Methodological framework for World Health Organization estimates of the global burden of foodborne disease

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Methodological framework for World Health Organization estimates of the global burden of foodborne disease

Background The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Methodological Framework for World Health Organization Estimates of the Global Burden of Foodborne Disease

Background: The Foodborne Disease Burden Epidemiology Reference Group (FERG) was established in 2007 by the World Health Organization to estimate the global burden of foodborne diseases (FBDs). This paper describes the methodological framework developed by FERG's Computational Task Force to transform epidemiological information into FBD burden estimates. Methods and Findings: The global and regional burden of 31 FBDs was quantified, along with limited estimates for 5 other FBDs, using Disability-Adjusted Life Years in a hazard- and incidence-based approach. To accomplish this task, the following workflow was defined: outline of disease models and collection of epidemiological data; design and completion of a database template; development of an imputation model; identification of disability weights; probabilistic burden assessment; and estimating the proportion of the disease burden by each hazard that is attributable to exposure by food (i.e., source attribution). All computations were performed in R and the different functions were compiled in the R package 'FERG'. Traceability and transparency were ensured by sharing results and methods in an interactive way with all FERG members throughout the process. Conclusions: We developed a comprehensive framework for estimating the global burden of FBDs, in which methodological simplicity and transparency were key elements. All the tools developed have been made available and can be translated into a user-friendly national toolkit for studying and monitoring food safety at the local level

Computational disease model for <i>Mycobacterium bovis</i>.

<p>Rectangles define parent nodes, while rounded rectangles defined child nodes. Green nodes contribute Years Lived with Disability, and red nodes contribute Years of Life Lost. Nodes contributing to the incidence of the index disease are identified by a thick border. INC = country-specific incidence; PROB–local = country-specific probability.</p

Computational disease model for <i>Echinococcus granulosus</i>.

<p>Rectangles define parent nodes, while rounded rectangles defined child nodes. Grey nodes do not contribute directly to the DALYs, green nodes contribute YLDs, and red nodes contribute YLLs. Nodes contributing to the incidence of the index disease are identified by a thick border. INC = country-specific incidence; PROB–global = probability applied to all countries; CE = cystic echinococcosis; CNS = central nervous system.</p

Computational Task Force workflow.

<p>CTF = Computational Task Force; YLDs = Years Lived with Disability; YLLs = Years of Life Lost due to mortality; DALYs = Disability-Adjusted Life Years; UN WPP 2012 = United Nations World Population Prospects 2012 Revision.</p

World Health Organization (WHO) Member States by subregion.

<p>World Health Organization (WHO) Member States by subregion.</p

FERG hazards, causally related health states and corresponding disability weights (DWs).

<p>Details on the derivation of the DWs are provided in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0142498#pone.0142498.s006" target="_blank">S2 Table</a>.</p

Number of imputed hazards by WHO member state.

<p>Number of imputed hazards by WHO member state.</p