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Global Health Observatory
Table
Indicator name:
Foodborne disability-adjusted life years per 100 000 population (mean, 95% uncertainty interval)
Short name:
Foodborne disability-adjusted life years per 100 000
Topic:
Food safety
Definition:
Rate of disability-adjusted life years per 100 000 population attributed to foodborne hazards
Associated terms:
Foodborne diseases, foodborne illness, illness, food safety, burden of disease, foodborne disease burden epidemiology reference group, FERG.
Disaggregation:
Data is disaggregated by hazard (all hazards; diarrhoeal hazards; enteric intoxications, chemical hazards; invasive disease hazards) and age (all ages; less than 5 years of age; 5 years of age and over).
Method of measurement

Several data sources are used to measure each hazard in this metadata category, including systematic reviews complemented with other literature sources, surveillance data and expert inputs.

For more details, please consult the following publication:

Devleesschauwer B, Vaes L, Fernandez K, Borghi E, Cao B, Fastl C, et al. Computational framework for the World Health Organization estimates of the global, regional and national burden of foodborne diseases 2026 edition; (https://doi.org/10.64898/2026.05.13.26353030) [Preprint].

Method of estimation:
Burden of disease estimation was approached using hazard-based and incidence-based methods. The hazard-based estimates encompassed all related sequelae specific to the hazard, and the incidence-based approach considered either current or past events to calculate Disability-Adjusted Life Years (DALYs) and their Years Lived with Disability (YLD) component. Incidence-based methods were preferred for foodborne disease studies being more sensitive to current epidemiological trends, consistency with hazard-based approaches and estimation of Years of Life Lost (YLLs). Prevalence-based methods were used when incidence data was lacking, estimating incidence based on prevalence and disease duration.
Method of estimation of global and regional aggregates:
Probabilistic burden assessment. The DALY calculations were implemented in a probabilistic framework, using 1000 Monte Carlo simulations (or 500 for the hazards where IHME/GBD envelopes were used). The calculation process yielded estimates of incidence, mortality, YLD, YLL, and DALY, by hazard, age group, sex, country, and year. Estimates are produced as absolute numbers, rates per 100 000 population, and rates per case. Probability distributions were summarized by their mean and 95% uncertainty interval. Regional, global and hazard totals were obtained by aggregating country-level estimates within each Monte Carlo iteration. This approach preserved the full uncertainty structure during aggregation, rather than summing only point estimates.
Preferred data sources:
Etiology-specific incidence data from public health registries or other sources.
Medical care-seeking behaviour, testing and diagnostic practices from cross-sectional surveys of the target population.
Laboratory testing and reporting practices from national or regional health laboratories and registries, scientific studies and reports, or through direct contact with relevant national experts.
Population and life expectancy data by country, year, age and sex were sourced from the United Nations World Population Prospects.
Unit of Measure:
Rate of disability-adjusted life years per 100 000 population
Expected frequency of data dissemination:
Following the Seventy-third World Health Assembly resolution on “Strengthening efforts on food safety” (WHA73.5), WHO will regularly monitor and provide updated estimates to the GHO that include national, regional and global level estimates of foodborne disease incidence, mortality and disease burden in terms of DALYs.
Contact person email:
fbd-burden@who.int
Name:
Ms Yuki Minato
IMRID:
3728
Limitations:
  • Complex, non‑standardized modelling due to multiple hazards, heterogeneous data sources, and hazard‑specific methods
  • Parasite‑specific challenges arising from highly focal transmission patterns and variable symptom presentation
  • Under‑ascertainment of infections caused by differing proportions of symptomatic vs. asymptomatic cases
  • Higher uncertainty for chemical hazards because estimates rely heavily on comparative risk assessment
  • Persistent data gaps, especially in low‑ and middle‑income countries, leading to extensive imputation
  • High heterogeneity in available studies in design, diagnostics, case definitions, and geographic coverage
  • Residual biases from underreporting, misclassification, and publication bias despite standardized review protocols
  • Limited ability to produce detailed breakdowns such as time trends, age/sex distributions, or age‑standardized rates
  • Wide uncertainty intervals for several hazards due to sparse or inconsistent data.
  • Non‑exhaustive hazard coverage with emerging hazards (e.g., pesticides, Angiostrongylus spp., hepatitis E virus) not yet included
  • No adjustments made for comorbidities
  • No explicit modelling of global drivers such as COVID‑19, antimicrobial resistance, or climate change

Despite these limitations, the study provides valuable insights into the global burden of foodborne diseases and highlights the need for a sustainable, multisectoral response to reduce the burden of foodborne diseases globally.

Links:
Computational framework for the World Health Organization estimates of the global, regional and national burden of foodborne diseases 2026 edition
Indicator Metadata Registry List
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