Changing Landscape of Foodborne Disease Arthur P. Liang, M.D., M. P. - - PowerPoint PPT Presentation

Changing Landscape of Foodborne Disease

Arthur P. Liang, M.D., M. P. H. Senior Advisor for Food Safety Division of Foodborne Waterborne & Environmental Diseases Centers for Disease Control & Prevention

CDC & States: The vital link

CDC provides the vital link between illness in people & the food safety systems of government agencies & food producers.

Disclosures

• Findings & conclusions in this presentation are

those of the author and do not necessarily represent the views of the Centers for Disease Control & Prevention

• Thank you to HPP for invitation
• Speaker reserves the right to say something

stupid, wrong or incredibly obvious

Executive Summary

• Genomics & Information Technology:

Accelerating pace of change

• Disease & Food surveillance finding a needle in a

haystack

• Food safety bar is being raised for ALL

More Class 1 Recalls(?)

Listeria Outbreaks & Incidence, 1983-2013

• No. outbreaks

Incidence (per million pop) Era Outbreaks per year Median cases per

• utbreak

Pre-PulseNet 0.3 69 Early PulseNet 2.3 11 Listeria Initiative 2.9 5.5

Listeria Outbreaks & Incidence, 1983-2014

• No. outbreaks

Incidence (per million pop) Era Outbreaks per year Median cases per

• utbreak

Pre-PulseNet 0.3 69 Early PulseNet 2.3 11 Listeria Initiative 2.9 5.5 WGS 8 4.5

Listeriosis Outbreaks & Incidence*, 1983-2015

• No. outbreaks

Incidence (per million pop)

WGS 7.5 4

*2015 incidence rate preliminary data from FoodNet

The bacteria and viruses that cause the most illnesses, hospitalizations, and deaths in the United States are:

• Salmonella
• Norovirus (Norwalk Virus)
• Campylobacter
• E. Coli
• Listeria
• Clostridium perfringens

https://www.foodsafety.gov/poisoning/causes/bacteriaviruses/

Accelerating pace of change…

• 1854 Era of Classical Epidemiology &

Microbiology 1920’s serotyping, 1940’s phage typing

• 1998 PulseNet Era
• 2014 Genome Sequencing Era

John Snow (1813-1858)

Era of Classical Epidemiology & Microbiology

How do we know it’s food? Outbreak investigation “church picnic” or “sore thumb”

• Large number of cases in one jurisdiction

− Detected by affected group − Local investigation − Local food handling error (s) − Local solution

Outbreak Detected by patients / their doctor

On January 12 A pediatric gastroenterologist notified the Washington State Dept of Health (WA DoH) of increase in emergency dept visits for bloody diarrhea & the hospitalization of 3 children with hemolytic uremic syndrome. January 15 No single exposure source from initial interviews Emergency Room & lab alerted for case finding

January 18

• 37 cases identified. 27 ate at same fast food chain A
• Cases named 13 different store locations of restaurant chain A

Chain has 66 restaurants in the Washington State. All received the same hamburger from the same distribution warehouse. “Controls” = No diarrhea in 2 wks, friend of a case, matched by neighborhood & age

Compare exposures of ill & well persons

Relative Risk = 1 No Association Relative Risk < 1 Negative Association Relative Risk > 1 Positive Association

Case - Control Study Calculate Relative Risk or Odds Ratio Ate Chain A hamburger Did not eat hamburger

Total

Sick 27 (73%) 10 37 Well 0 (0%) 16 16

matched odds ratio (mOR) = undefined; 95% confidence limit = 3.5 to ∞

“Local” food handling error:

Cook

• king

ing Temperatures peratures for r hamburger burger 1992 FDA – 140o F (60o C) Washington State 155o F (68o C) Cooking temperatures at implicated restaurants ±60o C, probably less 50 gm frozen hamburger patties, cooked 1 minute on each size, regardless of whether meat was still red or not

WA DoH Advisory: Outbreak likely linked to Restaurant Chain A hamburgers

“Local” Intervention Janua nuary y 18

January nuary 18, , 1993: 93: Voluntary luntary Recall call

• Restaurant Chain A Press Release: “…measures to

ensure menu items prepared in accordance with an advisory issued by the WA DoH.”

• Recall: ~250,000 hamburger patties

2 3 4

• E. Coli

i 0157 7 outbre reak ak linked nked to fast st-food

• od chain

in hamburg burgers, ers, Pacif ific ic Northwest thwest 1993 93 *

20 30 40 50 60 70 80 10 1 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 # of cases January

US & primary culture-confirmed cases = 333

first report Improved cooking temps Public alert

*cases by date of exposure who ate Chain A hamburger on a single day

Cases of E. coli by Date of Illness Onset October 5-18, 1999 N=11

Compare exposures of ill & well persons

Case - Control Study Calculate Relative Risk or Odds Ratio

Apple cider No apple cider

Total

Sick 10 (73%) 1 11 Well 0 (0%) 24 24

matched odds ratio (mOR) = undefined; unmatched P-value < 0.00001) Relative Risk > 1 Positive Association

“Local” Intervention October 12, 1999

• OSDH ordered Orchard A to
• discontinue unpasteurized apple cider production
• recalled the apple cider

Environmental Results Inspection of orchard & juice production site: no violations found − No dropped apples − Washed & brushed apples − Preservative added − Warning labels

PulseNet Era: circa 1996 - present

In 1995, the Hubble Space Telescope found distant galaxies and star clusters never seen before.

Pulsed-field gel electrophoresis (PFGE) makes “invisible” outbreaks visible

PulseNet, since 1996

• DNA “fingerprints” shared electronically
• Kept in national database at CDC

PulseNet Era: circa 1996 - present

• Small numbers of cases in many jurisdictions
• Detected by lab-based subtype surveillance
• Multistate / Country Multi-disciplinary investigation
• More challenging to investigate
• Higher stakes?
• Identifying “new” foods/ingredients

March 2

PulseNet identifies additional 7 cases in 6 states with an indistinguishable PFGE pattern

Outbreak Detection by Lab

March 1

NY State notified CDC of 4 cases Salmonella with indistinguishable PFGE patterns

Multi-state / National investigation

March 2

• Hypothesis generating questionnaire deployed

March 2

• First multi-state conference call
• Common exposures in early interviews:
• Chicken
• Seafood
• Fresh produce
• Japanese restaurant
• FDA notified & joins call

Outbreak Detection/Hypothesis Generation

March 1

Cluster Identified

March 8

 Exposure information points to seafood,

specifically sushi

 7/8 report seafood, 5/8 report sushi

March 2

Investigation Initiated

Restaurant-exposure Clusters

March 22 4th cluster of unrelated ill persons at sushi same restaurant in CT March 16 3rd cluster of unrelated ill persons ate sushi from same grocery store in WI March 22 5th cluster of unrelated ill persons ate sushi same restaurant in MD March 8 2 unrelated ill persons in TX ate the same Japanese restaurant March 13 Second cluster of unrelated ill persons at same Japanese restaurant in WI

= res estaur urant ant clus uster

Case-Meals Other Customers

“Spicy Tuna” 84% 37% (range:29 - 53%)

Epi i Ana naly lysis sis of

• f me

meal l rec eceipts eipts

March 29-April 9

• Compare ill patrons to well patrons from the several restaurants with

illness clusters

Well Patron Groups

• Orders from diners who ate at
• ne of the cluster restaurants
• Orders placed during the same

meal (lunch or dinner)

• Close to the date when the ill

person ate at the restaurant

FDA A Traceb eback ack

Seafood Importer/Supplier A

April il 11

Seafood Processor A.

April 13-14 FDA issued two Import Alerts for fresh & frozen tuna from Seafood Processor A. Seafood Importer/Supplier A recalls raw yellowfin tuna scrape

Three major pillars

1) Epidemiology – interviews & loyalty cards, case-control, observed vs expected

Data from interviews of ill persons, distribution of cases in person/place/time, results of analytic epidemiologic studies, the history of pathogen & past

• utbreaks

2) Traceback – lot codes, industry consultation

• f a suspected vehicle linked with ill persons to identify a common point where

contamination may have occurred & an assessment of the production facility at that common point

3) Laboratory – clinical, “DNA fingerprint,” food, environmental, results from testing of a cases, suspected vehicle or the production facility where contamination may have occurred

Higher epidemiologic “standard of proof”

Multi-disciplinary Evidence to implicate food

Multistate Outbreak of S Bareilly & S Nchanga Infections Associated with a Raw Scraped Ground Tuna Product, 2012

PulseNet increased the number of multistate foodborne outbreaks reported to CDC: 1973-2010

PulseNet begins

10 new food vehicles identified in multistate outbreaks, 2006 - 2009

1.

Bagged spinach, 2006

2.

Carrot juice, 2006

3.

Peanut butter, 2007 & 2009

4.

Broccoli powder on a snack food, 2007

5.

Pot pies, 2007

6.

Canned chili sauce, 2007

7.

Jalapeño & Serrano peppers, 2008

8.

White pepper, 2009

9.

Raw cookie dough, 2009

10.

Black & red pepper, 2009-10

National Foodborne Outbreak Surveillance System

13 new food vehicles identified in multistate outbreaks, 2006 - 2011

1.

Bagged spinach

2.

Carrot juice

3.

Peanut butter

4.

Broccoli powder on a snack food

5.

Dog food

6.

Pot pies

7.

Canned chili sauce

8.

Hot peppers

9.

White pepper

• 10. Raw cookie dough
• 11. Whole, raw papaya
• 12. Hazelnuts
• 13. Pine nuts

National Foodborne Outbreak Surveillance System

15 new food vehicles identified in multistate outbreaks, 2006 - 2012

1.

Bagged spinach

2.

Carrot juice

3.

Peanut butter

4.

Broccoli powder on a snack food

5.

Dog Food

6.

Pot pies/frozen meals

7.

Canned chili sauce

8.

Hot peppers

9.

Pepper

• 10. Raw cookie dough
• 11. Hazelnuts
• 12. Whole fresh papayas
• 13. Pine nuts
• 14. Kosher broiled chicken livers
• 15. Scraped tuna product

National Foodborne Outbreak Surveillance System

29 new vehicles identified in multistate outbreaks 2006 - 2015

National Foodborne Outbreak Surveillance System

1.

Bagged spinach

2.

Carrot juice

3.

Peanut butter

4.

Broccoli powder on a snack food

5.

Dog food

6.

Pot pies/frozen meals

7.

Canned hot dog chili sauce

8.

Fresh hot chili peppers

9.

Black pepper

• 10. Tahini sesame paste
• 11. Raw cookie dough
• 12. Aquatic water frogs
• 13. Fresh papaya
• 14. Frozen mamay fruit pulp
• 15. Bologna
• 16. In-shell hazelnuts
• 17. Pine nuts
• 18. Par-cooked, broiled chicken livers
• 19. Scraped tuna
• 20. Cashew cheese
• 21. Bearded dragons
• 22. Sugar cane juice
• 23. Sprouted chia seeds
• 24. Almond butter
• 25. Caramel apples
• 26. Sprouted nut butters
• 27. Dried mushrooms (in truffle oil puree)
• 28. Crested geckos
• 29. Wheat flour

32 new vehicles identified in multistate outbreaks since 2006 – May 2017

1.

Bagged spinach

2.

Carrot juice

3.

Peanut butter

4.

Broccoli powder on snack food

5.

Dog food

6.

Pot pies/frozen meals

7.

Canned hot dog chili sauce

8.

Fresh hot chili peppers

9.

Black pepper

10.

Tahini sesame paste

11.

Raw cookie dough

12.

Aquatic water frogs

13.

Fresh papaya

14.

Frozen mamay fruit pulp

15.

Bologna

16.

In-shell hazelnuts

17. Pine nuts 18. Par-cooked, broiled chicken livers 19. Scraped tuna 20. Cashew cheese 21. Bearded dragons 22. Sugar cane juice 23. Sprouted chia seeds 24. Almond butter 25. Caramel apples 26. Sprouted nut butters 27. Dried mushrooms (in truffle oil puree) 28. Crested geckos 29. Pistachios 30. Wheat flour 31. Powdered meal supplements 32. Soy nut butter

Genome Sequencing Era

WGS making the microbial “landscape” look like a different Universe Milky Way light vs radio telescope

Outbreak of Listerios is Linked to Recalled Stone Fruit

• July 2014 recall receives extensive media coverage
• Many inquiries to CDC FDA & health departments from concerned clinicians & public
• Many of whom had received automated telephone calls informing them that they had

purchased recalled fruit.

• During July 19–31, the CDC Listeria website received >500,000 page views
• Stone fruit isolates obtained from company

– 4 human isolates in 2014 with PFGE match – Patient 1 ate recalled nectarines & peaches – Patient 2 ate peaches, possibly recalled

• nes

– Patient 3 did not eat recalled fruits – Patient 4 no exposure information available

“Prediction is very difficult, esp. about the future.”

According to Yogi Berra, or Niels Bohr, or Albert Einstein, or Mark Twain, or Somebody

“Cross the river by feeling the stones.“

Deng Xiaoping 邓小平

• What will FDA / FSIS do? Swab-a-thons?
• What will CDC & state health departments do?
• Recall may trigger Outbreak investigation, instead of vice versa
• Will epidemiologists be responding more to a “food” signal?
• Long-tail, “never-ending” outbreak?
• “Outbreaks” are a “continuous variable”
• Definition of an outbreak changing?
• Greater than expected?

Source: Art Liang’s speculation

Future foodborne outbreaks more likely to be

• Dispersed in space: Multi-state, multi-national
• Dispersed in time: Multi-year
• Detected by sequence-based surveillance
• Detected as contaminated product first

Associated with

• Fresh produce & minimally processed foods
• Imported foods
• Novel food vehicles
• Novel routes & pathways of contamination

More dispersed & smaller: “low & slow”

Robert Tauxe, MD, Director, CDC Division of Foodborne, Waterborne & Environmental Diseases, September 20, 2017

Projected wgMLST database validation & deployment timeline

Apr 14 Oct 14 Apr 15 Oct 15 Apr 16 Oct 16 Apr 17 Oct 17 Apr 18 Oct 18 Apr 19

Development & internal validation Deployment Development & internal validation Deployment Development & internal validation Deployment Development & internal validation Deployment Development & internal validation External validation

← External validation ← External validation

Listeria monocytogenes Campylobacteraceae & Shiga toxin- producing

• E. coli (STEC)

Salmonella Vibrio, Shigella &

• ther diarrheagenic
• E. coli

Cronobacter & Yersinia

External validation →

← External validation

Food Microbiology “…in this place it takes all the running you can do, to keep in the same place.“

• Red Queen to Alice in Through the Looking Glass

Thank You!