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”.
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.
Nearly one dozen customers reached out to Pasha Mediterranean Grill in the 9300 block of Wurzbach Road and reported getting sick after dining at the restaurant, according to an inspection report from the San Antonio Metropolitan Health Department.
The restaurant’s managers also stated at least two employees had been sick with and reported symptoms of fever and diarrhea.
The manager told Metro Health that raw chicken and beef were discarded as a precaution after it was prepared by food handlers.
ABC News reports a Massachusetts restaurant has been shut down until further notice after nearly 40 people reported getting sick during a suspected salmonella outbreak.
The North Reading Board of Health posted an advisory saying the state Public Health Department had received complaints from 39 people who said they got sick at Kitty’s late last month. The state confirmed nine cases of salmonella and 30 suspected cases of salmonella.
The source of the outbreak was traced to the antipasto salad.
The restaurant was closed July 5 and allowed to reopen Friday after a sanitization but has since closed again.
Seattle’s King County public health is investigating an outbreak of Shiga toxin-producing E. coli (STEC) associated with I Love Sushi and Sodexo’s Café Mario at Nintendo of America campus in Redmond. Café Mario is operated by Sodexo and is not open to the public. At this time, the source of the illnesses has not been identified.
Since July 2, 2018, we have learned that four people (two King and two Snohomish County residents) have tested positive for STEC. All four consumed food from Café Mario in King County and work at the Nintendo of America campus in Redmond. Symptoms included abdominal cramps and bloody diarrhea. Illness onsets occurred during June 25–28, 2018. The four ill people consumed food from Café Mario on multiple days during June 18–22, 2018; one ill person also ate at I Love Sushi on June 19 and June 26, 2018, which is a food establishment that operates out of Café Mario once a week.\
On July 3, 2018, Public Health – Seattle & King County Environmental Health investigators visited Café Mario. Inspections were completed for both Café Mario and I Love Sushi.
At Café Mario, potential risk factors were identified and corrective actions discussed with Café Mario’s management, including inadequate hand washing practices and improper cold holding temperatures of food. At I Love Sushi, potential risk factors were also identified and discussed, including improper temperature storage of foods. Both restaurants were not open on July 4 due to it being a holiday.
On July 5, 2018, investigators closed Café Mario and the onsite I Love Sushi food services. Both restaurants will remain closed until approved to reopen by Public Health. Both food establishments will be required to complete a thorough cleaning and disinfection before reopening. Remaining food products are being held and environmental swabs were collected for laboratory testing. We are currently investigating whether any employees of these restaurants had a recent diarrheal illness. Investigators also reviewed with Café Mario’s management the Washington State Retail Food Code requirement that staff are not allowed to work while having vomiting or diarrhea.
Martin Elvery of Get West London reports that rat droppings hanging from the ceilings of rooms where fruit and vegetables were stored, products being repackaged and sold after being gnawed by mice and a cement mixer allegedly being used to mix marinated chicken are just some of the horrors Ealing’s food safety officers have uncovered over the past year.
The council carries out thorough, regular checks of all premises serving and selling food in the borough which are categorised for their level of risk on a sliding scale of A to E.
Whilst the vast majority – 82% this year – complied fully with food standards, they have had to take swift action to deal with a few. A report summarising them was presented to the council’s general purpose committee on Tuesday, June 26.
When officers visited food store rooms used to keep fruit and vegetables based at a store in The Green, in Southall, they were found to be riddled with rat droppings.
The report states rat and mouse droppings were found throughout at wall and floor junctions, and on high level shelving. They were also found hanging from the ceiling and on the door leading to the rear store room.
Tanveer Mann of Metro reports a kebab shop in Manchester was so filthy it had mouse droppings littered in every single room, a court has heard. The droppings were found in food preparation and customer areas at Go Shawarma, in Salford, as well as on the floor, on shelves, old work equipment, next to wrapped food and even alongside cleaning materials. Food waste was piled up inside the shop and rubbish bags outside. The situation was so grim the manager agreed to close the premises for two days to get on top of the problems, but then refused to be interviewed by council officers about the offence.
The conditions discovered by environtmental health inspectors at the Go Shawarma takeaway in Union Terrace, Salford. Virtually every room had mouse droppings.
Abdulraziq Ahmad, the owner of the takeaway on Bury Old Road, pleaded guilty to failing to adequately control pests, failing to have adequate provision for the disposal of waste and failing to have a documented food safety management system. He was fined a total of £2,250 and ordered to pay £1,000 costs and £75 victim surcharge when he appeared at Salford and Manchester magistrates court on June 19.