Mr Fadli Salleh, who was married with two young children, had been in critical condition in the intensive care unit (ICU) of Sengkang General Hospital (SKH) after he was one of 72 people who suffered gastroenteritis, allegedly after eating bento boxes prepared by Spize’s River Valley outlet for an event last Tuesday. (the raw egg looks like a Salmonella factory).
The party was for a Deepavali celebration organised by security company Brink’s Singapore and held on its premises at Kaki Bukit.
Mr Fadli attended the gathering as he was deployed to Brink’s Singapore, though the event itself did not involve Sats.
A Sats spokesman said: “We are providing support to the family during this sad and difficult time. Please approach Brinks if you have further questions.”
Brinks offered its condolences to Mr Fadli’s family and said it it was “deeply saddened” that an employee of its business partner died.
A joint statement by the National Environment Agency (NEA), MOH and Agri-Food and Veterinary Authority last Friday said the authorities were notified of the cases last Wednesday and they conducted a joint investigation that day.
Spize’s 409 River Valley Road branch’s licence was suspended at 7pm that evening.
The statement added that they were investigating several cases of gastroenteritis traced to the consumption of food prepared at the restaurant.
“Several hygiene lapses were observed, including leaving ready-to-eat food uncovered in a chiller, not providing soap for hand washing (soap dispenser was faulty) and slotting knives for preparing ready-to-eat food in the gap between the food preparation tables,” said the statement.
Spize had supplied 88 bento sets to Brink’s Singapore and Spize’s co-owner Mr Haresh Sabnani had told The Straits Times on Wednesday before news of Mr Fadli’s death was confirmed that “on that day, 221 bento sets were sent to six different locations, but only that one location was affected”.
The episode starts with a quick discussion of books the guys are planning on reading this week, and a book that arrived mysteriously at the offices of many other food safety folks (including Don and Ben). The food safety discussion goes to a story of a Chicago bus driver pooping on his bus and trying to clean it up with the contents of a coffee cup; Don and Ben chat about the pros and cons of this approach. The guys tackle the safety of storing breast milk, pickling eggs in miso, and what levels of contamination may have led the Romaine-linked E. coli O157 outbreak earlier this year. The show ends on raw flour, TTIs (not STIs) and raw chicken thingies.
The E. coli outbreak occurred between August and October and was traced back to the unpasteurized product, which has a best before date up to and including April 24, 2019.
An investigation is ongoing “to determine the source and extent of contamination,” the BCCDC said.
News 24 reports that at least 20 people have been hospitalised due to salmonella poisoning in Durban, KwaZulu-Natal, eNCA reported on Saturday.
Lancet Laboratories reportedly alerted doctors in the region about cases in both children and adults.
Food that has been affected include orange juice, eggs, fresh vegetables, frozen dinners, dairy products and peanut butter, based on tests by the laboratory.
Lancet says non-typhoidal salmonella species are the leading cause of bacterial food-borne illnesses.
There was this time about 15 years ago, and I was the scientific advisor for a group of food safety heads at Canadian supermarkets. We’d met once or twice a year, and the first four hours would be devoted to, no one takes my job seriously unless there’s an outbreak.
I could relate.
I guess they kept me on because we did good work when BSE was discovered in Canada in 2003: the only country where beef consumption increased after a mad cow disease warning, partly due to me standing in the snow at 6 am on a Guelph street doing national TV, lots due to Sarah and her team managing the phone lines and providing me with soundbites.
I get the sense Loblaws and its various spin-offs aren’t so vigilant
The picture of the tail end of a mouse — visible through the plastic bag surrounding a loaf of D’Italiano bread in a shopping cart — was posted to the website Reddit on Wednesday. The photo had attracted more than 180 comments by the next day.
In a statement, Loblaws public relations director Karen Gumbs apologized to customers — but also assured them the city’s public health department checked out the No Frills location and has “no concerns.”
“The store has taken a number of steps to ensure this doesn’t happen again, including working closely with their third-party pest control team, and inspecting bakery items daily,” she said.
Enterohemorrhagic Escherichia coli serogroup O80, involved in hemolytic uremic syndrome associated with extraintestinal infections, has emerged in France. We obtained circularized sequences of the O80 strain RDEx444, responsible for hemolytic uremic syndrome with bacteremia, and noncircularized sequences of 35 O80 E. coli isolated from humans and animals in Europe with or without Shiga toxin genes.
RDEx444 harbored a mosaic plasmid, pR444_A, combining extraintestinal virulence determinants and a multidrug resistance–encoding island. All strains belonged to clonal complex 165, which is distantly related to other major enterohemorrhagic E. coli lineages. All stx-positive strains contained eae-ξ, ehxA, and genes characteristic of pR444_A.
Among stx-negative strains, 1 produced extended-spectrum β-lactamase, 1 harbored the colistin-resistance gene mcr1, and 2 possessed genes characteristic of enteropathogenic and pyelonephritis E. coli. Because O80–clonal complex 165 strains can integrate intestinal and extraintestinal virulence factors in combination with diverse drug-resistance genes, they constitute dangerous and versatile multidrug-resistant pathogens.
Emerging Multidrug-Resistant Hybrid Pathotype Shiga Toxin–Producing Escherichia coli O80 and Related Strains of Clonal Complex 165, Europe
Cointe A, Birgy A, Mariani-Kurkdjian P, Liguori S, Courroux C, Blanco J, et al. Emerging multidrug-resistant hybrid pathotype Shiga toxin–producing Escherichia coli O80 and related strains of clonal complex 165, Europe. Emerg Infect Dis. 2018 Dec [date cited]. https://doi.org/10.3201/eid2412.180272
Tony McDougal of Poultry World reports that researchers wanted to see how the label impacted consumer perceptions on risk and food-handling behaviour in the light that poultry meat is an important source of foodborne infections, such as campylobacter, salmonella and E.coli.
A random sample of 1235 adults from a representative internet panel received an email linking to the study questionnaire. Information was gathered about knowledge of safe food-handling regarding poultry, their current food-handling behaviour and intention to change after reading the label, as well as influencing factors.
The results, published in the October edition of the journal Food Control, found that respondents of households with people aged 65 or older, with safe food-handling practices and who judge foodborne infections as severe, were more prone to have read the label.
The study also found that after reading the label during the survey, the intention to change behaviour did not differ between the readers and previous non-readers.
“The majority of the respondents had read the label on poultry meat and scored it as important, useful and reassuring. Therefore investigating the feasibility and possible benefits of a similar label on other meat products could be worthwhile.”
The study does not account for:
the fallibility of self-reported surveys (we all wash our hands);
does not account for multi-languages in the diverse cultures we all prepare food; does not account for cross-contamination.
Tony McDougal of Poultry World reports that researchers wanted to see how the label impacted consumer perceptions on risk and food-handling behaviour in the light that poultry meat is an important source of foodborne infections, such as campylobacter, salmonella and E.coli.
A random sample of 1235 adults from a representative internet panel received an email linking to the study questionnaire. Information was gathered about knowledge of safe food-handling regarding poultry, their current food-handling behaviour and intention to change after reading the label, as well as influencing factors.
The results, published in the October edition of the journal Food Control, found that respondents of households with people aged 65 or older, with safe food-handling practices and who judge foodborne infections as severe, were more prone to have read the label.
The study also found that after reading the label during the survey, the intention to change behaviour did not differ between the readers and previous non-readers.
“The majority of the respondents had read the label on poultry meat and scored it as important, useful and reassuring. Therefore investigating the feasibility and possible benefits of a similar label on other meat products could be worthwhile.”
Does not account for the fallibility of self-reported surveys (we all wash our hands); does not account for multi-languages in the diverse cultures we all prepare food; does not account for cross-contamination.
A new computer model that uses machine learning and de-identified and aggregated search and location data from logged-in Google users was significantly more accurate in identifying potentially unsafe restaurants when compared with existing methods of consumer complaints and routine inspections, according to new research led by Google and Harvard T.H. Chan School of Public Health. The findings indicate that the model can help identify lapses in food safety in near real time.
“Foodborne illnesses are common, costly, and land thousands of Americans in emergency rooms every year. This new technique, developed by Google, can help restaurants and local health departments find problems more quickly, before they become bigger public health problems,” said corresponding author Ashish Jha, K.T. Li Professor of Global Health at Harvard Chan School and director of the Harvard Global Health Institute.
The study will be published online November 6, 2018 in npj Digital Medicine.
Foodborne illnesses are a persistent problem in the U.S. and current methods by restaurants and local health departments for determining an outbreak rely primarily on consumer complaints or routine inspections. These methods can be slow and cumbersome, often resulting in delayed responses and further spread of disease.
To counter these shortcomings, Google researchers developed a machine-learned model and worked with Harvard to test it in Chicago and Las Vegas. The model works by first classifying search queries that can indicate foodborne illness, such as “stomach cramps” or “diarrhea.” The model then uses de-identified and aggregated location history data from the smartphones of people who have opted to save it, to determine which restaurants people searching those terms had recently visited.
Health departments in each city were then given a list of restaurants that were identified by the model as being potential sources of foodborne illness. The city would then dispatch health inspectors to these restaurants, though the health inspectors did not know whether their inspection was prompted by this new model or traditional methods. During the period of the study, health departments continued to follow their usual inspection procedures as well.
In Chicago, where the model was deployed between November 2016 and March 2017, the model prompted 71 inspections. The study found that the rate of unsafe restaurants among those detected by the model was 52.1% compared with 39.4% among inspections triggered by a complaint-based system. The researchers noted that Chicago has one of the most advanced monitoring programs in the nation and already employs social media mining techniques, yet this new model proved more precise in identifying restaurants that had food safety violations.
In Las Vegas, the model was deployed between May and August 2016. Compared with routine inspections performed by the health department, it had a higher precision rate of identifying unsafe restaurants.
When the researchers compared the model with routine inspections by health departments in Las Vegas and Chicago, they found that the overall rate across both cities of unsafe restaurants detected by the model was 52.3%, whereas the overall rate of detection of unsafe restaurants via routine inspections across the two cities was 22.7%.
The study showed that in 38% of all cases identified by this model, the restaurant potentially causing foodborne illness was not the most recent one visited by the person who was searching keywords related to symptoms. The authors said this is important because previous research has shown that people tend to blame the last restaurant they visited and therefore may be likely to file a complaint for the wrong restaurant. Yet clinically, foodborne illnesses can take 48 hours or even longer to become symptomatic after someone has been exposed, the authors said.
The new model outperformed complaint-based inspections and routine inspections in terms of precision, scale, and latency (the time that passed between people becoming sick and the outbreak being identified). The researchers noted that the model would be best leveraged as a supplement to existing methods used by health departments and restaurants, allowing them to better prioritize inspections and perform internal food safety evaluations. More proactive and timely responses to incidents could mean better public health outcomes. Additionally, the model could prove valuable for small and mid-size restaurants that can’t afford safety operations personnel to apply advanced food safety monitoring and data analysis techniques.
“In this study, we have just scratched the surface of what is possible in the realm of machine-learned epidemiology. I like the analogy to the work of Dr. John Snow, the father of modern epidemiology, who in 1854 had to go door to door in Central London, asking people where they took their water from to find the source of a cholera outbreak. Today, we can use online data to make epidemiological observations in near real-time, with the potential for significantly improving public health in a timely and cost-efficient manner,” said Evgeniy Gabrilovich, senior staff research scientist at Google and a co-author of the study.
My friend Gord Surgeoner always said stay close to the producers, help farmers, and you’ll get somewhere.
And I did.
My friend Mike from Buffalo, who served overseas and then ended up coaching kids’ hockey with me in Brisbane 5 years ago would say, I don’t miss Buffalo.
Mike’s on the far left, and he’s used that face to, uh, motivate the kids, but he’s a softie like me, and moved an hour up north to the beaches.
Gord did a lot of consulting for the U.S. military on bugs, I’ve done my share on foodborne illness, but it’s not the same as serving.
Mike, keep on, keeping on (without the weapon, there’s gun control laws in Australia, and watch out for those sharks).
Mr Fadli Salleh, who was married with two young children, had been in critical condition in the intensive care unit (ICU) of Sengkang General Hospital (SKH) after he was one of 72 people who suffered gastroenteritis, allegedly after eating bento boxes prepared by Spize’s River Valley outlet for an event last Tuesday. (the raw egg looks like a Salmonella factory).
