pathogen shedding period. However, when accounting for the frequency of exposure, using a high‐risk exposure‐receptor profile, consumption of ground beef was associated with the greatest risk of illness. Additionally, the model was used to evaluate the efficacy of hypothetical interventions affecting one or more exposure routes; concurrent evaluation of multiple routes allowed for the assessment of the combined effect of preharvest interventions across exposure pathways—which may have been previously underestimated—as well as the assessment of the effect of additional downstream interventions. This analysis represents a step towards a full evaluation of the risks associated with multiple exposure pathways; future incorporation of variability associated with environmental parameters and human behaviors would allow for a comprehensive assessment of the relative contribution of exposure pathways at the population level.     

The Economic Efficiency of Sampling Size: The Case of Beef Trim

The economically optimal sample size in a food safety test balances the marginal costs and marginal benefits of increasing the sample size. We provide a method for selecting the sample size when testing beef trim for Escherichia coli O157:H7 that equates the averted costs of recalls and health damages from contaminated meats sold to consumers with the increased costs of testing while allowing for uncertainty about the underlying prevalence rates of contamination. Using simulations, we show that, in most cases, the optimal sample size is larger than the current sample size of 60 and, in some cases, it exceeds 120. Moreover, lots with a lower prevalence rate have a higher expected damage because contamination is more difficult to detect. Our simulations indicate that these lots have a higher optimal sampling rate.     

A Mathematical Model for Pathogen Cross‐Contamination Dynamics during the Postharvest Processing of Leafy Greens

We developed a probabilistic mathematical model for the postharvest processing of leafy greens focusing on Escherichia coli O157:H7 contamination of fresh‐cut romaine lettuce as the case study. Our model can (i) support the investigation of cross‐contamination scenarios, and (ii) evaluate and compare different risk mitigation options. We used an agent‐based modeling framework to predict the pathogen prevalence and levels in bags of fresh‐cut lettuce and quantify spread of E. coli O157:H7 from contaminated lettuce to surface areas of processing equipment. Using an unbalanced factorial design, we were able to propagate combinations of random values assigned to model inputs through different processing steps and ranked statistically significant inputs with respect to their impacts on selected model outputs. Results indicated that whether contamination originated on incoming lettuce heads or on the surface areas of processing equipment, pathogen prevalence among bags of fresh‐cut lettuce and batches was most significantly impacted by the level of free chlorine in the flume tank and frequency of replacing the wash water inside the tank. Pathogen levels in bags of fresh‐cut lettuce were most significantly influenced by the initial levels of contamination on incoming lettuce heads or surface areas of processing equipment. The influence of surface contamination on pathogen prevalence or levels in fresh‐cut bags depended on the location of that surface relative to the flume tank. This study demonstrates that developing a flexible yet mathematically rigorous modeling tool, a “virtual laboratory,” can provide valuable insights into the effectiveness of individual and combined risk mitigation options.     

A Predictive Model for Survival of Escherichia coli O157:H7 and Generic E. coli in Soil Amended with Untreated Animal Manure

This study aimed at developing a predictive model that captures the influences of a variety of agricultural and environmental variables and is able to predict the concentrations of enteric bacteria in soil amended with untreated Biological Soil Amendments of Animal Origin (BSAAO) under dynamic conditions. We developed and validated a Random Forest model using data from a longitudinal field study conducted in mid-Atlantic United States investigating the survival of Escherichia coli O157:H7 and generic E. coli in soils amended with untreated dairy manure, horse manure, or poultry litter. Amendment type, days of rain since the previous sampling day, and soil moisture content were identified as the most influential agricultural and environmental variables impacting concentrations of viable E. coli O157:H7 and generic E. coli recovered from amended soils. Our model results also indicated that E. coli O157:H7 and generic E. coli declined at similar rates in amended soils under dynamic field conditions.The Random Forest model accurately predicted changes in viable E. coli concentrations over time under different agricultural and environmental conditions. Our model also accurately characterized the variability of E. coli concentration in amended soil over time by providing upper and lower prediction bound estimates. Cross-validation results indicated that our model can be potentially generalized to other geographic regions and incorporated into a risk assessment for evaluating the risks associated with application of untreated BSAAO. Our model can be validated for other regions and predictive performance also can be enhanced when data sets from additional geographic regions become available.     

Attribution of Human VTEC O157 Infection from Meat Products: A Quantitative Risk Assessment Approach

To address the risk posed to human health by the consumption of VTEC O157 within contaminated pork, lamb, and beef products within Great Britain, a quantitative risk assessment model has been developed. This model aims to simulate the prevalence and amount of VTEC O157 in different meat products at consumption within a single model framework by adapting previously developed models. The model is stochastic in nature, enabling both variability (natural variation between animals, carcasses, products) and uncertainty (lack of knowledge) about the input parameters to be modeled. Based on the model assumptions and data, it is concluded that the prevalence of VTEC O157 in meat products (joints and mince) at consumption is low (i.e., <0.04%). Beef products, particularly beef burgers, present the highest estimated risk with an estimated eight out of 100,000 servings on average resulting in human infection with VTEC O157.     

A QMRA for the Transmission of ESBL‐Producing Escherichia coli and Campylobacter from Poultry Farms to Humans Through Flies

The public health significance of transmission of ESBL‐producing Escherichia coli and Campylobacter from poultry farms to humans through flies was investigated using a worst‐case risk model. Human exposure was modeled by the fraction of contaminated flies, the number of specific bacteria per fly, the number of flies leaving the poultry farm, and the number of positive poultry houses in the Netherlands. Simplified risk calculations for transmission through consumption of chicken fillet were used for comparison, in terms of the number of human exposures, the total human exposure, and, for Campylobacter only, the number of human cases of illness. Comparing estimates of the worst‐case risk of transmission through flies with estimates of the real risk of chicken fillet consumption, the number of human exposures to ESBL‐producing E. coli was higher for chicken fillet as compared with flies, but the total level of exposure was higher for flies. For Campylobacter, risk values were nearly consistently higher for transmission through flies than for chicken fillet consumption. This indicates that the public health risk of transmission of both ESBL‐producing E. coli and Campylobacter to humans through flies might be of importance. It justifies further modeling of transmission through flies for which additional data (fly emigration, human exposure) are required. Similar analyses of other environmental transmission routes from poultry farms are suggested to precede further investigations into flies.     

Quantitative risk assessment-epidemic curve prediction model for leafy green outbreak investigation

The objective of this study was to leverage quantitative risk assessment to investigate possible root cause(s) of foodborne illness outbreaks related to Shiga toxin-producing Escherichia coli O157:H7 (STEC O157) infections in leafy greens in the United States. To this end, we developed the FDA leafy green quantitative risk assessment epidemic curve prediction model (FDA-LG QRA-EC) that simulated the lettuce supply chain. The model was used to predict the number of reported illnesses and the epidemic curve associated with lettuce contaminated with STEC O157 for a wide range of scenarios representing various contamination conditions and facility processing/sanitation practices. Model predictions were generated for fresh-cut and whole lettuce, quantifying the differing impacts of facility processing and home preparation on predicted illnesses. Our model revealed that the timespan (i.e., number of days with at least one reported illness) and the peak (i.e., day with the most predicted number of reported illnesses) of the epidemic curve of a STEC O157-lettuce outbreak were not strongly influenced by facility processing/sanitation practices and were indications of contamination pattern among incoming lettuce batches received by the facility or distribution center. Through comparisons with observed number of illnesses from recent STEC O157-lettuce outbreaks, the model identified contamination conditions on incoming lettuce heads that could result in an outbreak of similar size, which can be used to narrow down potential root cause hypotheses.     

A Multifactorial Risk Prioritization Framework for Foodborne Pathogens

We develop a prioritization framework for foodborne risks that considers public health impact as well as three other factors (market impact, consumer risk acceptance and perception, and social sensitivity). Canadian case studies are presented for six pathogen‐food combinations: Campylobacter spp. in chicken; Salmonella spp. in chicken and spinach; Escherichia coli O157 in spinach and beef; and Listeria monocytogenes in ready‐to‐eat meats. Public health impact is measured by disability‐adjusted life years and the cost of illness. Market impact is quantified by the economic importance of the domestic market. Likert‐type scales are used to capture consumer perception and acceptance of risk and social sensitivity to impacts on vulnerable consumer groups and industries. Risk ranking is facilitated through the development of a knowledge database presented in the format of info cards and the use of multicriteria decision analysis (MCDA) to aggregate the four factors. Three scenarios representing different stakeholders illustrate the use of MCDA to arrive at rankings of pathogen‐food combinations that reflect different criteria weights. The framework provides a flexible instrument to support policymakers in complex risk prioritization decision making when different stakeholder groups are involved and when multiple pathogen‐food combinations are compared.     

Impact of Microbial Ecology of Meat and Poultry Products on Predictions from Exposure Assessment Scenarios for Refrigerated Storage

A novel extension of traditional growth models for exposure assessment of food-borne microbial pathogens was developed to address the complex interactions of competing microbial populations in foods. Scenarios were designed for baseline refrigeration and mild abuse of servings of chicken broiler and ground beef Our approach employed high-quality data for microbiology of foods at production, refrigerated storage temperatures, and growth kinetics of microbial populations in culture media. Simple parallel models were developed for exponential growth of multiple pathogens and the abundant and ubiquitous nonpathogenic indigenous microbiota. Monte Carlo simulations were run for unconstrained growth and growth with the density-dependent constraint based on the "Jameson effect," inhibition of pathogen growth when the indigenous microbiota reached 10(9) counts per serving. The modes for unconstrained growth of the indigenous microbiota were 10(8), 10(10), and 10(11) counts per serving for chicken broilers, and 10(7), 10(9) and 10(11) counts per serving for ground beef at respective sites for backroom, meat case, and home refrigeration. Contamination rates and likelihoods of reaching temperatures supporting growth of the pathogens in the baseline refrigeration scenario were rare events. The unconstrained exponential growth models appeared to overestimate L. monocytogenes growth maxima for the baseline refrigeration scenario by 1500-7233% (10(6)-10(7) counts/serving) when the inhibitory effects of the indigenous microbiota are ignored. The extreme tails of the distributions for the constrained models appeared to overestimate growth maxima 110% (10(4)-10(5) counts/serving) for Salmonella spp. and 108% (6 x 10(3) counts/serving) for E. coli O157:H7 relative to the extremes of the unconstrained models. The approach of incorporating parallel models for pathogens and the indigenous microbiota into exposure assessment modeling motivates the design of validation studies to test the modeling assumptions, consistent with the analytical-deliberative process of risk analysis.     

Interventions Targeting Deep Tissue Lymph Nodes May Not Effectively Reduce the Risk of Salmonellosis from Ground Pork Consumption: A Quantitative Microbial Risk Assessment

The inclusion of deep tissue lymph nodes (DTLNs) or nonvisceral lymph nodes contaminated with Salmonella in wholesale fresh ground pork (WFGP) production may pose risks to public health. To assess the relative contribution of DTLNs to human salmonellosis occurrence associated with ground pork consumption and to investigate potential critical control points in the slaughter‐to‐table continuum for the control of human salmonellosis in the United States, a quantitative microbial risk assessment (QMRA) model was established. The model predicted an average of 45 cases of salmonellosis (95% CI = [19, 71]) per 100,000 Americans annually due to WFGP consumption. Sensitivity analysis of all stochastic input variables showed that cooking temperature was the most influential parameter for reducing salmonellosis cases associated with WFGP meals, followed by storage temperature and Salmonella concentration on contaminated carcass surface before fabrication. The input variables were grouped to represent three main factors along the slaughter‐to‐table chain influencing Salmonella doses ingested via WFGP meals: DTLN‐related factors, factors at processing other than DTLNs, and consumer‐related factors. The evaluation of the impact of each group of factors by second‐order Monte Carlo simulation showed that DTLN‐related factors had the lowest impact on the risk estimate among the three groups of factors. These findings indicate that interventions to reduce Salmonella contamination in DTLNs or to remove DTLNs from WFGP products may be less critical for reducing human infections attributable to ground pork than improving consumers’ cooking habits or interventions of carcass decontamination at processing.     

STOCHASTIC GROWTH IN THE UNITED STATES AND EURO AREA

This paper estimates, using data from the United States and the Euro Area, a two‐country stochastic growth model in which both neutral and investment‐specific technology shocks are nonstationary but cointegrated across economies. The results point to large and persistent swings in productivity, both favorable and adverse, originating in the United States but not transmitted to the Euro Area. More specifically, the results suggest that while the Euro Area missed out on the period of rapid investment‐specific technological change enjoyed in the United States during the 1990s, it also escaped the stagnation in neutral technological progress that plagued the United States in the 1970s.     

Vero-Cytotoxigenic Escherichia coli O157 in Pasteurized Milk Containers at the Point of Retail: A Qualitative Approach to Exposure Assessment

Dairies within the United Kingdom are classified into two groups, namely, off-farm and on-farm dairies (the latter often being small scale). We propose a model for the probability of milk sold as pasteurized reaching the point of retail contaminated with Vero-cytotoxigenic Escherichia coli (VTEC) O157 from each of these two pathways. We evaluate qualitatively the exposures inherent in each, and compare and contrast the two situations. The model framework is generic, in that it can in principle be used, with the relevant data modifications, to provide a qualitative assessment of the likely exposure from milk sold as pasteurized to any potentially milk-borne pathogenic organism. Furthermore, the methodological approaches presented are widely applicable in the microbial risk assessment field. The specific example presented will be of particular interest to the UK dairy and public health communities: we conclude that the exposure potential per liter consumed from milk processed in off-farm dairies is negligible, whereas the exposure potential per liter consumed from milk processed on-farm is low, but not sufficiently small to be regarded as negligible. We also identify areas of data sparsity, which need to be addressed for quantitative risk assessment to proceed, and highlight the critical points in the pasteurized milk production chain, which, in the event of a breakdown, have the potential to increase the risk to the consumer.     

Topics in Microbial Risk Assessment: Dynamic Flow Tree Process

Microbial risk assessment is emerging as a new discipline in risk assessment. A systematic approach to microbial risk assessment is presented that employs data analysis for developing parsimonious models and accounts formally for the variability and uncertainty of model inputs using analysis of variance and Monte Carlo simulation. The purpose of the paper is to raise and examine issues in conducting microbial risk assessments. The enteric pathogen Escherichia coli O157:H7 was selected as an example for this study due to its significance to public health. The framework for our work is consistent with the risk assessment components described by the National Research Council in 1983 (hazard identification; exposure assessment; dose-response assessment; and risk characterization). Exposure assessment focuses on hamburgers, cooked a range of temperatures from rare to well done, the latter typical for fast food restaurants. Features of the model include predictive microbiology components that account for random stochastic growth and death of organisms in hamburger. For dose-response modeling, Shigella data from human feeding studies were used as a surrogate for E. coli O157:H7. Risks were calculated using a threshold model and an alternative nonthreshold model. The 95% probability intervals for risk of illness for product cooked to a given internal temperature spanned five orders of magnitude for these models. The existence of even a small threshold has a dramatic impact on the estimated risk.     

AN INTERNATIONAL COMPARISON OF LIFETIME INEQUALITY: HOW CONTINENTAL EUROPE RESEMBLES NORTH AMERICA

We compare earnings inequality and mobility across the United States, Canada, France, Germany and the United Kingdom during the late 1990s. A flexible model of earnings dynamics that isolates positional mobility within a stable earnings distribution is estimated. Earnings trajectories are then simulated, and lifetime annuity value distributions are constructed. Earnings mobility and employment risk are found to be positively correlated with base‐year inequality. Taken together they produce more equalization in countries with high cross‐section inequality such that the countries in our sample have more similar lifetime inequality levels than cross‐section measures suggest.     

Risk Assessment of Salmonellosis from Consumption of Alfalfa Sprouts and Evaluation of the Public Health Impact of Sprout Seed Treatment and Spent Irrigation Water Testing

We developed a risk assessment of human salmonellosis associated with consumption of alfalfa sprouts in the United States to evaluate the public health impact of applying treatments to seeds (0–5‐log₁₀ reduction in Salmonella ) and testing spent irrigation water (SIW) during production. The risk model considered variability and uncertainty in Salmonella contamination in seeds, Salmonella growth and spread during sprout production, sprout consumption, and Salmonella dose response. Based on an estimated prevalence of 2.35% for 6.8 kg seed batches and without interventions, the model predicted 76,600 (95% confidence interval (CI) 15,400 – 248,000) cases/year. Risk reduction (by 5 ‐ to 7‐fold) predicted from a 1‐log₁₀ seed treatment alone was comparable to SIW testing alone, and each additional 1‐log₁₀ seed treatment was predicted to provide a greater risk reduction than SIW testing. A 3‐log₁₀ or a 5‐log₁₀ seed treatment reduced the predicted cases/year to 139 (95% CI 33 – 448) or 1.4 (95% CI <1 – 4.5), respectively. Combined with SIW testing, a 3‐log₁₀ or 5‐log₁₀ seed treatment reduced the cases/year to 45 (95% CI 10–146) or <1 (95% CI <1 – 1.5), respectively. If the SIW coverage was less complete (i.e., less representative), a smaller risk reduction was predicted, e.g., a combined 3‐log₁₀ seed treatment and SIW testing with 20% coverage resulted in an estimated 92 (95% CI 22 – 298) cases/year. Analysis of alternative scenarios using different assumptions for key model inputs showed that the predicted relative risk reductions are robust. This risk assessment provides a comprehensive approach for evaluating the public health impact of various interventions in a sprout production system.     

EVOLVING INTERNATIONAL INFLATION DYNAMICS: WORLD AND COUNTRY‐SPECIFIC FACTORS

The decline in the level and persistence of inflation over the 1980s is a common feature of the most industrialized economies in the world. The rise in inflation volatility of the late 1970s and the subsequent fall of the 1980s is country specific for the UK, Canada, and, to a lesser extent, the United States, Italy, and Japan. Since the late 1980s, inflation predictability has declined significantly across the industrialized world. We link the empirical results to recent theories of international inflation.     

Quantitative Assessment of Human MRSA Risks from Swine

The public health community, news media, and members of the general public have expressed significant concern that methicillin‐resistant Staphylococcus aureus (MRSA) transmitted from pigs to humans may harm human health. Studies of the prevalence and dynamics of swine‐associated (ST398) MRSA have sampled MRSA at discrete points in the presumed causative chain leading from swine to human patients, including sampling bacteria from live pigs, retail meats, farm workers, and hospital patients. Nonzero prevalence is generally interpreted as indicating a potential human health hazard from MRSA infections, but quantitative assessments of resulting risks are not usually provided. This article integrates available data from several sources to construct a conservative (plausible upper bound) probability estimate for the actual human health harm (MRSA infections and fatalities) arising from ST398‐MRSA from pigs. The model provides plausible upper bounds of approximately one excess human infection per year among all U.S. pig farm workers, and one human infection per 31 years among the remaining total population of the United States. These results assume the possibility of transmission events not yet observed, so additional data collection may reduce these estimates further.     

WHICH SECTORS MAKE POOR COUNTRIES SO UNPRODUCTIVE?

Which sectors are most responsible for the low total factor productivities of developing countries? To answer this question we develop a new framework for sectoral development accounting. Applying this framework to the Penn World Table, we find that in equipment, construction, and food the sectoral TFP differences between developing countries and the United States are much larger than in the aggregate. However, in manufactured consumption the sectoral TFP differences are about equal to the aggregate TFP differences, and in services they are much smaller. We show that our level of disaggregation allows us to reconcile the results of existing studies of sectoral productivity differences, which have focused on noncomparable two‐sector decompositions of the aggregate data. We also show that our results help shed light on existing theories of aggregate TFP differences.