1. Online foodborne illness surveillance and visitor data entry patterns: Building and strengthening public health infrastructure Holly Wethington, MS PhD Candidate, Sociology National Food Safety & Toxicology Center Michigan State University American Public Health Association Annual Meeting Washington DC November 2004

2. Foodborne Disease Epidemiology Changes in demographics, food preferences, food distribution systems, microbial adaptation Newly identified pathogens have emerged in the US Immunosuppressed population increasing $23 billion dollar annual cost (Hedberg, MacDonald, and Shapiro, 1994) 76 million illnesses, 320,000 hospitalizations, and 5,000 deaths annually (Mead et al., 1999) © Nature publishing group 2003

3. Current Foodborne Disease Surveillance 3 main purposes of surveillance ( Olsen et al., 2000): – –disease prevention and control, – –knowledge of disease causation, – –administrative guidance Limitations (Olsen et al. 2000): 1. 1. not all outbreaks are included (e.g. cruise, water) 2. 2. outbreaks not included if indirect route of transmission 3. 3. determining a causal food vehicle is problematic 4. 4. deficiency in standard criteria for classifying a death as foodborne disease related © Dennis Kunkel Microscopy, Inc.

4. Burden of Illness Pyramid. (CDC, FoodNet Data Sources) Burden of Illness The current system requires laboratory confirmation Underreporting remains a problem: – –Estimated 1-2% incident report rate (CD Summary, 1998) One MI survey found a mean 35 day interval between onset date and report completion: – –no opportunity for preventive efforts No surge capacity Culture-confirmed case Reported to Health Department/CDC Lab tests for organism Exposure in the general population Person becomes ill Person seeks care Specimen obtained

5. RUsick2 Foodborne Disease Forum We designed a syndromic surveillance system to augment existing laboratory-based surveillance Overcomes several limitations: – –Can increase rate of reporting so that small and medium sized outbreaks no longer escape detection – –Can hasten investigation so preventive measures can occur – –Capacity in event of large outbreak Original RUsick2 operated from November 2002 - October 2004 Enabled people who suspected food poisoning to come to our website, report their illness, and see if others became sick from the same food from the same place around the same time.

6. Several pages of data input Output reports towards the end: – –displayed percentages of other RUsick2 visitors that entered the same symptom or food item or food source – –kept personal information confidential from other RUsick2 visitors – –kept full names of food establishments confidential from other RUsick2 visitors – –output intended to motivate people coming to the web site Password given so visitors could return and modify their report or view reports at a later date RUsick2 Foodborne Disease Forum

7. Methods Pilot counties; nationwide Data input section (follows CDC’s Standard Foodborne Illness Questionnaire) The individual goes through several entry levels as shown on the right DATA COLLECTED 1: Case ID assigned 2: Personal Characteristics (age, gender) 3: County, city 4: Symptoms 5: Identifiers (name, email, phone) 6: Suspected Foods and Food Sources 7: Suspected Food(s) 8: Suspected Food Source(s) 9: Non-food Exposures 10: Four Day Food History 11: Food Sources 12: Contact Information (last name, address) 13: First Summary Report (tallies on other visitors who reported eating the same foods) 14: Source Matching (asked to match up which foods came from which food sources) 15: Match foods to food sources 16: Second Summary Report (can view reports) 17: Comparison Report (compare target period to comparison period)

8. Designed so people could leave at any point, different “options” for period of time spent on the website Nov. 1, 2002 - Dec. 1, 2003 Entry Level 4 (Symptoms & Onset date entered) 3,693 visitors total; 2,044 reached at least level 4

9. Results (restricted to Entry Level 4 and beyond; n=2,044) 18.3% from pilot counties 11.7% from MI, not pilot counties 70% outside MI 60% female Mean age = 36 years (SD=14.24y) Median age = 34 years 17% >50 years 6% >60 years

10. Results (restricted to Entry Level 4 and beyond; n=2,044) 13.5% sought medical attention Mean no. food items = 9.97 (SD=7.81) – –Greater number than telephone reports (mean = 4.4; n=87) Mean no. food sources = 1.81 (SD=1.24) – –Slightly greater number than telephone reports (mean = 1.65; n=87) 59%: email address 54%: at least one phone number 61%: willing to leave some sort of contact information

11. Discussion Gender breakdown consistent with literature Median age not surprising The percentage that sought healthcare was small Geographic location: mostly outside of MI Nearly 2/3 were willing to leave contact info Online food history reports were more complete than telephone reports

12. Limitations of RUsick2 Web-based – –Excluded those without web access Difficult to convince individuals to report foodborne illness. Difficult to identify clusters because low rate of participation due to minimal national advertising Online food histories more complete than telephone food histories Can save LHD time The pilot test found that it can increase the rate of reporting 4 fold in a geographic location if well advertised Strengths of RUsick2

13. The “new and improved” RUsick2 … a conduit to the health dept. reporting system a website for people to create their own report to be given to LHD gives instructions and links for visitors to contact their local health department does not offer any output reports helps people remember their food histories without any time pressure – –Visitors still given a password to modify their report

14. Online reporting to health departments has potential Electronic reporting lessens the amount of time LHD employees need to stay on the phone with individuals trying to remember what they ate Electronic reporting has better capacity in the event of a large outbreak Conclusions © 2000 Transportation Steering Committee. http://www.baltometro.org http://www.baltometro.org

15. Thank you!