Global and regional projections of the economic burden of Alzheimer's disease and related dementias from 2019 to 2050: A value of statistical life approach
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Background: The burden of Alzheimer's disease and related dementias (ADRDs) is expected to grow rapidly with population aging, especially in low- and middle-income countries, in the next few decades. We used a willingness-to-pay approach to project the global, regional, and national economic burden of ADRDs from 2019 to 2050 under status quo. Methods: We projected age group and country-specific disability-adjusted life years (DALYs) lost to ADRDs in future years based on historical growth in disease burden and available population projections. We used country-specific extrapolations of the value of a statistical life (VSL) year and its future projections based on historical income growth to estimate the economic burden - measured in terms of the value of lost DALYs - of ADRDs. A probabilistic uncertainty analysis was used to calculate point estimates and 95% uncertainty bounds of the economic burden. Findings: In 2019, the global VSL-based economic burden of ADRDs was an estimated $2.8 trillion. The burden was projected to increase to $4.7 trillion (95% uncertainty bound: $4 trillion-$5.5 trillion) in 2030, $8.5 trillion ($6.8 trillion-$10.8 trillion) in 2040, and $16.9 trillion ($11.3 trillion-$27.3 trillion) in 2050. Low- and middle-income countries (LMICs) would account for 65% of the global VSL-based economic burden in 2050, as compared with only 18% in 2019. Within LMICs, upper-middle income countries would carry the largest VSL-based economic burden by 2050 (92% of LMICs burden and 60% of global burden). Interpretation: ADRDs have a large and inequitable projected future VSL-based economic burden. Funding: The Davos Alzheimer's Collaborative.
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Nandi and colleagues estimated an economic burden of dementia of $2.8 trillion in 2019.
“Nandi and colleagues estimated global costs of dementia and found an economic burden of $2.8 trillion in 2019.9”
From Societal Costs of Dementia: 204 Countries, 2000–2019 (2024) · cites this paper as [9]
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- Authors
- Nandi, A., Counts, N., Chen, S., Seligman, B., Tortorice, D., Vigo, D., & Bloom, D. E.
- Affiliations
- Population Council (US)
- Albert Einstein College of Medicine (US)
- Heidelberg University (DE)
- University of California, Los Angeles (US)
- College of the Holy Cross (US)
- University of British Columbia (CA)
- Harvard University (US)
- Corresponding author
- Nandi, Arindam
- Venue
- eClinicalMedicine
- Publisher
- Elsevier BV
- Published
- 2022-09
- Volume
- 51
- Pages
- 101580
- ISSN
- 2589-5370 (ISSN-L)
- PMC
- PMC9310134
- OpenAlex
- W4286696753
- Cited by
- 402
- References
- 38
- Citations by year
- 2026: 91 · 2025: 166 · 2024: 95 · 2023: 45 · 2022: 5
- FWCI
- 50.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- EClinicalMedicine (publishedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Pfizer
- Merck
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Keywords
- Alzheimer's disease and related dementias, economic burden, value of a statistical life, disability-adjusted life years, population aging, low- and middle-income countries, health disparities, future projections, willingness to pay, global burden of disease
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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