Economic impact of an Escherichia coli O157:H7 outbreak in Japan

Diversity and Local Coadaptation of Escherichia coli and Coliphages From Small Ruminants

Bacteriophages are highly specific predators that drive bacterial diversity through coevolution while striking tradeoffs among preserving host populations for long-term exploitation and increasing their virulence, structural stability, or host range. Escherichia coli and other coliform bacteria present in the microbiota of milk and during early ripening of raw milk cheeses have been linked to the production of gas, manifested by the appearance of eyes, and the development of off-flavors; thus, they might cause early blowing and cheese spoilage. Here, we report the characterization of coliphages isolated from manure from small ruminant farms and E. coli strains isolated from goat and sheep raw milk cheese. Additionally, the virulence and host range of locally isolated and laboratory collection phages were determined by comparing the susceptibility of E. coli strains from different sources. In agreement with the high genetic diversity found within the species E. coli, clustering analysis of whole-cell protein revealed a total of 13 distinct profiles but none of the raw milk cheese isolates showed inhibition of growth by reference or water-isolated coliphages. Conversely, 10 newly isolated phages had a broad host range (i.e., able to lyse ≥50% of bacterial hosts tested), thus exhibiting utility for biocontrol and only one cheese-isolated E. coli strain was resistant to all the phages. Whereas there was a high positive correlation between bacterial susceptibility range and lysis intensity, the phages virulence decreased as range increased until reaching a plateau. These results suggest local gene-for-gene coevolution between hosts and phages with selective tradeoffs for both resistance and competitive ability of the bacteria and host-range extension and virulence of the phage populations. Hence, different phage cocktail formulations might be required when devising long-term and short-term biocontrol strategies.

Microbial Quality of Ready-to-Eat Foods Sold in School Cafeterias in Chongqing, China

ABSTRACT

The microbiological quality of ready-to-eat (RTE) foods from school cafeterias in Chongqing, People's Republic of China, was evaluated and compared with a guideline published by a provincial health commission. These RTE foods were divided into five types based on their preparation processes and potential risks: 1, general cooked and hot-held foods; 2, cooked meats; 3, heated aquatic products; 4, fresh fruits or vegetables; and 5, cooked foods with postcooking handling (e.g., cutting, cooling, or addition of ingredients or condiments). Food types 1 through 3 (subjected to thermal processes and hot-held) were microbiologically safer than types 4 and 5 (prepared by nonthermal process or with postcooking processes). None of the samples of types 1 through 3 were unsatisfactory based on their aerobic plate counts (APC) and total coliforms (TC), whereas 43.1% of type 4 and 8.3 and 71.7% of type 5 samples were unsatisfactory due to high counts of TC and high APC and TC, respectively. Two, 12, and 50 samples of types 2, 4, and 5, respectively, were unacceptable due to high levels of Staphylococcus aureus. Bacillus cereus and Vibrio parahaemolyticus were detected, but levels were below the unacceptable limits. None of the samples were positive for Salmonella, Listeria monocytogenes, or Escherichia coli O157. The bacterial profile can be used by policy makers and epidemiologists for microbiological risk assessments, which may be conducive to developing interventions to control hazards, improve food hygiene, and develop safety management systems for school cafeterias in China.

HIGHLIGHTS

Monetizing the Impact of Food Safety Recalls on the Low-Moisture Food Industry

ABSTRACT

New Food Safety and Modernization Act rules require that food producers implement and validate processes that sufficiently reduce the risk of known hazards, such as those posed by microbial pathogens. Investments in food safety technology choices are ultimately business decisions, and current decision-making methods make it difficult to quantify financial value associated with food safety risk reduction. Predicted financial loss is a tangible way to quantify how a recall might affect the manufacturer. The hypothesis of this study was that class I recalls of low-moisture foods due to the presence of microbial pathogens have a significant negative economic impact on the affected manufacturers, which can be quantified in terms of loss in market capitalization. Financial impacts of the recalls were analyzed over a 10-year period by computing the cumulative abnormal return (CAR) in stock values over a recall event period for 22 low-moisture foods made by publicly held companies. Abnormal returns were aggregated over an event window (0 to 20 days) to compute the CAR, which was multiplied by prerecall market capitalization to compute monetary losses due to the recall event. The CARs for a 20-day postrecall period were -26.5 to 8.4%, with a mean of -5.1%. These CARs translated to a median loss in corporate value due to a recall of $243 million for the recall events analyzed in this study. If implementation of a food safety technology could reduce risk of a recall by fivefold, the mean annual economic benefit would be >$2 million in reduced risk for companies such as those included in the study. Such analyses can positively impact business decisions to invest in food safety technologies.

HIGHLIGHTS

The economic burden of a Salmonella Thompson outbreak caused by smoked salmon in the Netherlands, 2012-2013

Background

In 2012, the Netherlands experienced the most extensive food-related outbreak of Salmonella ever recorded. It was caused by smoked salmon contaminated with Salmonella Thompson during processing. In total, 1149 cases of salmonellosis were laboratory confirmed and reported to RIVM. Twenty percent of cases was hospitalised and four cases were reported to be fatal. The purpose of this study was to estimate total costs of the Salmonella Thompson outbreak.

Methods

Data from a case-control study were used to estimate the cost-of-illness of reported cases (i.e. healthcare costs, patient costs and production losses). Outbreak control costs were estimated based on interviews with staff from health authorities. Using the Dutch foodborne disease burden and cost-of-illness model, we estimated the number of underestimated cases and the associated cost-of-illness.

Results

The estimated number of cases, including reported and underestimated cases was 21 123. Adjusted for underestimation, the total cost-of-illness would be €6.8 million (95% CI €2.5-€16.7 million) with productivity losses being the main cost driver. Adding outbreak control costs, the total outbreak costs are estimated at €7.5 million.

Conclusion

In the Netherlands, measures are taken to reduce salmonella concentrations in food, but detection of contamination during food processing remains difficult. As shown, Salmonella outbreaks have the potential for a relatively high disease and economic burden for society. Early warning and close cooperation between the industry, health authorities and laboratories is essential for rapid detection, control of outbreaks, and to reduce disease and economic burden.

Proteomic comparison of three clinical diarrhoeagenic drug-resistant Escherichia coli isolates grown on CHROMagar™STEC media

Shiga-toxin-producing Escherichia coli (STEC) and enteropathogenic Escherichia coli (EPEC) are key diarrhoea-causing foodborne pathogens. We used proteomics to characterize the virulence and antimicrobial resistance protein profiles of three clinical pathogenic E. coli isolates (two EPEC [one resistant to ciprofloxacin] and one STEC) cultured on CHROMagar™STEC solid media after minimal laboratory passage. We identified 4767 unique peptides from 1630 protein group across all three clinical E. coli strains. Label-free proteomic analysis allowed the identification of virulence and drug resistance proteins that were unique to each of the clinical isolates compared in this study. The B subunit of Shiga toxin, ToxB, was uniquely detected in the STEC strain while several other virulence factors including SheA, OmpF, OmpC and OmpX were significantly more abundant in the STEC strain. The ciprofloxacin resistant EPEC isolate possessed reduced levels of key virulence proteins compared to the ciprofloxacin susceptible EPEC and STEC strains. Parallel reaction monitoring assays validated the presence of biologically relevant proteins across biologically-replicated cultures. Propagation of clinical isolates on a relevant solid medium followed by mass spectrometry analysis represents a convenient means to quantify virulence factors and drug resistance determinants that might otherwise be lost through extensive in vitro passage in enteropathogenic bacteria.

SIGNIFICANCE

Through the use of quantitative proteomics, we have characterized the virulence and antimicrobial resistance attributes of three clinically isolated, pathogenic E. coli strains cultured on solid media. Our results provide new, quantitative data on the expressed proteomes of these tellurite-resistant, diarrhoeagenic E. coli strains and reveal a subset of antimicrobial resistance and virulence proteins that are differentially abundant between these clinical strains. Our quantitative proteomics-based approach should thus have applicability in microbiological diagnostic labs for the identification of pathogenic/drug resistant E. coli in the future.

FoodChain-Lab: A Trace-Back and Trace-Forward Tool Developed and Applied during Food-Borne Disease Outbreak Investigations in Germany and Europe

FoodChain-Lab is modular open-source software for trace-back and trace-forward analysis in food-borne disease outbreak investigations. Development of FoodChain-Lab has been driven by a need for appropriate software in several food-related outbreaks in Germany since 2011. The software allows integrated data management, data linkage, enrichment and visualization as well as interactive supply chain analyses. Identification of possible outbreak sources or vehicles is facilitated by calculation of tracing scores for food-handling stations (companies or persons) and food products under investigation. The software also supports consideration of station-specific cross-contamination, analysis of geographical relationships, and topological clustering of the tracing network structure. FoodChain-Lab has been applied successfully in previous outbreak investigations, for example during the 2011 EHEC outbreak and the 2013/14 European hepatitis A outbreak. The software is most useful in complex, multi-area outbreak investigations where epidemiological evidence may be insufficient to discriminate between multiple implicated food products. The automated analysis and visualization components would be of greater value if trading information on food ingredients and compound products was more easily available.

A likelihood-based approach to identifying contaminated food products using sales data: performance and challenges

Foodborne disease outbreaks of recent years demonstrate that due to increasingly interconnected supply chains these type of crisis situations have the potential to affect thousands of people, leading to significant healthcare costs, loss of revenue for food companies, and—in the worst cases—death. When a disease outbreak is detected, identifying the contaminated food quickly is vital to minimize suffering and limit economic losses. Here we present a likelihood-based approach that has the potential to accelerate the time needed to identify possibly contaminated food products, which is based on exploitation of food products sales data and the distribution of foodborne illness case reports. Using a real world food sales data set and artificially generated outbreak scenarios, we show that this method performs very well for contamination scenarios originating from a single “guilty” food product. As it is neither always possible nor necessary to identify the single offending product, the method has been extended such that it can be used as a binary classifier. With this extension it is possible to generate a set of potentially “guilty” products that contains the real outbreak source with very high accuracy. Furthermore we explore the patterns of food distributions that lead to “hard-to-identify” foods, the possibility of identifying these food groups a priori, and the extent to which the likelihood-based method can be used to quantify uncertainty. We find that high spatial correlation of sales data between products may be a useful indicator for “hard-to-identify” products.

Response to foodborne disease outbreaks is complicated by globalization of our food supply chains. Rapid identification of contaminated products is essential to limit the damage caused by foodborne disease. Worldwide, foodborne disease outbreaks are responsible for $9B a year in medical costs and over $75B in economic losses. Yet relevant data required to accelerate the identification of suspicious food already exists as part of the inventory control systems used by retailers and distributors today. Combining this retail data with public health case reports has the potential to hasten outbreak investigations and provide public health investigators with better information on suspected products to test. This paper demonstrates the feasibility of the principle and efficiency of this approach. Based on these findings it can be concluded that in foodborne disease outbreaks retail data could be used to speed and target public health investigations and consequently reduce numbers of sick/dead people as well as reduce economic losses to the industry.

The economics of enteric infections: human foodborne disease costs

The World Health Organization estimates that in 2005, 1.5 million people died, worldwide, from diarrheal diseases. A separate study estimated that 70% of diarrheal diseases are foodborne. The widely cited US estimate is that there are 76 million foodborne illnesses annually, resulting in 325,000 hospitalizations and 5200 deaths. However, there are epidemiologic and methodologic challenges to accurately estimate the economic burden of foodborne disease on society, either in terms of monetary costs or non-monetary units of measurement. Studies on the economic burden of foodborne disease vary considerably: some analyze the effects of a single pathogen or a single outbreak, whereas others attempt to estimate all foodborne disease in a country. Differences in surveillance systems, methodology, and other factors preclude meaningful comparisons across existing studies. However, if it were possible to completely estimate the societal costs for all acute foodborne diseases and their chronic sequelae worldwide, on the basis of currently available data, worldwide costs from these illnesses would be substantial. Moreover, foodborne infections are largely manifested as intestinal illnesses and are largely preventable. Total costs of foodborne disease would be much smaller in the United States and the world if economic incentives for industry to produce safer food were improved. However, costs of implementing new food safety prevention and control rules must be weighed against the estimated benefits of reducing foodborne disease to determine net benefits so that governments have information to efficiently allocate funds among competing programs.

Microbiological quality of ready-to-eat food served in schools in Wales, United Kingdom

A survey of the general microbiological quality of ready-to-eat food served in schools was undertaken across Wales, United Kingdom. Of the 2,351 samples taken, four were identified as containing unsatisfactory counts of Escherichia coli, four contained unsatisfactory counts of Staphylococcus aureus, and one contained an unacceptable count of Bacillus cereus when compared with guidelines for the microbiological quality of ready-to-eat food published by the United Kingdom Public Health Laboratory Service in 2000. No samples contained detectable levels of Salmonella, Listeria species, or Clostridium perfringens. When compared with data on the general microbiological quality of food available in Wales, the food sampled from schools was of relatively better microbiological quality.