Foodborne illness source attribution estimates for Salmonella, Escherichia coli O157 (E. coli O157), Listeria monocytogenes (Lm), and Campylobacter using outbreak surveillance data : report, Interagency Food Safety Analytics Collaboration (IFSAC) Project
Advanced Search
Select up to three search categories and corresponding keywords using the fields to the right. Refer to the Help section for more detailed instructions.

Search our Collections & Repository

All these words:

For very narrow results

This exact word or phrase:

When looking for a specific result

Any of these words:

Best used for discovery & interchangable words

None of these words:

Recommended to be used in conjunction with other fields

Language:

Dates

Publication Date Range:

to

Document Data

Title:

Document Type:

Library

Collection:

Series:

People

Author:

Help
Clear All

Query Builder

Query box

Help
Clear All

For additional assistance using the Custom Query please check out our Help Page

i

Foodborne illness source attribution estimates for Salmonella, Escherichia coli O157 (E. coli O157), Listeria monocytogenes (Lm), and Campylobacter using outbreak surveillance data : report, Interagency Food Safety Analytics Collaboration (IFSAC) Project

Filetype[PDF-1023.69 KB]


  • English

  • Details:

    • Description:
      Each year in the United States (U.S.), an estimated 9 million people get sick, 55,000 are hospitalized, and 1,000 die of foodborne disease caused by known pathogens (Scallan et al., 2011). Having these estimates help us understand the scope of the public health problem. However, to develop effective prevention measures, we need to better understand the types of foods contributing to the problem.

      Estimating the percentage of foodborne illnesses associated with specific foods is called foodborne illness source attribution. Determining the types of food that cause foodborne illnesses will not only guide efforts to improve food safety, but will also help identify opportunities to influence food safety policy. Regulatory agencies can use source attribution estimates to inform agency priorities, support development of regulations and performance standards and measures, and conduct risk assessments, among other activities.

      With the creation of the Interagency Food Safety Analytics Collaboration (IFSAC) in 2011, the U.S. Food and Drug Administration (FDA), the U.S. Department of Agriculture’s Food Safety and Inspection Service (USDA/FSIS), and Centers for Disease Control and Prevention (CDC) agreed to pursue shared food safety goals: to improve data and methods used to estimate foodborne illness source attribution, and to provide timely estimates of source attribution for 4 key foodborne pathogens, Salmonella, Escherichia coli O157 (E. coli O157), Listeria monocytogenes (Lm), and Campylobacter. These pathogens are considered a high priority to IFSAC because of the frequency and severity of illness they cause, and, most importantly, their susceptibility to targeted interventions. To accomplish these goals, IFSAC developed a suite of complementary projects to address different aspects of these goals and to support the overall IFSAC strategic vision. This report documents the culmination of the goal to provide harmonized foodborne illness source attribution estimates by developing, for the first time, a single, robust method to produce estimates that all 3 agencies may use in their food safety activities.

      Similar to a recently published study (Painter et al., 2013), we used outbreak surveillance data to estimate the percentages of domestically acquired, foodborne illnesses (both outbreak and sporadic) associated with consumption of foods assigned to predefined food categories (attribution percentages). However, our approach differs in several ways from the method used by Painter et al., and the approach and methods used to conduct this analysis rely on the findings and outputs from several IFSAC projects.* For example, we include the most recent outbreak data available (1998–2012) and attribute illnesses to food categories recently updated to align with those used by food safety regulatory agencies (Cole et al., 2013). In addition, our statistical model uses methods to smooth variation in outbreak size and decrease the influence of outliers. Our model also gives less weight to data from 1998 through 2007 than to the most recent 5‐years of data (2008–2012). To minimize uncertainty, we only use data from outbreaks in which the implicated food could be assigned to a single food category.

      This report provides a brief summary of our methods and results. It describes how we estimated attribution percentages for Salmonella, E. coli O157, Lm, and Campylobacter for each food category. Estimated attribution percentages also include a calculation of the 90% credibility interval. These improved estimates of foodborne illness source attribution derived from outbreak data can inform efforts to prioritize food safety initiatives, interventions, and policies for reducing foodborne illnesses. Additional details describing our methods will be discussed at the February 24, 2015 IFSAC public meeting.

      This report was written by members of the Interagency Food Safety Analytics Collaboration (IFSAC) and includes contributions from others in the Centers for Disease Control and Prevention (CDC), the U.S. Food and Drug Administration (FDA), and the U.S. Department of Agriculture’s Food Safety and Inspection Service (USDA/FSIS).

    • Document Type:
    • Place as Subject:
    • Main Document Checksum:
    • File Type:

    Supporting Files

    • No Additional Files

    More +

    You May Also Like

    Checkout today's featured content at stacks.cdc.gov