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RAC Risk Ranking Models Workshop

RAC Risk Ranking Models Workshop. August 18, 2005. Consequence Management System. Purpose of the CMS. To help quantify the potential consequences of food safety and defense events. Estimate the impact on: Consumers Public Health infrastructure Business, government and the public

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RAC Risk Ranking Models Workshop

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  1. RAC Risk Ranking Models Workshop August 18, 2005 Consequence Management System

  2. Purpose of the CMS To help quantify the potential consequences of food safety and defense events • Estimate the impact on: • Consumers • Public Health infrastructure • Business, government and the public • Alternative interventions • Facilities (containment and remediation) • Training and education

  3. What policy issues does CMS address? • Vulnerable agent/food combinations • Helps identify which combinations of agent/food have the largest potential for scope and scale of outbreak • Critical control points • Helps identify where to focus resources in the food distribution/endpoint chain for most benefit • Cost effectiveness • Helps weigh the cost/benefit of various policy and intervention decisions • Time frames • Illustrates the time frames that would maximize the effectiveness of policies and actions

  4. How is CMS structured? Simulates the evolution and impact of an entire food event temporally and geographically • Data-centric - reflect real data and real prior incidents • Visual - quickly visualize and assess the impact of decisions • Flexible - accommodate all reasonable scenarios • Practical – operate when some attributes are unknown or imprecise • Extensible – facilitate easy enhancement to include improved data and models as they become available

  5. Example of use of CMS CMS Demonstration

  6. Software platform Windows 2000/XP Implemented as original program code. All required components are included with CMS installation

  7. What does CMS deliver ? . . . • “What-If” scenario planning • Quantify vulnerabilities • Assist in priority setting • Facilitate allocation of resources • Support decision making • Consequence assessment • Morbidity, mortality, economic impact • All impacted constituencies (consumers, general public, health care industry, global and domestic food industries, government) • Training • Food system, agents, crisis management • Table top exercises

  8. . . . and to whom? • Federal agencies • FDA, DHS, CDC, USDA, EPA • State and local agencies • Departments of Public Health, Agriculture, Homeland Security, Emergency Response, First responders • Industries expressing interest • Grower/shippers, manufacturers, suppliers, transportation, wholesalers, distributors, retail/foodservice operators

  9. Public Health outcome metrics • User selectable • Supports any metric that: • allows interpolation between symptom levels • correlates with impact metrics • allows evaluation of economic costs (desirable) • Example: • Mild Illness (no time off work) • Moderate Illness (1 – 5 days off work) • Severe Illness (6 + days off work, no hospitalization) • Short Term Hospital Admission (1 - 5 days) • Long Term Hospital Admission (6+ days) • Mortality

  10. Economic outcome metrics • User selectable • Supports any outcome metric that: • allows interpolation between impact levels • has supporting data • Examples: • QALY • DALY • Dollars

  11. How transparent is CMS? • All data are anonymized and viewable with provided Data Entry/Viewing module • Data Entry module • All statistical distributions are viewable with provided code-shared statistics module • Statistics Module • Complex processes may be modeled via external modeling systems: • Where external model is compatible (API) and appropriate (real-time speed) they may be called directly • Outputs of incompatible external models (e.g. Analytica) are recoded as inputs for the CMS

  12. What data does CMS need? (Year 1) Food Sourcing Deterministic information Interviews with producers Trade associations, USDA/ERS data. Food Distribution Deterministic information Industry provided data Food Processing Deterministic informationInterviews, Literature Review Agent Characteristics Deterministic information Expert Panel ,Literature Review Food Handling Models Literature ReviewFood Handling Practices Model Agent-Food Interaction Models E. Todd model - E. coli on lettuce Food Consumption Deterministic information ERS NHANES II data from USDA NPD data on lettuce consumption Secondary Transmission Expert Elicitation Expert elicitation with FDA, CDC Dose Response Expert Elicitation Expert elicitation with FDA. CDC NCFPD PH Response and Epi Team Disease Progression Expert Elicitation Expert elicitation with FDA, CDC NCFPD Model Patient ResponseExpert Elicitation Expert elicitation from CDC NCFPD PH Response and Epi Team Health System Response Expert Elicitation/Model Expert elicitation with FDA/CDC, State and local PHD; NCFPD Model Intervention Impact Expert Elicitation/ModelExpert Elicitation with FCFPD and Industry BT Safety designed system Data Repository Tabs Literature Review Event Impact Model ERS code for Cost Calculator (Salmonella) NCFPD Economics Team

  13. . . . Data Gaps? (Year 1) Food Sourcing Food Distribution Food Processing Food Handling Agent Characteristics Agent-Food Interaction Food Consumption Secondary Transmission Dose Response Disease Progression Patient Response Health System Response Intervention Impact Event Impact Data Repository

  14. How do you compensate for missing data? • Hierarchically structured approach • Internet search • Literature review • Expert elicitation • Original data collection/research • Ongoing dialog with experts in relevant fields

  15. We gratefully acknowledge funding by the following organizations:

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