Archiving of food samples from restaurants and caterers

Transcription

1 Archiving of food samples from restaurants and caterers Fumiko Kasuga National Institute of Health Sciences, Japan (National Institute of Infectious Diseases)

2 An example of data collection for Hazard Characterization Analysis of outbreak data in Japan

3 Hazard Characterization describes, Pathogen concerned serotypes, virulence, toxins, etc Population involved, susceptible, at risk Vehicle foods contaminated, protect pathogens against stomach acid, inactivate pathogens or inhibit proliferation Dose response: how likely to get ill?

4 Data for dose-response Pathogen dose ingested concentration in food food amount taken Attack rate (or P(infection), P(death), etc.) population exposed infected, ill, dead, etc.

5 Data source for dose-response Data source Pathogen Target population Food virulence dose range size components amount Human feeding data weak to mild controlled healthy adults controlled monotonous controlled Animal experiment data rather strong controlled difficult to convert controlled monotonous controlled Outbreak data various usually difficult to know from babies to elderly usually difficult to know diverse usually difficult to know * Outbreak data has limitations, needs assumptions when used, but reflects real-world events.

6 What we have experienced

7 Food and Agriculture Organization of the United Nations World Health Organization MRA 00/03 Joint FAO/WHO Expert Consultation on Risk Assessment of Microbiological Hazards in Foods FAO Headquarters, Rome, Italy July Preliminary Report - Hazard Identification and Hazard Characterization of Salmonella in broilers and eggs

8 Beta-Poisson model for Salmonella spp. derived using outbreak data 1.0 Attack Rate Otbrk-BP Log Dose In HC of MRA, both experimental and epidemiological information are used to develop dose-response relationship between pathogen dose ingested and the attack rate. This is an example of a dose-response of Salmonella infection from outbreak data. I would like to draw your attention not to beta-poisson curve, but to these individual data dots. As I marked here, more than half of the data was provided from Japan. When I first brought these data to the drafting group meeting, nobody knew that Japan had such amount of data sets. And we, the drafting group members, realized that there was unpublished data in the world that might provide important information for risk assessment at international level. So, I would like to talk first how it became possible to collect these data. And second, why those data were kept unrecognized.

9 Why was it possible?

10 Japanese Directive "Control measures against foodborne outbreaks" issued in march 1997 by Director General of Environmental Sanitation Bureau of the Japanese Ministry of Health and Welfare large scale cooking facilities more than 750 meals per day more than 300 dishes of a single menu at a time food saving 50 gram aliquots of each raw food material and cooked dish more than 2 weeks, lower than -20 C To the accumulation of those data, a recently released Directive has certainly contributed. This was issued in 1997 by MHW. According to this Directive, large scale cooking facilities that satisfy these criteria are advised to save 50 gram aliquots.for possible future examination at an incident. Although it is prepared for large scale kitchens, and though it is not mandatory, many smaller kitchens that have social responsibilities such as those in schools and hospitals have adopted this system. Especially in most school kitchens, new freezers have been equipped for the purpose of food saving since 1997, even though those freezers for lower than 20 degree cost expensive. This reflects our severe regret for a series of outbreaks of E. coli O157:H7 that deprived several childrens lives in the previous year.

11 Original purpose of food-storing system was to improve identification of vehicle food by microbiological examination.

12 Food-storing system improvement of causative food identification Coordination Quantitative data (concentration in food) co-operation with laboratories Kitchen owners cost supply Health centers epidemiological investigation Complete data set for Hazard Characterization Prefectural laboratories facility and technique capacity cost supply Exposed Ill Food amount taken This food saving system primarily improved identification of implicated food when outbreak took place, especially when causative agents had long latent periods. Nevertheless, we cannot overlook the fact that understanding by kitchen owners on expenses for the freezers and investigation technique of experts in local health centers are necessary to effective functioning of this system. For quantitative data that appeared in the dose-response figure, additional efforts were made at prefectural institutions for the enumeration of the pathogens. Certain level of facilities and technique for the examination, cost expenses were needed. For sufficient data set for HC, both activities shown here, and coordination of people in different organizations are essential.

13 How do we combine those data?

14 Outbreak reports Format, elements vary Essential elements are required to be included. Rapid reports by FAX or s Changeable, not confirmed Detail reports Several months later Administrative reports in Japanese

15 Outbreaks for which detail reports to MHLW are required (1) With more than 50 patients With less than 50 patients and with following characteristics Death involved Caused by imported food Occurred in more than two prefectures by single source

16 Outbreaks for which detail reports to MHLW are required (2) With less than 50 patients and with following characteristics (continued) Unique epidemiology, or complicated investigation and actions needed Caused by the following pathogens Yersinia enterocolitica O8 Campylobacter jejuni / coli Salmonella Enteritidis Enterohemorrhagic E. coli Clostridium botulinum

17 Analysis of outbreak data ( ) with Salmonella concentrations in implicated foods: In total 39 outbreak reports were collected, and they were divided into 5 categories upon settings.

18 Outbreaks occurred at schools Ages of pupils in an elementary school are 6 to 12. Most schools serve the same lunch menu to all of their pupils on a single day. All the pupils in the school are reasonably considered to be the exposed population in those outbreaks. The exposed population to the contaminated food is usually very large

19 Outbreaks occurred at schools Case Salmonella serotype Vehicle Bacterial Food amount Dose ingested Exposed Death Illness Attack rate No. (phage type) concentration intake (g) (CFU) i j 1SE *1 (PT *2 1) peanuts dressing <100 *3 80 < SE peanuts dressing 4.3 *4 80 * SE (PT 22) beef and bean sprouts with sesame dressing 40 * SE (PT 1) spinach with peanuts dressing 1.4 * *1 SE: Salmonella Enteritidis *2 PT: phage type *3 direct plate count, detection limit 100 CFU/g *4 MPN/g *5 direct plate count, CFU/g *6 food amount undefined in original report and assumed to be as same as Case No. 1

20 Outbreaks occurred at schools Symptoms *7 D S Fe V N C Fa H O Food condition prior to testing frozen for 9 days unknown Reported laboratory test methods *8 10 g sample was negative for SE, when 0.1 ml of 10 times diluted sample was plated on SS medium. SE was detected from 25 g sample that was incubated in EEM. 3 tube-mpn method using SBG medium, confirmed on DHL refrigerated 0.1 ml of 10 times diluted sample of 10 g plated on MLCB frozen for 7 days 10 g sample diluted to 1:10, then 5 tube-mpn method using EEM, SBG, SS, and DHL.. *7 abbreviation for symptoms: D; diarrhea, S; stomachache, Fe; fever, V; vomitting, N; nausea, C; chill, Fa; fatigue, H; headache, O; others *8 abbreviation for culture media: SBG; Selenite Brilliant Green, DHL; Deoxycholate Hydrogen Sulfide Lactose Agar, MLCB; Mannitol Lysine Crystal Violet Brilliant Green Agar, EEM; Enterobacteriaceae-Enrichment Mannitol, SS; Salmonella Shigella Agar

21 Outbreaks occurred at daycare centers The age of children is less than 1 up to 6 years old. In general, the size of daycare population is smaller than that of schools and each daycare has its own kitchen in most places. Therefore the exposed populations were smaller than those of school cases. Attack rates were higher than those in school outbreaks, which might reflect the susceptibility of the population.

22 Outbreaks occurred at daycare centers Case Salmonella serotype Vehicle Bacterial Food amount Dose ingested Exposed Death Illness Attack rate No. (phage type) *1 concentration intake (g) (CFU) i j 5 SE macaroni salad 1100 *2 40 * *7 0 3 * *7 6 SE chicken and eggs on rice 27 *2, * * * *8 7 SE egg salad 0.78 * SE (PT 1) scrambled eggs *3, *1 abbreviation used as same as Table 1 *2 direct plate count, CFU/g *3 MPN/g *4 bacterial concentration in stored raw egg mixture *5 food amount undefined in original report and assumed to be as same as Case No. 7 *6 mean of reported values *7 adult nurses *8 children under 6

23 Outbreaks occurred at hospitals Hospital inpatients are generally considered to be more susceptible to pathogens than the healthy, normal population. The attack rates in collected outbreaks, however, were not very high. the influence of concurrent medications including antibiotics??

24 Outbreaks occurred at hospitals Case Salmonella serotype Vehicle Bacterial Food amount Dose ingested Exposed Death Illness Attack rate No. (phage type) *1 concentration intake (g) (CFU) i j 9 SE (PT 1) tartar sauce <100 *2 36 < SE natto with raw eggs * SE (PT 4) grated yam diluted with soup 2400 * S.typhimurium grated yam diluted with soup 2300 *4 60 * S.typhimurium grated yam diluted with soup (with quail eggs) *3 60 * *1 abbreviation used as same as Table 1 *2 direct plate count, detection limit 100 CFU/g *3 direct plate count, CFU/g *4 MPN/g *5 food amount undefined in original report and assumed to be as same as Case No. 11

25 Outbreaks occurred at restaurants, hotels, caterers, and other business kitchens (20 outbreaks) Kitchens vary in size, the scale of outbreaks also differs. Amounts of ingested food were not always specified in the original reports, and assumptions were often made to estimate ingested dose of pathogens. The food storage conditions were also different among the outbreaks.

26 Outbreaks caused by confectionaries (6 outbreaks) Number of exposed people varies much in this group, from small outbreak with 5 cases to very large outbreak with more than one thousand.

27 Comparison of dose-response from outbreaks where food samples were kept frozen or not - effect of freezing food system

28 Relationship between the ingested bacterial dose and the attack rate Attack rate (%) Foods frozen Foods non-frozen Log bacterial dose ingested

29 Outbreaks where food portions were stored frozen Dose-response relationship in outbreaks where foods were frozen Attack rate (%) Log bacterial dose ingested

30 Outbreaks where food portions were not frozen Dose-response relationship in outbreaks where foods were not frozen Attack rate (%) Log bacterial dose ingested

31 Summary of my talk (1) Food-storing system Might be a good example of co-operation of management and assessment. Existing measures helped data collection for risk assessment. Very useful for developing dose-response models. Need to encourage local authorities to continue enumeration of causative microbes. May need additional mechanism, cost supply.

32 Summary of my talk (2) Outbreak reports Not always comprehensive, improvement of epidemiological investigation and report formatting needed. Case definition, recognition of foodborne outbreak is not systematically defined. Underestimation of reported cases. Many outbreak reports are useful. Translating to English under discussion. Current summary to be available.

33 Thank you! Co-workers: Masamitsu Hirota 1), Masamichi Wada 2), Toshihiko Yunokawa 3), Hajime Toyofuku 4), Masaki Shibatsuji 5), Hideshi Michino 5), Toshiaki Kuwasaki 5), Susumu Kumagai 6), Shigeki Yamamoto 1) 1) National Institute of Health Sciences 2) Nagano Research Institute for Health and Pollution 3) National Institute of Public Health 4) Food Safety Programme, World Health Organization 5) Ministry of Health, Labour and Welfare 6) The University of Tokyo Special advisors: Anna Lammerding, Aamir Fazil, Eric Ebel