Fw: [BITES-L] bites Oct. 15/10
Sent via BlackBerry from T-Mobile
From: Doug Powell <dpowell@KSU.EDU>
Sender: Bites <BITES-L@LISTSERV.KSU.EDU>
Date: Fri, 15 Oct 2010 10:20:33 -0500
To: BITES-L@LISTSERV.KSU.EDU<BITES-L@LISTSERV.KSU.EDU>
ReplyTo: Doug Powell <dpowell@KSU.EDU>
Subject: [BITES-L] bites Oct. 15/10
bites Oct. 15/10
Scores on Doors too clear for UK restaurant grading schemes
Lessons learned from E. coli outbreak in UK nursery
DELAWARE: Health official is model of public service
MANITOBA: Infections tied to Russian juice at Folklorama
Observational study of food safety practices in retail deli departments
US bill demands Salmonella vaccination of New York layer chickens
US: Jolley: Five minutes with Jeff Benedict, E. coli & Jack in the Box
Eat safer: Novel approach detects unknown food pathogens
Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007
Killer cattle virus wiped out
Bioniche scientists present at Modern Vaccine & Adjuvant Formulation Conference in FRANCE
TEXAS: Health inspectors find unsafe food surfaces at Seabrook Valero
AUSTRALIA: Food recall
how to subscribe
Scores on Doors too clear for UK restaurant grading schemes
15.oct.10
barfblog
Doug Powell
http://www.barfblog.com/blog/144589/10/10/15/scores-doors-too-clear-uk-restaurant-grading-schemes
Only a Lord could get away with a report titled, Common Sense Common Safety.
It ain't common sense if it hasn't been thought of.
The report, published today in the U.K. by Lord Young, the Prime Minister's adviser on health and safety law and practice, puts forward a series of policies for improving the perception of health and safety, to ensure it is taken seriously by employers and the general public, while ensuring the burden on small business is as insignificant as possible.
Wouldn't it be better to improve health and safety, and then the perception would be improved – if there was actual data to back up the claims of improved health and safety?
The report is written in a snooty tone that apparently only the British can achieve, and was deliberated in the context of the compensation culture – those vulgar lawyers looking for recompense for slighted victims.
Prime Minister David Cameron said,
"A damaging compensation culture has arisen, as if people can absolve themselves from any personal responsibility for their own actions, with the spectre of lawyers only too willing to pounce with a claim for damages on the slightest pretext.
"We simply cannot go on like this. That's why I asked Lord Young to do this review and put some common sense back into health and safety. And that's exactly what he has done."
The U.K. Food Standards Agency was quick to say the Lord backed their restaurant inspection disclosure scheme.
Under the voluntary Food Hygiene Rating Scheme, each business is given a hygiene rating (from 0-5) when it is inspected by a food safety officer from the business's local authority. The hygiene rating shows how closely the business is meeting the requirements of food hygiene law.
I was never sure about the 0-5 rating – is 5 good or bad – whereas a letter grading has clearer meaning. The actual report contains some clues:
The good Lord says that local authority participation in the Food Standards Agency's Food Hygiene Rating Scheme be made mandatory, and that usage of the scheme by consumers by harnessing the power and influence of local and national media.
He also says the voluntary display of ratings should be reviewed after 12 months and, if necessary, make display compulsory – particularly for those businesses that fail to achieve a 'generally satisfactory' rating.
"I welcome the FSA's decision to drop the unfortunate title 'scores on the doors', which has been used in the past for this initiative, and its decision to drop the use of stars, which have a connotation of cost and service. I am pleased that they have decided instead to use a simple numerical scale with appropriate descriptors. These decisions were based on the results of independent research with consumers and this is what they found to be clearest and easiest to use."
Scores on doors may be too direct for the Lord; I hope the Aussies keep using it. And I look forward to the 0-5 studies being published in a peer-reviewed journal so mere mortals can review the research.
The good Lord also cites the Los Angeles example of restaurant inspection disclosure – they use letter grades – and inflates an already dubious estimate by stating there was a 20 per cent drop in the number of people being admitted to hospital for food related illnesses after the introduction of the letter grades.
Restaurant inspection is a snapshot in time and disclosure is no panacea. It can boost the overall culture of food safety, hold operators accountable, and is a way of marketing food safety so that consumers can choose.
http://www.number10.gov.uk/news/latest-news/2010/10/lord-young-report-55605
http://www.food.gov.uk/news/newsarchive/2010/oct/lordyoungreport
Lessons learned from E. coli outbreak in UK nursery
15.ot.10
barfblog
Doug Powell
http://www.barfblog.com/blog/144590/10/10/15/lessons-learned-e-coli-outbreak-uk-nursery
In Feb. 2010, the Feltham Hill Nursery and Infant School was closed for three weeks when E. coli O157 was contracted by pupils, affecting 18 people in all.
A report to the Hounslow Council contained 28 recommendations to improve future responses to emergency situations, including:
• the situation should have been declared 'an emergency' sooner than it was;
• there were delays in stopping the spread of the outbreak because the school had no emergency plan;
• information sharing between the school and the health authorities was poor;
• confusion over information given to parents resulted in many being worried that the outbreak was not being controlled.
Two children were treated in hospital for the bug, one of which was for a prolonged period of time. The report reveals that the source of the outbreak was never discovered.
The complete report is available at:
http://democraticservices.hounslow.gov.uk/mgConvert2PDF.aspx?ID=53762
http://www.hounslowchronicle.co.uk/west-london-news/local-hounslow-news/2010/10/15/e-coli-report-reveals-lessons-learned-109642-27478308/
DELAWARE: Health official is model of public service
15.oct.10
The Star Press
http://www.thestarpress.com/article/20101015/OPINION01/10150338
The person who follows Robert Jones as administrator of the Delaware County Health Department will inherit a health department that is well run and efficient, something that can't be said of some other government offices.
Yet, those same successes have set high standards for performance and customer service for Jones' successor. Jones leaves behind a legacy that will be difficult to live up to.
Jones announced his retirement last night at a county health board meeting.
His tenure ends after more than two decades of service, marked by taking the health department from the laughing stock of the state to a professionally run, innovative and progressive professional agency that is now the envy of the state.
Jones is a model public servant who prefers education and collaboration, but he's not afraid to take a strong stand when necessary.
It takes courage to close down popular restaurants temporarily because of unsanitary conditions that could lead to outbreaks of foodborne illness.
MANITOBA: Infections tied to Russian juice at Folklorama
15.oct.10
Winnipeg Free Press
Jen Skerritt
http://www.winnipegfreepress.com/local/infections-tied-to-russian-juice-at-folklorama-105014189.html
Winnipeg health officials believe it was a Russian fruit drink that sent five people to hospital with E. Coli contamination at Folklorama last summer, but Russian pavilion officials aren't convinced.
Winnipeg Regional Health Authority officials investigated what led to an outbreak of verotoxigenic E. coli in the first two weeks of August after 40 people fell ill with symptoms. The five people who were hospitalized included a two-year-old boy who suffered acute renal failure and was put on dialysis in pediatric intensive care.
The investigation found 85 per cent of people who fell ill from toxic E. coli attended the Russian pavilion at the city's annual cultural festival, and items served as part of the "Russian combination platter," including borscht, meatballs, rice and Russian juice, were eyed as potential sources of contamination.
Medical officer Dr. Pierre Plourde said a study of 33 people who fell sick and 28 others who didn't found that people who consumed the Russian juice were six times more likely to have fallen ill. He said statistically, that makes the juice the most likely food item that spread the infection, and that officials suspect the juice came into contact with contaminated ground beef.
Plourde said it is a "mystery" how the juice came into contact with raw meat.
Russian Cultural Association officials weren't buying the WRHA's statistical conclusion.
"We had 70 volunteers, including 12 kids age five to 12, who danced two or three times a day, and nobody got sick," said Sofia Barklon, co-ordinator of the Russian pavilion.
The suspected drink is called kompot, made by boiling fresh apples, blueberries and blackberries and refrigerating the mixture until cooled.
Kompot was in jars in the volunteer room. "They drink kompot like water. It was our free drink for volunteers," Barklon said.
She said public health inspectors came to test the drink and found no problems.
The outbreak report confirmed health inspectors found deficiencies in the pavilion's kitchen on Aug. 1 -- the first day the Folklorama venue opened.
Inspectors found improperly stored raw hamburger meat in a refrigerator near ready-to-eat foods and drinks, and found one refrigerator was storing food at 12 C, an unsafe temperature to keep potentially hazardous foods.
Plourde said the "minor" breaches were corrected immediately, and the bulk of exposure to toxic E. coli did not occur until Aug. 3-5.
Plourde said boiling should have killed any contaminants in the fruit drink, leading officials to hypothesize it came into contact with raw meat.
Observational study of food safety practices in retail deli departments
15.oct.10
FoodRisk.org
M.B. Lubran, R. Pouillot, S. Bohm, E.M. Calvey, J. Meng, and S. Dennis
http://foodrisk.org/pubs/naf/
Notational analysis is an observational method in which a food employee's actions can be recorded quickly and in the sequence that they occur. The notational analysis technique was initially employed to record the behavior of food employees by Clayton and Griffith (2004), who adapted the technique from the field of sports science. Lubran et al. (2010) used this tool to record the actions of food employees in deli departments at six chain and three independent retail establishments in Maryland and Virginia, as they prepared deli products for sale. The frequency of contact with objects and deli products before sale, hand washing and glove changing during preparation, and equipment, utensil, and surface cleaning and sanitizing was determined. Compliance with the U.S. Food and Drug Administration's 2005 model Food Code recommendations, which must be adopted by the individual state and local jurisdictions that are responsible for directly regulating retail establishments, was also assessed.
The Notational Analysis Form and the code key used by Lubran et al (2010) are available for download.
How to Use the Tool
Each action a food employee performs can be recorded on the Notational Analysis Form. The form is designed to record the behavior of one food employee at a time. Before using the tool, the researcher needs to develop a list of codes or short-hand notations for objects, equipment, actions, and other things they expect to encounter within the observation environment (see code key used by Lubran et al., 2010). An example of an action observed by Lubran et al. (2010) which was recorded as a single action of the form using the code key is "PUP SAL" or "Pickup salami". Once a code key has been developed, it is recommended that these codes and the form be pilot-tested to ensure they are exhaustive and that the observer(s) is properly trained on how to use them.
In addition to recording the actions the food employee performs, the observer can also use the form to record whether food safety actions (such as hand-washing) were recommended to be performed, according to the Food and Drug Administration's (FDA) Food Code, as a result of the food employee's previous sequence of actions. For example, an employee may be observed touching his or her hair and then picking up a ready-to-eat sandwich. In this case, the Food Code would recommend that the food employee should have washed their hands in between these actions because they touched bare human body parts other than clean hands and clean, exposed portions of arms before engaging in food preparation (see §2-301.14). Another use of the form is to record whether the food safety actions the food employee performs are performed adequately or are attempted but not fully completed. For a description of these different classifications of actions based on the Food Code recommendations used in previous studies, please see Lubran et al. (2010) or Green et al. (2006). Finally, space is also provided in the form for notes and to record the time at pre-determined intervals (for example, every 10 actions).
Some suggestions for improving data collection which were used in this and other studies include that:
* No data should be collected during the first 10 to 15 minutes of observation (Green et al., 2006; Clayton & Griffith, 2004 waited 30 minutes).
* Protective clothing similar to those worn by the employees of each business should be warn in an attempt to blend in with the surroundings (Clayton & Griffith, 2004).
* A diagram of the work space should be recorded to aid in review of the data. The work space should encompass the entire area used by deli counter food employees.
References:
* Lubran, M.B., Pouillot, R., Bohm, S., Calvey, E.M., Meng, J. and S. Dennis. 2010. Observational Study of Food Safety Practices in Retail Deli Departments. J. Food Prot. 73:1849-1857.
* Clayton, D. A., and C. J. Griffith. 2004. Observation of food safety practices in catering using notational analysis. Br. Food J. 106:211–217.
* Green, L. R., C. A. Selman, V. Radke, D. Ripley, J. C. Mack, D. W. Reimann, T. Stigger, M. Motsinger, and L. Bushnell. 2006. Food worker hand washing practices: an observation study. J. Food Prot. 69:2417–2423.
US bill demands Salmonella vaccination of New York layer chickens
15.oct.10
VetsWeb
http://www.vetsweb.com/news/us-bill-demands-salmonella-vaccination-of-new-york-layer-chickens-1529.html
Two New York lawmakers have introduced a bill that would require any eggs sold in New York State to come from chickens that have been vaccinated against salmonella.
The introduction of this bill is in response to the nation's largest recall of eggs. The requirement would include eggs produced by New York farmers, and those that are imported from neighboring states.
New York egg producers say the bill focuses only on a small fraction of what should be a comprehensive approach to sanitation in egg houses. Egg farmers say that smart management of their operations and strict sanitary controls go a long way to preventing salmonella outbreaks like the one that struck an Iowa egg producer in August. Many of those controls are already governed by a state-run program that most large-scale producers follow. Salmonella vaccination alone will not protect consumers, but must be included as part of any on-the-farm food safety program, Brian Kavanagh said. Kavanagh is a New York Assemblyman and represents Manhattan. "We've become persuaded that although vaccination is not a silver bullet, it should be part of a comprehensive program," he said. "It is considered to be part of the best practice by some producers."
But some decry the legislation, saying the bill has no chance of passing. "It is not going anywhere," said Peter Gregg, spokesman for the New York Farm Bureau. New York has not had an outbreak of salmonella linked to eggs produced in the state since the 1980s, Gregg said. A voluntary egg quality assurance program, managed by the New York State Department of Agriculture and Markets, governs nearly 90 percent of the eggs produced in New York, he said. This voluntary farm management tool has been in place since the mid-1990s. Salmonella vaccination is not part of the program, but New York producers are already using chickens vaccinated for salmonella in their operations.
US: Jolley: Five minutes with Jeff Benedict, E. coli & Jack in the Box
15.oct.10
Cattle Network
http://www.cattlenetwork.com/Jolley--Five-Minutes-With-Jeff-Benedict--E--coli---Jack-In-The-Box/2010-10-15/article_cattlefeatures.aspx?oid=1273062&fid=CN-FEATURES
You know the feeling – you read something and those little hairs on the back of your stand at attention. "Oh, damn,' you say, 'here we go, again.'
Here is what I read last week: "For the past year and a half I've been writing a book about the biggest E. coli outbreak in U.S. history. It started in Seattle in 1993 and ended up spreading through most Western states. Jack in the Box restaurants was implicated as the source. Writing this story has changed my life, particularly when it comes to the way I eat. And I'm not just talking about beef."
It was on a blog written by Jeff Benedict, author of eight books on a variety of subjects and my immediate reaction was "Another cheap shot tell-all written by a Michael Pollan wannabe and based on five minutes of flimsy research."
Yeah, that's what I thought.
I mean the Seattle Jack in the Box incident is the seminal event in modern food safety. It was a wake up call, five alarm fire and a legal bombshell all tied up in one cold slap in the face for the food industry. It was a story that just begs for sensationalism long after the fact. A lot of people got sick; four children died and the true life-and-death penalties of food borne illnesses became a gaudy, multi-colored tattoo on the face of public consciousness.
But let me give Benedict a break. After digging into his background, I found out that he researches his subject matter. He really interviews people on both sides of an issue. Maybe what he'll write might actually fly under the harder-and-harder to find banner of 'fair and balanced.'
He has quite a list of subjects under his belt. His first book – Public Heroes, Private Felons: Athletes and Crimes Against Women – was written during his first year of law school in 1997. He was on a book-a-year schedule, publishing three more books by 2000: Pros and Cons: The Criminals Who Play in the NFL; Athletes and Acquaintance Rape; and Without Reservation: How a Controversial Indian Tribe Rose to Power and Built the World's Largest Casino. Most importantly, he writes for Sports Illustrated which makes him my hero. Brilliant writers have labored for that magazine. The editors have a long record of hiring talented people.
Benedict doesn't shy away from issues that make headlines on those cheesy supermarket tabloids, though. After Kobe Bryant was arrested on rape charges he published Out of Bounds: Inside the NBA's Culture of Rape, Violence & Crime. The book led to an ABC News 20/20 special and three stories he wrote for Sports Illustrated.
For those of you with an opinion on eminent domain, Benedict's Little Pink House: A True Story of Defiance and Courage might cause you to give him a standing 'O'. He wrote about Kelo v. New London, one of the most controversial Supreme Court decisions since Roe v. Wade. The New York Times reviewer wrote, "Little Pink House" is the story of Susette Kelo, who left a loveless marriage in 1997 to renovate a tiny Victorian water¬front house. Kelo quickly found herself on the wrong end of an ambitious plan to turn her neighborhood into a vast corporate playground for Pfizer Inc., complete with a luxury hotel, a health club and sleek condos. The investigative reporter Jeff Benedict has decided to cast Kelo in the style of Julia Roberts as Erin Brockovich. But this comes at some journalistic cost: by the time he's finished introducing us to his protagonist (who "had a body that defied the fact that she had delivered five children. Her fiery red hair ran all the way down to her waist"), he risks having written the world's first bodice-ripper about the takings clause."
Benedict's book on the Jack in the Box incident might be worth reading and it will stir the pot, again; a disappointment to a few people that are happy that it had finally faded into history. He spent three years researching it and it's given him some bona fides in food safety issues.
I asked him a few questions about the book and food safety and found myself agreeing with him on quite a few things. A few of his other opinions? I'm not so sure – read his answer to my last question, for instance. You be the judge.
Q. You're working on a book about the Jack in the Box E. coli outbreak nearly 18 years ago. Why did you pick that event as your next subject?
A. Actually, I initially set out to write a book about the Salmonella outbreak tied to the Peanut Corporation of America nearly two years ago. Nine people died in the outbreak. I interviewed surviving family members from that outbreak in Vermont, Minnesota and Oregon. I also met personally with Peanut Corporation CEO Stewart Parnell at his home and in his attorney's law office in Roanoke, Virginia, shortly after he invoked his Fifth Amendment privilege and chose not to answer questions before Congress. But in the end, that case didn't have all the necessary elements for a book.
Nonetheless, while researching that case I became familiar with Bill Marler. He represented numerous families in the peanut case. His name also surfaced in my research of other food poison outbreaks. Through discussions with him and other experts, I increasingly turned my attention to the Jack in the Box case. That case is ideal for a book or a movie. Plus, all the key players were willing to participate, including some of the Jack in the Box officials who were at the helm when the outbreak took place.
Q. There were two key figures in that first major outbreak: Robert Nugent, Jack in the Box's CEO and Dave Theno. Nugent became the scapegoat; Theno created E. coli 101 or 'how to clean up the mess afterwards.' In your book research, what have you found out about these two people?
A. On top of numerous phone interviews and many email exchanges with both men, I travelled to San Diego and spent time with Bob Nugent and Dave Theno. I even met Theno in Texas and toured a meat packing plant that uses the safety procedures that he helped implement in the aftermath of the Jack in the Box outbreak.
I don't want to give too much away here. But suffice it to say that I was very impressed with Nugent's candor and his genuine sorrow. People will be surprised by his contribution to the story. As for Theno, he's a character that is impossible not to like. One of the best things Nugent did was hire Theno. I don't think he could have gotten a better guy to revolutionize Jack in the Box's food safety system.
Q. You seem to be enamored of Bill Marler, a lawyer who built his business around food safety issues. He's not one of the most popular people in the meat business. Talking to cattlemen, now, what has he accomplished in the food safety arena?
A. First off, if everybody liked Bill Marler he probably wouldn't be doing his job. No leader pleases everyone. Bill Marler has really emerged as a self-made authority on foodborne illness and food safety. He's changed the way insurance carriers compensate foodborne illness victims, especially children. He has done the only independent testing of non-O157 E. coli (STEC's) presence in meat. He has raised awareness to food safety risks and educated the public through outreach and non-profit work. I could go on.
The bottom line is that if you take him out of the picture, the business of food safety would look terribly different today. And I do mean terribly. It's rare that one person can cast such a huge shadow over an entire industry. As another highly respected lawyer told me, "Bill Marler is the #1 lawyer in his field. How often can you say that about someone?"
Q. The Senate might vote on the Food Safety Modernization Act right after the mid-term elections or whenever Senator Tom Coburn (R-OK) decides to release it. Like most bills, it has strengths and weaknesses. What's your opinion on the changes it might create – good and bad - if passed?
A. I have not spent a lot of time focused on the bill except to know that the House passed a similar bill in July of 2009. I understand that both bills only focus on food regulated by the FDA not the FSIS. I think it is fairly clear that more oversight is necessary on food regulated by FDA. Being inspected once every 5-7 years simply does not make sense.
Q. There is an ongoing debate between some of the people in the meat business about the six E. coli STEC's. The AMI says, "declaring non-O157 STECS to be adulterants will not enhance the food safety system, and we think that application of such a policy could consume resources that could be better spent elsewhere to achieve meaningful food safety progress."
Marler self-funded a half million-dollar project aimed at demonstrating the prevalence of STEC's in beef sold at retail to back up his petition to have them declared adulterants. With the limited resources available, what's the best answer?
A. There's no question that the USDA should declare these non-0157 strains as adulterants. That simple step would be a catalyst for all labs to test for the presence of these strains in stool cultures submitted by physicians. There's a simple way of seeing the wisdom in this approach. Prior to the Jack in the Box outbreak, E. coli 0157H7 was not considered an adulterant. As a result, doctors didn't look for it and labs didn't test for it. That all changed after four children died. The change in laws has prevented another large-scale outbreak tied to E. coli O157:H7. The mandated testing leads to early detection, which enables public health officials to notify the public before an outbreak gets out of control. This, to me, is a no-brainer.
Q. Let's point out that meat is not the leading source of foodborne illness. It's a dubious honor that belongs to vegetables. Two of the most widely publicized outbreaks of the past few years were tied to peanuts and eggs. Yet many people still say, "In America, we have the safest food in the world." Break it down for me; in your opinion, how safe is our food?
A. Any time you have such grand scale mass production as we currently see with beef, pork, chicken, and eggs and so many other products, there are going to be problems.
The root cause of many of our food safety issues today is size. We have gotten so far away from consuming locally grown fruits and vegetables and locally raised meat and poultry. The food system has gotten so big and so complicated that most people have no idea where their food comes from, who produced it, or how it got from farm to fork. In fact, a lot of food today doesn't come from farms. It comes from what I'll call factories. The risks go down when you know who, when, where and how your food was produced.
Chuck Jolley is a free lance writer, based in Kansas City, who covers a wide range of ag industry topics for Cattlenetwork.com and Agnetwork.com.
Eat safer: Novel approach detects unknown food pathogens
15.oct.10
Indiana University
Cindy Fox Aisen
http://www.genengnews.com/industry-updates/eat-safer-novel-approach-detects-unknown-food-pathogens/97094066/
INDIANAPOLIS -- Technologies for rapid detection of bacterial pathogens are crucial to maintaining a secure food supply.
Researchers from the School of Science at Indiana University-Purdue University Indianapolis (IUPUI) and the Bindley Bioscience Center at Purdue University have developed a novel approach to automated detection and classification of harmful bacteria in food. The investigators have designed and implemented a sophisticated statistical approach that allows computers to improve their ability to detect the presence of bacterial contamination in tested samples. These formulas propel machine-learning, enabling the identification of known and unknown classes of food pathogens.
The study appears in the October issue of the journal Statistical Analysis and Data Mining.
"The sheer number of existing bacterial pathogens and their high mutation rate makes it extremely difficult to automate their detection," said M. Murat Dundar, Ph.D., assistant professor of computer science in the School of Science at IUPUI and the university's principal investigator of the study. "There are thousands of different bacteria subtypes and you can't collect enough subsets to add to a computer's memory so it can identify them when it sees them in the future. Unless we enable our equipment to modify detection and identification based on what it has already seen, we may miss discovering isolated or even major outbreaks."
To detect and identify colonies of pathogens such as listeria, staphylococcus, salmonella, vibrio and E. coli based on the optical properties of their colonies, the researchers used a prototype laser scanner, developed by Purdue University researchers. Without the new enhanced machine-learning approach, the light-scattering sensor used for classification of bacteria is unable to detect classes of pathogens not explicitly programmed into the system's identification procedure.
"We are very excited because this new machine-learning approach is a major step towards a fully automated identification of known and emerging pathogens in real time, hopefully circumventing full-blown, food-borne illness outbreaks in the near future. Ultimately we would like to see this deployed to tens of centers as part of a national bio-warning system," said Dundar.
"Our work is not based on any particular property of light scattering detection and therefore it can potentially be applied to other label-free techniques for classification of pathogenic bacteria, such as various forms of vibrational spectroscopy," added Bartek Rajwa, Ph.D., the Purdue principal investigator of the study.
Dundar and his colleagues believe this methodology can be expanded to the analysis of blood and other biological samples as well.
Salmonella enterica Pulsed-Field Gel Electrophoresis Clusters, Minnesota, USA, 2001–2007
01.nov.10
CDC, Volume 16, Number 11
Joshua M. Rounds, Craig W. Hedberg, Stephanie Meyer, David J. Boxrud, and Kirk E. Smith
http://www.cdc.gov/eid/content/16/11/1678.htm
Abstract
We determined characteristics of Salmonella enterica pulsed-field gel electrophoresis clusters that predict their being solved (i.e., that result in identification of a confirmed outbreak). Clusters were investigated by the Minnesota Department of Health by using a dynamic iterative model. During 2001–2007, a total of 43 (12.5%) of 344 clusters were solved. Clusters of >4 isolates were more likely to be solved than clusters of 2 isolates. Clusters in which the first 3 case isolates were received at the Minnesota Department of Health within 7 days were more likely to be solved than were clusters in which the first 3 case isolates were received over a period >14 days. If resources do not permit investigation of all S. enterica pulsed-field gel electrophoresis clusters, investigation of clusters of >4 cases and clusters in which the first 3 case isolates were received at a public health laboratory within 7 days may improve outbreak investigations.
Salmonellosis is a major foodborne illness that results in ≈1.4 million infections, 15,000 hospitalizations, and 400 deaths each year in the United States (1,2). Salmonella infections are primarily of foodborne origin but can also occur through contact with infected animals, humans, or their feces (3). The epidemiology of salmonellosis is complex largely because there are >2,500 distinct serotypes (serovars) with different reservoirs and diverse geographic incidences (4). Changes in food consumption, production, and distribution have led to an increasing frequency of multistate outbreaks associated with fresh produce and processed foods (5).
The development of molecular subtyping by pulsed-field gel electrophoresis (PFGE) has revolutionized Salmonella spp. surveillance. The National Molecular Subtyping Network for Foodborne Disease Surveillance (PulseNet) provides state and local public health department laboratories with standardized methods to subtype Salmonella serovars and normalize PFGE patterns against a global reference standard provided by the Centers for Disease Control and Prevention (CDC) (6,7). Molecular subtyping enhances case definition specificity, enabling outbreaks to be detected and controlled at an earlier stage, and enabling detection of geographically dispersed outbreaks (8–10).
Although the benefits of molecular subtyping, specifically by PFGE, in foodborne disease outbreak detection and investigation have been well established, there is no consensus about when a PFGE cluster warrants further investigation and almost no quantitative analysis about characteristics of PFGE clusters that indicate a common source will be identified (11–15). Cluster size and the number of days from receipt of the first cluster case isolate to the third case isolate received by the public health laboratory were predictors of a source of infection being identified for Listeria monocytogenes clusters in France (16). The objective of this study was to determine characteristics of Salmonella PFGE clusters that could serve as useful predictors for their being solved (i.e., result in identification of a confirmed outbreak). This information could help public health agencies with limited resources prioritize investigation of Salmonella PFGE clusters.
Materials and Methods
Salmonella infections are reportable to the Minnesota Department of Health (MDH) by state law (17). Clinical laboratories are required to forward all Salmonella isolates to the MDH Public Health Laboratory (PHL). PFGE subtyping after digestion with XbaI is conducted on all isolates as soon as they are received according to PulseNet protocols (18). PFGE subtypes are uploaded into the national PulseNet database (6). All Minnesota residents with a culture-confirmed Salmonella infection are routinely interviewed as soon as possible by MDH staff with a standard questionnaire about symptom history, food consumption, and other potential exposures occurring in the 7 days before onset of illness. The questionnaire contains detailed food exposure questions, including open-ended food histories and objective yes/no questions about numerous specific food items, as well as brand names and purchase locations. Clusters are investigated by using an iterative model in which suspicious exposures identified during initial case-patient interviews are added to the standard interview for subsequent cases (19–21). Similarly, initial cluster case-patients may be reinterviewed to ensure uniform ascertainment of the suspicious exposures. This iterative approach is used to identify exposures for further evaluation with formal hypothesis testing, product sampling, or product tracing (19).
A cluster was defined as >2 cases of salmonellosis in different households with isolates of the same serovar and PFGE subtype and with specimen collection dates within 2 weeks (22). Thus, a single cluster would be ongoing as long as a new isolate was collected within 2 weeks after the most recent isolate in the cluster. A cluster was considered solved if the epidemiologic evaluation of that cluster resulted in the identification of a common source of infection for those cases and consequently the documentation of a confirmed outbreak. Therefore, the terms solved cluster and confirmed outbreak are equivalent and used interchangeably.
Inclusion and Exclusion Criteria
Laboratory-confirmed cases of nontyphoidal Salmonella enterica infection among Minnesota residents with specimen collection dates from January 1, 2001, through December 31, 2007, for which isolates were received and subtyped by MDH PHL were included in the study. Isolates not received through routine surveillance (i.e., testing was requested or conducted by MDH as a part of an ongoing investigation) were excluded from the analysis.
Solved clusters were included if they were detected and identified solely on the basis of investigation of cases identified through submission of isolates to MDH for routine laboratory surveillance. Solved clusters for which a call to the MDH foodborne disease hotline (www.health.state.mn.us/divs/idepc/dtopics/foodborne/reporting.html) (e.g., from the public or a healthcare provider) directly contributed to the identification of an outbreak were excluded from analysis. Secondary clusters, defined as clusters in which the cases were part of a confirmed outbreak that had been previously identified, were also excluded from analysis. Clusters that were part of a probable outbreak (an epidemiologic evaluation suggested, but did not confirm, a common source of infection) were also excluded.
Study Variables
Variables incorporated into the analysis were cluster year, cluster size, cluster case density, cluster serovar, cluster subtype, and cluster serovar diversity. Cluster size was defined as the number of cases in each cluster and was categorized into cluster sizes of 2, 3, 4, and >5. For clusters in which a common source was identified, only cases received before the cluster was solved were included. Cluster case density was defined as the number of days from receipt date of the first cluster isolate at MDH PHL to the receipt date of the third cluster isolate and was categorized into cluster case densities of 0, 1–7, 8–14, and >14 days (16).
Cluster serovar was coded as a categorical variable on the basis of serovar frequency. Serovars representing >20% of all isolates (Typhimurium and Enteritidis) were categorized as very common, those representing 3%–20% (Newport, Heidelberg, and Montevideo) as common, and those representing <3% (all other serovars) as uncommon. The relationship between common and uncommon PFGE subtypes and solving a cluster was examined for serovars Typhimurium and Enteritidis. For serovar Typhimurium, clusters with CDC PFGE subtype designations JPXX01.0003, JPXX01.0410, and JPXX01.0111 (each representing >8% of all Typhimurium isolates) were categorized as common, and all other subtypes were categorized as uncommon. For serovar Enteritidis, clusters with CDC PFGE subtype designations JEGX01.0004 and JEGX01.0030 (each representing >20% of all Enteritidis isolates) were categorized as common, and all other subtypes were categorized as uncommon.
Cluster serovar diversity was examined by categorizing the 17 most frequent serovars into highly clonal or low clonality serovars on the basis of the Simpson diversity index (23). Serovars with a Simpson index score <0.90 were considered highly clonal, and serovars with a Simpson index score >0.90 were considered to have low clonality. Cluster investigation thresholds were examined by comparing the percentage of outbreak clusters meeting a threshold, cluster investigation positive predictive value, and estimated interview burden in hours per year for various investigational thresholds. The time required to interview each patient with a Salmonella infection by using the MDH standard questionnaire was recorded for a 6-month period in 2008, and the median interview time was calculated.
Statistical Analysis
A descriptive analysis was conducted to characterize the frequency of Salmonella serovars and subtypes. Mantel-Haenszel χ2 test for trend was used to characterize temporal trends in the number of Salmonella clusters that were solved. Two-sided Wilcoxon rank-sum tests were used to compare the median cluster size and cluster density of point source and non–point source outbreaks. Univariate analysis was performed to calculate odds ratios (ORs) and 95% confidence intervals (CIs) characterizing the crude associations between Salmonella cluster serovar, cluster PFGE subtype, cluster serovar diversity, cluster size, and cluster case density and a cluster being solved. Mantel-Haenszel χ2 tests for trend and interaction terms were used to investigate the linear nature of the relationship between cluster size, cluster case density, and the outcome. SAS software version 9.1 (SAS Institute, Cary, NC, USA) was used for descriptive and univariate analysis. An α value <0.05 was considered significant.
Results
During 2001–2007, a total of 4,154 nontyphoidal Salmonella isolates from Minnesota residents were received at MDH through routine surveillance; they represented 98% of reported Salmonella cases (n = 4,235, incidence 11.78 cases/100,000 person-years). PFGE subtyping was performed for 4,018 (97%) isolates, which were included in the study. Among these isolates, 194 Salmonella serovars were observed. The 6 most common S. enterica serovars were Typhimurium, 1,004 (25%); Enteritidis, 822 (20.5%); Newport, 314 (7.8%); Heidelberg, 223 (5.6%); Montevideo, 121 (3.0%); and Saintpaul, 81 (2.0%) (Figure 1).
The frequency of PFGE subtypes was examined in detail for serovars Typhimurium and Enteritidis. The 3 most common subtypes of serovar Typhimurium were JPXX01.0003, 107 (11%); JPXX01.0410, 87 (9%); and JPXX01.0111, 85 (8%). The 3 most common subtypes of serovar Enteritidis were JEGX01.0004, 309 (38%); JEGX01.0030, 181(22%); and JEGX01.0005, 106 (13%).
Serovar diversity was examined by comparing Simpson diversity indices for the 17 most frequent serovars (Table 1). Javiana, Newport, Agona, Infantis, and Typhimurium were low clonality serovars. Heidelberg, Hadar, Enteritidis, Thompson, and I 4,5,12:I:– were highly clonal serovars.
Cluster and Outbreak Characteristics
During 2001–2007, a total of 376 Salmonella PFGE clusters were detected; they represented 1,399 (35%) isolates. Thirty-two (8.5%) clusters were excluded from analysis (21 secondary clusters, 7 clusters in which a hotline call directly contributed to identification of an outbreak, and 4 probable outbreak clusters). Forty-three (12.5%) of the 344 clusters included in the analysis were solved.
During 2001–2007, a total of 65 confirmed Salmonella outbreaks involving Minnesota cases were identified; these represented 502 (12.5%) isolates. Twenty-two (34%) outbreaks were excluded from analysis (6 were multistate outbreaks in which only 1 case was identified in Minnesota; in 7 outbreaks, a hotline call contributed to identification of the outbreak; 1 was an outbreak was not detected by PFGE; 4 were outbreaks that did not have cases that met the cluster definition; and 4 outbreaks were considered probable). The remaining 43 outbreaks, representing 287 (7%) isolates, were included in the analysis and were composed of 35 foodborne, 6 person-to-person, and 2 animal contact outbreaks. Of these 43 outbreaks, 30 (70%) involved 1 facility (restaurant, daycare center, school) or event and therefore were classified as point source. Thirteen (30%) involved commercially distributed food items at multiple points of sale (grocery stores, restaurants) and therefore were classified as non–point source. The median cluster size of point source outbreaks was 3 cases, and the median cluster size of non-point source outbreaks was 5 cases (p<0.01, by Wilcoxon rank-sum test). The median cluster density was 6 days for point source and non-point source outbreaks (p = 0.74 by Wilcoxon rank-sum test).
Temporal Trends
During the study period, the median number of Salmonella isolates subtyped per year was 567 (range 507–662 isolates). The median number of Salmonella clusters per year was 50 (r ange 44–57 clusters). The median number of confirmed Salmonella outbreaks per year was 6 (range 4–8 outbreaks). There were no statistically significant trends in the proportion of Salmonella clusters that resulted in identification of a confirmed outbreak (p = 0.20) (Figure 2).
Cluster Serovar and Cluster Serovar Diversity
Clusters of the common Salmonella serovars Newport, Heidelberg, and Montevideo had 2.7× higher odds of being solved than did clusters of the very common serovars Enteritidis and Typhimurium (Table 2). The proportion of uncommon serovar clusters that were solved did not differ significantly from the proportion of very common or common serovar clusters that were solved (Table 2). Low clonality serovar clusters were not significantly more likely to be solved than highly clonal serovar clusters (OR 1.6, 95% CI 0.8–3.1).
Cluster Subtype
No significant associations between the subtype frequency of a cluster and a cluster being solved were observed. Uncommon serovar Enteritidis subtype clusters were not significantly more likely to be solved than were common subtype clusters (OR 1.4, 95% CI 0.4–5.1). Uncommon serovar Typhimurium subtype clusters were not significantly more likely to be solved than were common subtype clusters (OR 0.9, 95% CI 0.3–3.2).
Cluster Size
The probability of a cluster being solved increased significantly as the number of cluster cases increased (Mantel-Haenszel χ2 for trend 13.7, p<0.001) (Table 2). The odds of solving a cluster of >5 cases were 3.8× higher than the odds of solving a cluster of 2 cases. Clusters of 4 cases were 3.9× more likely to be solved than were clusters of 2 cases. Twenty-four percent of clusters with >4 cases were solved (Table 2). Clusters of 3 cases were 2.1× more likely to be solved than clusters of 2 cases, but the difference was not statistically significant. There was statistical evidence of a nonlinear relationship between cluster size and solving the cluster (Wald χ2 for interaction 5.0, p = 0.03). The dose response between cluster size and solving a cluster plateaued after a cluster size of 4.
Cluster Case Density
The proportion of clusters solved increased significantly as the density of cluster cases increased (Mantel-Haenszel χ2 for trend, 12.7, p<0.001) (Table 2). The odds of solving a cluster if the first 3 case isolates were received on the same day were 25.8× higher than the odds of solving a cluster in which the first 3 case isolates were received during a period >14 days (Table 2). The odds of solving a cluster if the first 3 case isolates were received within 1–7 days were 5.0× higher than the odds of solving a cluster in which the first 3 case isolates were received during a period >14 days. Clusters in which the first 3 case isolates were received within 8–14 days were 2.8× more likely to be solved than clusters in which the first 3 case isolates were received during a period >14 days, but the difference was not statistically significant (Table 2). There was statistical evidence of a nonlinear relationship between cluster case density and solving the cluster (Wald χ2 for interaction, 6.96, p<0.01).
Cluster Investigation Threshold
During June–December 2008, 10 MDH staff interviewed 214 persons with Salmonella infections and recorded the time required to complete the MDH standard questionnaire. Interview times did not vary between interviewers. The median interview time was 27 minutes (range 13–56 minutes). Therefore, conducting standard interviews of all cases in the 344 clusters of >2 cases (n = 1,182 [31%] cases) required an estimated 76 interview hours/year. This threshold detected all 43 outbreaks identified through routine laboratory surveillance during the study period and resulted in a cluster investigation positive predictive value (percentage of clusters investigated that were solved) of 13% (Table 3). Other cluster investigation thresholds had outbreak detection sensitivities of 53%–81% and positive predictive values of 23%–28% (Table 3).
Discussion
During the study period, 344 Salmonella PFGE clusters were identified and 43 (13%) were solved. Cluster size and cluster case density were the most useful predictors of a cluster being solved. The proportion of clusters that were solved increased as the number of cases in the cluster increased (up to 4 cases). The association was not linear and the percentage solved did not increase further for clusters with >5 cases. The observed association is logical because as the number of cluster cases increases, the amount of epidemiologic data available for evaluation also increases. Our results suggest that public health officials should not wait to investigate Salmonella clusters if >4 cluster cases have been received.
The ability to solve a cluster of cases of Salmonella infection was also strongly associated with the density of the cluster cases. The proportion of clusters that were solved increased as the density of the cluster cases increased, but this relationship was not linear. This association is also logical. Dense clusters increase the likelihood that the cluster cases are epidemiologically linked rather than unrelated sporadic cases. In addition, dense clusters also likely signal larger outbreaks. Our results demonstrated a clear increase in the success of solving clusters in which the first 3 case isolates were received within 7 days.
In theory, PFGE subtyping is less useful for recognizing clusters of unusual serovars worth investigating. In the current study, clusters of the common serovars Newport, Montevideo, and Heidelberg were statistically more likely to be solved than clusters of the very common serovars Enteritidis and Typhimurium. However, clusters of uncommon serovars were not more likely to be solved than were clusters of common or very common serovars. It has been suggested that uncommon serovar clusters may be associated with uncommon food vehicles, which makes them more difficult to solve by using standard methods (24). The relationship between serovar frequency and the likelihood of solving a cluster is unclear and warrants further study.
The limited number of solved clusters prevented multivariate analysis from being used to characterize the independent effect of predictors and possible effect modification between predictors. However, comparing the magnitude of the estimated effect of cluster size and cluster case density suggests that cluster case density may be a more useful predictor of a cluster being solved.
The 22 confirmed outbreaks that were excluded from the analysis demonstrate the value for national collaboration such as PulseNet and use of outbreak detection methods in addition to PFGE clustering within a given state. Six outbreaks were solved in which Minnesota only had 1 case, which demonstrated the utility of molecular subtyping in detecting geographically dispersed outbreaks. For 7 confirmed outbreaks, a call placed to the MDH foodborne illness hotline contributed to identification of the outbreak and demonstrated the utility of complaint systems in detecting outbreaks.
Interviewing all persons with Salmonella infection required a median of 27 minutes per person with Salmonella infection when the MDH standard questionnaire was used. By extrapolation, MDH staff spent ≈244 hours/year conducting routine interviews of persons with Salmonella infections. This figure does not include time spent attempting to reach persons, gathering demographic information from clinicians, or reinterviewing persons for cluster investigations. We recommend interviewing all persons with Salmonella infection and investigating all PFGE clusters to identify as many outbreaks as possible. However, many health departments do not have the resources to interview all persons with Salmonella infection or investigate all small clusters. Rather, they must balance the time required for these efforts and the ability to detect outbreaks (25).
Incorporating a cluster investigation threshold on the basis of cluster size and cluster case density can decrease the number of unsuccessful cluster investigations and conserve public health resources. However, this approach would also reduce the number of outbreaks that would be identified. One reason for this finding is that outbreaks that are manifested as smaller, less dense clusters would not be investigated. Another potential disadvantage of a cluster threshold approach is that delay of interviews until a cluster is solved can decrease the quality of exposure information obtained and therefore the likelihood that the cluster will be solved (12).
Four confirmed outbreaks during the study did not meet the cluster definition, and many confirmed outbreaks had cases that were outside the cluster definition. This finding is an important reminder that lack of temporal clustering does not eliminate the possibility of an outbreak. Increasing the period covered by a cluster definition will yield the benefit of solving more outbreaks. However, more resources will be expended conducting unsuccessful cluster investigations. The results of this study suggest that the use of a 2-week cluster window is sufficiently sensitive to detect most outbreaks. However, in practice, MDH epidemiologists do not use a strict 2-week cluster window when investigating clusters. Instead, all persons with Salmonella infection are interviewed and cases with matching PFGE patterns are often compared even if the second case is received >2 weeks after the first case.
The potential utility of the cluster investigation thresholds reported is based on the characteristics of the population of Minnesota and MDH surveillance methods: conducting real-time PFGE subtyping of all Salmonella isolates, interviewing all case-patients in real time by using a detailed exposure questionnaire from a central location for the entire state, and investigating clusters by using an iterative model (19–21). These factors aid in the timeliness of outbreak detection and investigation in Minnesota. These results may not be applicable in jurisdictions in which PFGE is not conducted in real time or batching of PFGE isolates occurs. Additional studies at the national level and in other states are needed to understand surveillance characteristics in other states and determine useful predictors of multistate clusters being solved.
Although successful cluster investigations will depend on the experience and ability of public health staff involved, this study demonstrates the increased probability of a cluster being solved as the number of cases in a cluster increases and as the cluster density increases. Specifically, investigation of PFGE clusters of >4 Salmonella case isolates and clusters in which the first 3 cases were received at the MDH PHL within 1 week yielded a major benefit in terms of outbreak identification. These results establish a benchmark for surveillance of Salmonella infections, and may provide a basis for investigating clusters of Salmonella cases for public health agencies with limited resources.
Acknowledgments
We thank Jeff Bender; the Public Health Laboratory staff; and the Foodborne, Vectorborne, and Zoonotic Diseases Unit staff at the Minnesota Department of Health for their contributions to the study.
This study was supported in part by a cooperative agreement (U50/CCU51190) with the Centers for Disease Control and Prevention as part of the Emerging Infections Program, Foodborne Diseases Active Surveillance Network (FoodNet).
Mr Rounds is an epidemiologist with the Minnesota Department of Health. His research interests include evaluating public health surveillance methods to improve outbreak investigations and disease control efforts.
References
1. Voetsch AC, Van Gilder TJ, Angulo FJ, Farley MM, Shallow S, Marcus R, et al. FoodNet estimate of the burden of illness caused by nontyphoidal Salmonella infections in the United States. Clin Infect Dis. 2004;38(Suppl 3):S127–34. PubMed DOI
2. Mead PS, Sultsker L, Dietz V, McCaig LF, Bresee JS, Shapiro C, et al. Food-related illness and death in the United States. Emerg Infect Dis. 1999;5:607–25. PubMed DOI
3. Salmonellosis. In: Heymann DL, Thuriaux MC, editors. Control of communicable diseases manual. 18th ed. Washington: United Book Press; 2004. p. 469–73.
4. Olsen SJ, Bishop R, Brenner FW, Roels TH, Bean N, Tauxe RV, et al. The changing epidemiology of salmonella: trends in serotypes isolated from humans in the United States, 1987–1997. J Infect Dis. 2001;183:753–61. PubMed DOI
5. Salmonella infections. In: Pickering LK, Baker CJ, Kimberlin DW, Long SS, editors. Red book: 2006 report of the Committee on Infectious Diseases. 27th ed. Elk Grove Village (IL): American Academy of Pediatrics, 2006. p. 584–89.
6. Swaminathan B, Barrett TJ, Hunter SB, Tauxe RV. CDC PulseNet Task Force. PulseNet: the molecular subtyping network for foodborne bacterial disease surveillance, United States. Emerg Infect Dis. 2001;7:382–9.
7. Swaminathan B, Barrett TJ, Fields P. Surveillance for human Salmonella infections in the United States. J AOAC Int. 2006;89:553–9.
8. Tauxe RV. Molecular subtyping and the transformation of public health. Foodborne Pathog Dis. 2006;3:4–8. PubMed DOI
9. Allos BM, Moore MR, Griffin PM, Tauxe RV. Surveillance for sporadic foodborne disease in the 21st century: the FoodNet perspective. Clin Infect Dis. 2004;38(Suppl 3):S115–20. PubMed DOI
10. Barrett TJ, Gerner-Smidt P, Swaminathan B. Interpretation of pulsed-field gel electrophoresis patterns in foodborne disease investigations and surveillance. Foodborne Pathog Dis. 2006;3:20–31. PubMed DOI
11. Buehler JW, Hopkins RS, Overhage JM, Sosin DM, Tong V; CDC Working Group. Framework for evaluating public health surveillance systems for early detection of outbreaks: recommendations form the CDC Working Group. MMWR Recomm Rep. 2004;53(RR-5):1–11.
12. Hedberg CW, Greenblatt JR, Matyas BT, Lemmings J, Sharp DJ, Skibicki RT, et al. Timeliness of enteric disease surveillance in 6 US states. Emerg Infect Dis. 2008;14:311–3. PubMed DOI
13. Lynch M, Painter J, Woodruff R, Braden C. Surveillance for foodborne-disease outbreaks—United States, 1998–2002. MMWR Surveill Summ. 2006;55(SS10):1–42.
14. Hedberg CW, Besser JM. Commentary: cluster evaluation, PulseNet, and public health pracitce. Foodborne Pathog Dis. 2006;3:32–5. PubMed DOI
15. Council to Improve Foodborne Outbreak Response (CIFOR). Guidelines for foodborne disease outbreak response. Atlanta: Council of State and Territorial Epidemiologists; 2009.
16. Hedberg CW, Jacquet C, Goulet V. Surveillance of listeriosis in France, 2000–2004: evaluation of cluster investigation criteria. Presented at the 16th International Symposium on Problems of Listeriosis. Savannah (GA) USA; 2007 Mar 20–23 [cited 20101 Jul 8]. http://www.aphl.org/profdev/conferences/proceedings/Documents/2007_ISOPOL/Surveillance_of_Listeriosis_in_France.pdf
17. Reportable disease rule. Minnesota Department of Health. 2009 Jun 23 [cited 2010 Jul 8]. http://www.health.state.mn.us/divs/idepc/dtopics/reportable/rule/rule.html
18. Ribot EM, Fair MA, Gautom R, Cameron DN, Hunter SB, Swaminathan B, et al. Standardization of pulsed-field gel electrophoresis protocols for the subtyping of Escherichia coli O157:H7, Salmonella, and Shigella for PulseNet. Foodborne Pathog Dis. 2006;3:59–67. PubMed DOI
19. Smith KE, Medus C, Meyer SD, Boxrud DJ, Leano F, Hedberg CW, et al. Outbreaks of salmonellosis in Minnesota (1998 through 2006) associated with frozen, microwaveable, breaded, stuffed chicken products. J Food Prot. 2008;71:2153–60.
20. Centers for Disease Control and Prevention. Multistate outbreak of Salmonella infections associated with frozen pot pies—United States, 2007. MMWR Morb Mortal Wkly Rep. 2008;57:1277–80.
21. Hedican E, Hooker C, Jenkins T, Medus C, Jawahir S, Leano F, et al. Restaurant Salmonella Enteritidis outbreak associated with an asymptomatic infected food worker. J Food Prot. 2009;72:2332–6.
22. Bender JB, Hedberg CW, Boxrud DJ, Besser JM, Wicklund JH, Smith KE, et al. Use of molecular subtyping in surveillance for Salmonella enterica serotype Typhimurium. N Engl J Med. 2001;344:189–95. PubMed DOI
23. Boxrud D, Pederson-Gulrud K, Wotton J, Medus C, Lyszkowicz E, Besser J, et al. Comparison of multiple-locus variable-number tandem repeat analysis, pulsed-field gel electrophoresis, and phage typing for subtype analysis of Salmonella enterica serotype Enteritidis. J Clin Microbiol. 2007;45:536–43. PubMed DOI
24. Lynch MF, Tauxe RV, Hedberg CW. The growing burden of foodborne outbreaks due to contaminated fresh produce: risks and opportunities. Epidemiol Infect. 2009;137:307–15. PubMed DOI
25. Hoffman RE, Greenblatt J, Matyas BT, Sharp DJ, Esteban E, Hodge K, et al. Capacity of state and territorial health agencies to prevent foodborne illness. Emerg Infect Dis. 2005;11:11–6.
Killer cattle virus wiped out
16.oct.10
Sydney Morning Herald
Guardian News & Media
http://www.smh.com.au/world/science/killer-cattle-virus-wiped-out-20101015-16nnw.html
Scientists have eradicated a killer virus in the wild, only the second time such a feat has been achieved.
Researchers at the United Nations said that rinderpest, a virus that causes devastating cattle plague, has been wiped out. It is the first such announcement since the end of smallpox more than 30 years ago.
John Anderson, the head of the UN's Food and Agriculture Organisation, called the success ''the biggest achievement of veterinary history''.
A global eradication plan for rinderpest, backed by the UN and the World Organisation for Animal Health, began in 1994.
Infected livestock were killed and animals in areas surrounding outbreaks were vaccinated to protect them from the disease.
Bioniche scientists present at Modern Vaccine & Adjuvant Formulation Conference in FRANCE
15.oct.10
Bioniche Life Sciences Inc.
http://www.prnewswire.com/news-releases/bioniche-scientists-present-at-modern-vaccine--adjuvant-formulation-conference-in-france-105023944.html
BELLEVILLE, ON -- Bioniche Life Sciences Inc. (TSX: BNC), a research-based, technology driven Canadian biopharmaceutical company, today announced that two of its senior research scientists gave presentations at the Modern Vaccine and Adjuvant Formulation Conference in Cannes, France this week.
Challenge Study Results for EconicheTM
Dr. Dragan Rogan, Chief Veterinary Scientific Officer at Bioniche Life Sciences Inc., presented a paper that he co-authored, "Vaccination with Type III Secreted Proteins Leads to Decreased Shedding in Calves Following Experimental Infection with Escherichia coli O157". The other authors were Dr. Kevin Allen, Dr. Brett Finlay, Dr. Andrew Potter and Dr. David Asper.
Dr. Rogan's presentation summarized the results of a study of the Company's E. coli O157 vaccine in an experimental infection (controlled challenge) model, whereby thirty calves were immunized with the vaccine and commingled with thirty calves that were administered a saline-adjuvant placebo. Calves were vaccinated three times in a 42-day period, then were infected with E. coli O157. Fecal shedding was monitored daily for 14 days. During this period, vaccinates were shown to have a mean log shedding reduction of 1.4 (p=0.002). Researchers concluded that vaccination significantly reduced the number of animals shedding E. coli O157, as well as the number of organisms shed. These data supported the full licensure of the Company's E. coli O157 vaccine (trademarked EconicheTM) by the Canadian Food Inspection Agency (CFIA), as announced in October, 2008.
Immune Adjuvant Activity of Novel Oligonucleotide Sequences
Dr. Nigel C. Phillips, Senior Vice-President, Scientific Affairs and Chief Scientific Officer at Bioniche Life Sciences Inc., gave a presentation about the Company's oligonucleotide development program and the latest oligonucleotide sequences that have been shown to have immune adjuvant activity. His presentation was co-authored by Mélanie Lehoux and Mario C. Filion.
Dr. Phillips highlighted the fact that these oligonucleotide sequences contain non-DNA-bases and, unlike other oligonucleotide immune adjuvants, do not require chemical modifications such as backbone protection or terminal modification. The Company's sequences have demonstrated immune adjuvant activity in animal models using hepatitis B surface antigen and H1N1 virions. These models have shown that they are capable of inducing antiviral antibodies using very limited amounts of antigen and short-term immunization protocols.
About the Oligonucleotide Technology Platform
In 2000, Bioniche announced the discovery of a new class of molecules with potential anticancer activity, referred to by the Company under the trademark, "OligomodulatorTM". This new class of molecules with potential clinical anticancer activity and immune modulating properties is composed of short non-antisense DNA Oligonucleotides that appear to possess a range of novel pharmacological activities. The Company has continued to develop the Oligonucleotide technology platform in the areas of immune stimulation and modulation.
About EconicheTM
EconicheTM has been developed by a strategic alliance formed in 2000 between the University of British Columbia (UBC), the Alberta Research Council (ARC), the University of Saskatchewan's Vaccine & Infectious Disease Organization (VIDO), and Bioniche, which holds the rights for worldwide commercialization of the vaccine. The vaccine prevents the E. coli O157 bacteria from attaching to the intestines of vaccinated cattle, thereby reducing their reproduction within the animal, and reducing the amount of bacteria that can be released through cattle manure in the environment. More than 30,000 cattle have been involved in clinical testing of the vaccine, which is fully licensed in Canada. A U.S. conditional license is pending.
TEXAS: Health inspectors find unsafe food surfaces at Seabrook Valero
14.oct.10
Ultimate Clear Lake
Jeff Louderback
http://www.ultimateclearlake.com/stories/217511-health-inspectors-find-unsafe-food-surfaces-at-seabrook-valero
Harris County health inspectors observed a variety of violations related to unsafe food surface rules at the Valero convenience store on Oct. 7 at 3324 Nasa Road in Seabrook.
The department considers this type of violation as one that could lead to the spread of foodborne illnesses.
According to Harris County, unsafe food surface problems include cracked/chipped plates, cups, knives; a cutting board that cannot be easily cleaned; slime on soda nozzles, soda gun and holster, ice machine, and yogurt machines; a cracked or damaged interior surface of a microwave oven; and can openers, knives, utensils that are not clean, broken or in poor condition.
The restaurant did not have enough violations to warrant further action or a return visit from the department, however similar problems were cited when the store was inspected in January.
The store received a score of 6 on a 0-100 scale with 0 being the best number and 100 marking the worst score possible. An establishment must have a score of 20 or higher to be considered a concern and require a follow-up inspection.
AUSTRALIA: Food recall
15.oct.10
FSANZ
http://www.foodstandards.gov.au/consumerinformation/foodrecalls/currentconsumerlevelrecalls/tahinimicrobiologica4962.cfm
Date Notified To FSANZ:
15 October 2010
Food Product:
Tahini
Name of Product:
El Helwa Tahini
Package Description & Size:
908 g, Plastic jar
Use By Date Or Lot Code:
Best Before December 2011
Australian Distribution:
VIC only
Overseas Distribution:
Nil
Reason for Recall:
Microbiological contamination –Salmonella
Comments:
ALEX IMPORTERS
El Helwa Tahini, 908 g plastic jar, Best Before December 2011
Alex Importers is conducting a recall of the above product due to Salmonella contamination.
Any consumers concerned about their health should seek medical advice
The recall applies only to the above product with the nominated size and best before date. No other Alex Importers products are affected by this recall. Customers should return the product to the place of purchase for a full cash refund.
Alex Importers is greatly concerned at any risk to its customers. This recall is being undertaken to ensure the safety of our customers as an ongoing commitment to maintain the highest possible standards of safety and product quality at all times.
For further information please call:
Alex Importers on 0404859684
bites is produced by Dr. Douglas Powell and food safety friends at Kansas State University. For further information, please contact dpowell@ksu.edu or check out bites.ksu.edu.
TO SUBSCRIBE to the listserv version of bites, send mail to:
(subscription is free)
listserv@listserv.ksu.edu
leave subject line blank
in the body of the message type:
subscribe bites-L firstname lastname
i.e. subscribe bites-L Doug Powell
TO UNSUBSCRIBE from the listserv version of bites, send mail to:
listserv@listserv.ksu.edu
leave subject line blank
in the body of the message type: signoff bites-L
archived at http://archives.foodsafety.ksu.edu/fsnet-archives.htm and bites.ksu.edu
posted by Tom Karst @ 12:29 PM
0 Comments:
Post a Comment
Subscribe to Post Comments [Atom]
<< Home