Belgian National Burden of Disease Study (BeBOD)

What are the most important diseases in Belgium? Which risk factors contribute most to the overall disease burden? How is the burden of disease evolving over time, and how does it differ across the country? In a context of increasing budgetary constraints, a precise answer to these basic questions is more than ever necessary to inform policy-making.

To inform healthcare planning and address future needs, Sciensano is conducting projections on the burden of disease in Belgium. By generating estimates of future prevalence and Years Lived with Disability (YLD) across different age groups, sexes, and regions, we can anticipate how patterns of morbidity may evolve over time. YLD projections quantify the impact of various diseases in terms of years lived with disability, while prevalence estimates indicate the number of individuals who may be affected. Together, these metrics provide a forward-looking assessment of health challenges likely to affect Belgium, helping to prioritize interventions and allocate resources more effectively.

For more info, please visit the BeBOD project page or read the BeBOD protocol.

  Other BeBOD visualisation tools

Estimates of the fatal and non-fatal burden of 38 key diseases

Estimates of the fatal burden of 131 causes of death

Estimates of the non-fatal burden of 57 cancer sites

Estimates of the risk factor attributable burden

BeBOD estimates of the burden of disease

Years Lived with Disability (YLDs)

YLDs quantify the morbidity impact of diseases. They are calculated as the product of the number of prevalent cases with the disability weight (DW), averaged over the different health states of the disease. The DWs reflect the relative reduction in quality of life, on a scale from 0 (perfect health) to 1 (death). We calculate YLDs using the Global Burden of Disease DWs.

Number of prevalent cases

The number of prevalent cases for each disease was calculated based on a variety of Belgian data sources, including the Belgian Cancer Registry, the Intermutualistic Agency, the Belgian Health Interview Survey, the Hospital Discharge Data, the Intego general practice sentinel network, and the European kidney registry (ERA-EDTA).

Projections

To produce these projections, we used a Bayesian modeling approach via Integrated Nested Laplace Approximation (INLA) to analyze past trends and extend them into future estimates. An automated model selection process identified the best-fitting model for each disease, ensuring robust and accurate projections. Additionally, population projections from the Federal Planning Bureau were incorporated to account for expected changes in population structure, allowing us to anticipate shifts in disease prevalence and Years Lived with Disability (YLD) across age, sex, and regional categories. More details on the applied methodology can be found in the BeBOD projection protocol.

Explore our estimates

  Slope

Explore ranks in cases and years lived with disabilities by age, sex, region, and year.

  Trends

Explore trends in cases and years lived with disabilities by age, sex, and region.

  Results

Explore and download our estimates of cases and years lived with disabilities.

Download all estimates

All estimates can be downloaded in RDS format via Zenodo:

Citation

Robby De Pauw & Brecht Devleesschauwer. (2024). BeBOD projections of prevalence, and years lived with disability for 33 causes, 2013-2040 (v2024-12-12) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14363505

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.