FoodCORE Update, New York City15th Annual PulseNet Meeting
7th Annual OutbreakNet MeetingSeptember 22, 2011September 22, 2011
Bureau of Communicable Disease
Public Health Laboratory
New York City Department of Health and Mental Hygiene
New York City Department of New York City Department of Health and Mental HygieneHealth and Mental Hygiene
• Population is 8 million
– 43% of NY State’s population
– 321 square miles
• Significant burden of illness due
to foodborne pathogens each year
– ~1300 salmonellosis, 80 STEC, and 40 listeriosis cases
• 22,000 food establishments
• 13,000 food retail establishments
– Supermarkets, delis “bodegas”, big box wholesale stores
NYC DOHMH Foodborne Disease Surveillance and
Outbreak Response
• Bureau of Communicable Disease (BCD)
• Public Health Laboratory (PHL)
– Environmental Microbiology Lab:
PulseNet Unit, Food Unit
– General (clinical) Microbiology Lab:
Enteric Unit, General Micro Unit
• Environmental Health
– Office of Environmental Investigations (OEI)
– EHS-Net
Prior to FoodCORE
• Surveillance for select pathogens such as STEC and Listeria is complete and timely (e.g. complete food histories and real time PFGE)
• Surveillance activities for salmonellosis (approximately • Surveillance activities for salmonellosis (approximately 1300 cases annually) was limited due to volume– Cases were not routinely interviewed
– Most Salmonella isolates were not routinely PFGE-typed (only 30-40% of isolates were subtyped and turn around time was >1 month)
FoodCORE in NYC
• 2009-2010– One of three sites selected for pilot year
(OutbreakNet Sentinel Sites)
– Hired a team of 6 students to assist with epi surveillance activitiessurveillance activities
– Hired one student 1 student to help improve data flow in the lab
• 2010-Present– Received additional funding to continue epi
activities and further enhance laboratory activities, 2010-present
FoodCORE NYC – Epi Activities
• Hired six students to assist with surveillance activities
– Recruit from three local MPH programs
– Work ~ 20 hours per week
– Work during business and after hours
• Began detailed hypothesis generating interviews of • Began detailed hypothesis generating interviews of salmonellosis cases
– Exclude patients in high risk settings as needed
– Open ended food history as well as ~100 specific exposures and food items
• Students provide surge capacity for cluster/outbreak investigations and assigned analytic projects
ENTER CASE PATIENT INFORMATION IN LINELIST
CHECK EACH MORNING FOR NEW CASES
RECEIVE REPORT(from Laboratory and/or provider)
Flow chart for salmonellosis case investigations
UPDATE LAB INFORMATION(Serotype, PFGE pattern names, cluster codes)
STANDARD OR LIMITED* INTERVIEW OF PATIENT(Exclude as appropriate)
DATA ENTERED INTO ACCESS
DATABASE
*A limited interview is conducted for the following patients: international travelers and infants who are not eating solid food.
Analyze Exposure Data
• Review exposures for patients identified as part of a cluster– Increase of a particular serotype
– PFGE clusters– PFGE clusters
– Multi-state clusters
• Conducting timely interviews– Improves patient recall to obtain better
exposure data
– Allows us to take more rapid public health actions (i.e. exclusions)
Data Entry and Management
• MS Access database for epi data
– Uses multiple subforms because database has so many variables
– Data entry takes approximately 15-20 minutes – Data entry takes approximately 15-20 minutes per survey
– Database can be fragile
– Need to update database and analysis programs as the questionnaire changes
Median Duration of Interviews, Sept 2009-Aug 2011
20
25
30
35
Med
ian
Tim
e (
Min
ute
s)
0
5
10
15
20
All Interviews (n=1360)
Interviews in English (n=942)
Interviews in a language other than
English (n=418)
Med
ian
Tim
e (
Language of Interview, Sept 2009-Aug 2011
N (%)
Interviews with language information 1588
English 1182 (74)
*Other languages include: Albanian, Arabic, Bengali, Creole, French, Hebrew, Russian, Polish, and Vietnamese
English 1182 (74)
Spanish 204 (13)
Mandarin 95 (6)
Cantonese 41 (3)
Other 66 (4)
Reason Patient Not Interviewed (n=391),Sept 2009-Aug 2011
Day and Time of Interview, Sept 2009-Aug 2011
N (%)
Total 733
Weekday, 9AM-5PM 559 (76)
Weeknight, 5PM-8PM 101 (14)
Sunday*, 4PM-8PM 73 (10)
* Sunday calls were discontinued in September 2010
Evaluation of Enhanced Salmonellosis Surveillance
• To quantify the difference between pre-enhanced and enhanced surveillance (funded by FoodCORE)
• Analyzed confirmed case reports of salmonellosis that are NYC residents– Pre-enhanced surveillance (N=1283): September 1, 2008
– August 31, 2009
– Enhanced surveillance (N=1293): September 1, 2009 –August 31, 2010
• Evaluated timeliness and completeness.
Cases Reported and Interviewed
Pre-Enhanced Surveillance
Enhanced Surveillance
Total Cases 1283 1293
Interviews Performed 92 (7%) 1071 (83%)
Median days from report date to interview date 11 3
Interviewed Cases with Complete Demographic or Clinical Data
Pre-Enhanced Surveillance
N (%)
Enhanced Surveillance
N (%)
Total Interviewed Cases 92 1071
Complete Demographic Information 52 (57) 1044 (97)
Complete Clinical Information 11 (12) 932 (87)
Interviewed Cases with Complete Food Exposure Information
Pre-Enhanced Surveillance
N (%)
Enhanced Surveillance
N (%)
Total Interviewed Cases 92 765*
Complete Food Exposure 21 (23) 306 (40)
* This excludes patients who traveled internationally during their incubation period, asymptomatic urine shedders, and infants not eating any solid foods.
30
35
40
45
Perc
en
t o
f R
ep
ort
s
Interviews with Missing Food Exposure Fields for Enhanced Surveillance (n=765)
Represents 85% of reports
0
5
10
15
20
25
0 5 10 15 20 25 30 35 40 45 50 55 60 65
Perc
en
t o
f R
ep
ort
s
Number of Missing Fields
High Risk Case-Patients Identified
• High Risk Cases: Daycare attendees or workers, foodhandlers, or healthcare workershealthcare workers
• Pre-enhanced surveillance identified 4 (0.3%) high risk cases
• Enhanced surveillance identified 40 (3%) high risk cases
Challenges
• Increased administrative work
• Overseeing the student scheduling
• High turn-over among student interviewers
– Recruiting, interviewing, hiring paperwork, and extensive training
Students must be supervised afterhours• Students must be supervised afterhours
– Offer comp time to full time staff to supervise afterhours
• Conduct quarterly in-person evaluations of students to provide feeback
• Creating and managing databases
– Implementing MAVEN expected to go live in Feb 2012
– Keeping up with data entry
• Continue enhanced surveillance activities
– Quarterly meetings involving foodborne staff and students to discuss ideas for improving surveillance
• Collecting and reporting metrics data
Ongoing FoodCORE Activities
• Collecting and reporting metrics data
– Evaluating the impact on detection and investigation outcomes of clusters and outbreaks
– Evaluating Listeria and STEC surveillance
• Regular cluster/outbreak meetings involving the students
• Collaborating with EHS-Net projects in NYC
FoodCORE – PulseNet
• 2009-2010– Developed MS Access database for PFGE
tracking (connections between LIMS and BioNumerics, reduce manual entry)BioNumerics, reduce manual entry)
• 2010-present– Hired 2 technologists
– Began PFGE-typing all Salmonella (except Enteritidis) starting in April 2011
NYC PHL and FoodCORE Activities to Date
• Increased # Salmonella PFGE-typed
• Shortened turn around time (TAT)
• Comparing 5 month time period in 2010 • Comparing 5 month time period in 2010 vs. 2011
Number of Salmonella
Isolates PFGE’dMedian TAT
2010 (Apr – Aug)
279 35 days
2011 (Apr – Aug)
373 18 days
NYC PHL and FoodCORE Proposed Activities
Enteric Lab • STEC: enhance capacity to rapidly identify non-
O157 serotypes (beyond “Top 6”, obtain complete E. coli Set I Antisera to ID in-house)E. coli Set I Antisera to ID in-house)
• Salmonella: initiate molecular serotyping procedure (to complement traditional serotyping, and reduce TAT)
NYC PHL and FoodCORE Proposed Activities
PulseNet Lab
• Continue enhanced PFGE-typing of Salmonella isolates
• Certify multiple staff for PFGE gels and analysis (Salmonella, STEC, Listeria)
• Improve PFGE cluster detection- Establish routines for querying PFGE data
- Collaborate with BCD epis to identify ‘meaningful’ clusters
FoodCORE Lab and Epi Collaboration
• Utilize secure DOH network drive to share PFGE, enteric, and epi data
• Install BioNumerics at BCD, train staff• Install BioNumerics at BCD, train staff
• Check local PFGE databases for pattern clusters, and identify local matches to multistate clusters (use PulseNet weekly cluster lists, bundle files)
• Confirm epi-detected clusters with PFGE
• Multiple data streams, not all connected or compatible: CDSS, Salmonella Epi MS Access, BioNumerics, PFGE MS Access, PHL LIMS (currently PowerLab)
FoodCORE Lab and Epi Challenges
• PHL adopting new LIMS = StarLIMS (next 6 months?)
• BCD implementing MAVEN in Feb 2012
• Hiring and purchasing delays
Accomplishments
• Increase the proportion of salmonellosis cases interviewed
• Dramatically improved the timeliness of our interviewsinterviews
• Obtaining more complete demographic, clinical, and exposure data
• Identifying more high risk cases so we can implement public health measures
Accomplishments
• Increased timeliness and the proportion of Salmonella isolates subtyped by PFGE
• Disseminate health education material to the • Disseminate health education material to the public
• Ability to detect and investigate clusters is improving
• Evaluating and improving surveillance
AcknowledgmentsCDC-OutbreakNet
APHL
USDA/FSIS
Bureau of Communicable Disease
• Sharon Balter
• Heather Hanson
• Cassandra Harrison
• HaeNa Waechter
Current Student Interns
• Keith Atchison
• Noelle Bessette
• Andrea Farnham
• Jillian Knorr
• Eric Peterson
• Chinh Tran
• Allan Uribe
• HaeNa Waechter
Public Health Laboratory
• Ludwin Chicaiza
• Tanya Geiz
• Dorothy Kamenshine
• Laura Kornstein
• Lillian Lee
• Jacob Paternostro
• Jennifer Rakeman
• Bun Tha
Past Student Interns
• Elena Blebea
• Jessica Burton
• Nicole Espinoza
• David Lee
• Crystal Martin
• Bryan Moy
• Kelsey Petrie
• Manessa Shaw
• Erica Simons
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