1. Food and Non-Food Exposures Associated with Enteric Foodborne Illness in Rural Texas—An Exploratory Surveillance Study, 2013-2014 Joseph (Greg) Rosen Public Health Associate Office for State, Tribal, Local and Territorial Support Centers for Disease Control and Prevention PHAP/PHPS Summer Seminar June 1 – 5, 2015 Centers for Disease Control and Prevention Office for State, Tribal, Local and Territorial Support

2. What Makes “Food Poisoning” Relevant to Public Health?  9 million infections annually in the U.S.  55,000 hospitalizations & 1,000 fatalities  $100M in preventable healthcare costs  10,000 cases reported in Texas (2013) 1 Interagency Food Safety Analytics Collaboration (IFSAC) Project, Foodborne Illness Source Attribution Estimates for Salmonella, Escherichia coli 0147 (E. Coli 0157), Listeria monocytogenes (Lm), and Campylobacter using Outbreak Surveillance Data 2 Case counts and incidence rates in Texas, 2001-2013. Texas Department of State Health Services.

3.  Bacterial organisms residing in the human and animal intestines  Modality of transmission  Contaminated food/water sources; infected animals  Human-to-human: fecal-oral  Prevention required at the individual and systemic levels Background: Enteric Pathogens – What Are They? E. coli O157:H7, associated with ground beef Salmonella Newport, implicated pathogen in an outbreak associated with alfalfa sprouts (2010)

4.  Source attribution difficult for sporadic cases  Food consumption and lifestyle behavior patterns vary across Texas communities  Understand healthcare- seeking behaviors in the population  Antimicrobial-resistant pathogens Background: Impetus for Risk Factor Analysis in Rural Texas Courtesy of Texas Department of State Health Services, Center for Health Statistics

5.  Identified case records of Campylobacter, Salmonella, and Shigella in Region 6/5 South (2013-2014)  Used the Texas electronic disease surveillance system  Interview form prompted 7- day exposure history from illness onset date Methodology: Prospective Study Design

6.  Attempted structured telephone interviews with case-patients  Excluded outbreak- associated case-patients  Calculated demographic and risk factor frequencies Methodology: Inclusion/Exclusion Metrics in Study Population Campylobacter, Salmonella, or Shigella pathogen identified? Resides in one of the seven Region 6/5 South surveillance counties? Case-patient associated with an outbreak? Contact to administer food history/exposure questionnaire Excluded from analysis NO YES

7.  139/240 completed interviews  Age ranged from 0-91 years (median=9)  Majority were non- Hispanic Whites (N=55)  Females constituted 56% Results: Demographic Characteristics of Enteric Foodborne Illness Case-Patients

8. Results: Self-Reported Risk Factors among Case- Patients, Region 6/5 South, 2013-2014 (N=139) Risk FactorCases (%) Non-Food Exposures Contact with household pets69 (50) Exposure to livestock or poultry36 (26) Drinking water from a private well35 (25) Ill close contact(s)23 (17) Recreational water exposure (pool, lake, water fountain) 17 (12) Food Exposures Consume any beef products62 (45) Fresh fruit consumption58 (42) Consume any poultry (chicken, turkey) products 54 (39) Fresh vegetable consumption49 (35) Pork consumption28 (20) Handle any raw meat15 (11) Consume food with raw or undercooked eggs 14 (10)  Salmonella (55%) most frequently reported pathogen  Mean symptom duration = 9 days  26% hospitalized (50% for > 65+)

9. Results: Risk or Associated Factors among Case- Patients, by Age Group, 2013-2014 (N=139) *Difference statistically significant, as determined by a p-value < 0.05 using a Mantel-Haenszel chi-square test. ^Difference not statistically significant, as determined by a p-value > 0.05 using a Mantel-Haenszel chi-square test, due to small sample size.

10. Risk Factors among Case-Patients, by Sex, Region 6/5 South, 2013-2014 (N=139) ^Difference not statistically significant, as determined by a p-value > 0.05 using a Mantel-Haenszel chi-square test, due to small sample size.

11.  Small sample size  Dietary recall biases  No measurement of indicators of food safety, hand hygiene, or healthcare accessibility  No distinction between risky and non-risk food consumption patterns Limitations

12.  Case-patients in rural Texas reporting high frequencies of non-food related risk factors  Healthcare election bias may account for high concentration of < 18  Examine healthcare- seeking behaviors and care access  Prevention tailored to different age groups  Emphasis on animal safety and hand hygiene Conclusions and Recommendations

13. For more information, please contact CDC’s Office for State, Tribal, Local and Territorial Support 4770 Buford Highway NE, Mailstop E-70, Atlanta, GA 30341 Telephone: 1-800-CDC-INFO (232-4636)/TTY: 1-888-232-6348 E-mail: OSTLTSfeedback@cdc.govWeb: http://www.cdc.gov/stltpublichealthOSTLTSfeedback@cdc.govhttp://www.cdc.gov/stltpublichealth The findings and conclusions in this presentation are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Questions or Comments? Joseph (Greg) Rosen ypp2@cdc.gov Greg.Rosen@dshs.state.tx.us Centers for Disease Control and Prevention Office for State, Tribal, Local and Territorial Support