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Roadmap for Today

Background Information for Workshop on Revision of USDA Economic Research Service Cost of Foodborne Illness Estimates Sandra Hoffmann U.S. Dept. of Agriculture, Economic Research Service March 29, 2018 Washington, DC.

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Roadmap for Today

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  1. Background Information for Workshop on Revision of USDA Economic Research Service Cost of Foodborne Illness EstimatesSandra HoffmannU.S. Dept. of Agriculture, Economic Research ServiceMarch 29, 2018Washington, DC The views expressed herein are those of the author and do not necessarily reflect the views of the Economic Research Service or U.S. Department of Agriculture.

  2. Roadmap for Today • Focus on current approach and scope • Brief discussion of vision for disease modeling revision

  3. ERS Cost Estimates of Foodborne Illness Data Product • Released late 2014 • Update plan for 2019/2020 • Update • Disease outcome trees • Economics • Medical treatment costs • Treatment of time • VSLs • Expand • To include all specified and unspecified pathogens in Scallan et al. (20011a, 2011b) • Chronic sequellae considered • Treatment of lost time

  4. Builds on a decade plus of research on cost of foodborne illness at ERS

  5. Based on more recent publications by Hoffmann, Batz and Morris • Expanded Scope • 4 pathogens  15 pathogens • Updated with New CDC Incidence Estimates • Mead et al. 1999  Scallan et al. 2011 • Updated for Economic Growth • 2009 dollars  2013 dollars • VSL updated for income growth and inflation Designed to Extend ERS CoI Calculator

  6. Overview of Content: Disease Modelling • Foundation: • Scallan et al. 2011. Foodborne illness acquired in the United States--major pathogens • Cases, hospitalizations, deaths, by pathogen • ERS estimates include cost for 15 of 31 major pathogens in Scallan et al. 2011 • over 95% of cases and hospitalizations, 98% of deaths • More detailed disease outcome trees than Scallan et al. 2011 • Severity of hospitalizations/complications • Duration of non-hospitalized and hospitalized cases • Estimate missing state-transition probabilities and calibrate for consistency with Scallan et al. 2011 • Additional consequences: • Major chronic sequelae • Congenital outcomes

  7. 2013 Estimates: Designed to Complement, Not Replace Existing ERS Estimates • Used ERS models for Listeria, STEC O157:H7, Campylobacter, and Salmonella • Date from 1996 on • Updated with Scallan et al. hospitalization and fatality rates • For 11 other pathogens develop new models • Uncertainty modeling limited to incidence uncertainty • Goal: consistency in treatment across pathogens

  8. Information Sources • Scallanet al. 2011. Major pathogens • National Inpatient Sample • FoodNetPopulation Survey (care seeking) • Peer-reviewed literature • Medical textbooks, reviews of clinical characteristics, and other literature for disease duration and symptoms where not included in NIS data • Analogy to other pathogens • E.g., mild diarrheal illness analogized to mild salmonellosis

  9. Evidentiary Criteria Used • Primary data where available and representative • High quality systematic reviews or meta-analysis used where available • Scope did not permit new systematic reviews • Used evidentiary criteria similar to that recommended for systematic reviews • Case control preferred to cohort studies • Nationally representative samples and active surveillance preferred to passive surveillance • Sample size • Representativeness relative to U.S. national population • U.S. studies preferred to non-U.S. studies of equal quality

  10. Example: Yersinia enterocolitica Rate of care seeing from FoodNet Population Survey NIS Data -- liklihood -- severity -- duration

  11. Example: Cryptosporidium spp. Scientific literature

  12. Disease Outcomes Vary in Complexity: Ex. Listeria monocytogenes (adult)

  13. Disease Outcomes Vary in Complexity: Ex. Listeria monocytogenes (congenital)

  14. Economic Burden Estimation • Non-hospitalized cases • Do or don’t seek care • FoodNet population survey • Pathogen-specific rates of bloody and non-bloody diarrhea from outbreak and clinical data + rate of care seeking for each • Lost wages, but not medications • Cost of outpatient visit • Hospitalized cases • NIS data, primary diagnosis using ICD-9-CM code • Lost wages of those ill (we’ll be expanding this) • Deaths • Scallan et al. 2011 mortality incidence and VSL

  15. Detailed Health State Descriptions

  16. Cost of Illness by Analogy • Hospital costs: • Done where NIS data had insufficient coverage • STEC non-O157 = STEC O157 • Cyclospora = Cryptosporidium perfringens • Vibrio other = Salmonella • Vibrio vulnificus = Listeria adjusted for ICU use rates • All pathogens: non-inpatient costs of hospitalized cases = those for salmonellosis • Outpatient: mild and moderate cases health care utilization and costs = those for salmonellosis

  17. Chronic Sequelae • Campylobacter (GBS), • STECs (ESRD) • Cryptosporidium (diarrhea relapse) • Listeria (congenital cases  disabilities) • Both disease outcome trees and costs based on prior studies

  18. Plan for 2020 Update • Update disease outcome trees and cost estimates for: • Listeria, STEC, Campylobacter, and Salmonella • Revise state transition probabilities, where needed • Update acute complications, where needed • Expand chronic sequellae, where appropriate • Expand pathogens covered • 31 pathogens from Scallan et al. 2011 major pathogens and incidence from Scallan et al. 2011 unknown pathogens • Other changes in scope?

  19. Pathogens > 95% of cases, hospitalizations, deaths Provides estimate of full economic burden Currently Included Plan to Include 15 pathogens currently included plus: Astrovirus Bacillus cereus Brucella spp. Clostridium botulinum Cryptosporidium spp. Cryptosporidium cayetanensis ETEC E. coli, diarrheagenic other than STEC and ETEC Giardia intestinalis Hepatitis A Mycobacterium bovis Rotavirus Salmonella entericaserotype Typhi Sapovirus Staphylococcus aureus Streptococcus spp., Group A Trichinellaspp. Vibrio cholerae, toxogenic Unspecified pathogens • 15 pathogens • FoodNet pathogens • Campylobacter • Cryptosporidium parvum • Cyclosporacayetanensis • STECO157 • Listeria monocytogenes • Salmonella enterica(non-typhoidal) • Shigella • Vibrio vulnificus • V. parahaemolyticus • V. other non-cholerae • Yersinia enterocolitica • plus • STEC non-O157 • Norovirus • Toxoplasma gondii

  20. Acute Complications Currently Included

  21. Chronic SequellaeCurrently Included

  22. Issues for Workshop Discussion (1) • Scope • Certainly parallel with CDC incidence • What changes are expected in CDC incidence estimates? • What would be the value of adding other hazards? • Allergens • Food toxins, e.g., seafood toxins • Food intolerances, e.g., lactose, gluten, fructose • Managing increase in scope • Are there pathogens that have analogous health outcomes? • What information sources should be used to support this decision? • What criteria should be used to decide on analogies? • How best to deal with foodborne illness of unidentified etiology • How to model severity and duration

  23. Issues for Workshop Discussion (2) • Changes in Acute Disease Outcomes • Where have advances in treatment or diagnostics led to shorter or less severe outcomes? • Have changes in the effectiveness of antibiotics led to longer or more severe outcomes? • Is it time yet to worry about modeling uncertainty about the effectiveness of antibiotic therapy? • Acute Complications • Are we missing any major complications? • Do any of the pathogens we’re adding have significant complications? • Chronic Sequelae (a major focus of the workshop) • What are we missing and how strong is the evidence to support inclusion? • Have treatments or diagnostics of any of the sequelae currently included reduced incidence, severity or duration?

  24. Questions? Discussion.

  25. Contact InformationSandra HoffmannUSDA Economic Research Serviceshoffmann@ers.usda.gov(202) 694-5354

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