BACKGROUND: New effective treatments for dementia are lacking, and early prevention focusing on risk factors of dementia is important. Non-pharmacological intervention therapies aimed at these factors may provide a valuable tool for reducing the incidence of dementia. This study focused on the development of a mathematical model to predict the number of individuals with neurodegenerative diseases, specifically Alzheimer's disease, Parkinson's disease, vascular dementia, and amyotrophic lateral sclerosis. Scenarios for non-pharmacological intervention therapies based on risk factor reduction were also assessed. The estimated total costs and potential cost savings from societal were included. METHODS: Based on demographic and financial data from the EU, a mathematical model was developed to predict the prevalence and resulting care costs of neurodegenerative diseases in the population. Each disease (Alzheimer's disease, Parkinson's disease, vascular dementia, and amyotrophic lateral sclerosis) used parameters that included prevalence, incidence, and death risk ratio, and the simulation is related to the age of the cohort and the disease stage. RESULTS: A replicable simulation for predicting the prevalence and resulting cost of care for neurodegenerative diseases in the population exhibited an increase in treatment costs from 267 billion EUR in 2021 to 528 billion EUR by 2050 in the EU alone. Scenarios related to the reduction of the prevalence of dementia by up to 20% per decade led to total discounted treatment cost savings of up to 558 billion EUR. CONCLUSION: The model indicates the magnitude of the financial burden placed on EU healthcare systems due to the growth in the population prevalence of neurodegenerative diseases in the coming decades. Lifestyle interventions based on reducing the most common risk factors could serve as a prevention strategy to reduce the incidence of dementia with substantial cost-savings potential. These findings could support the implementation of public health approaches throughout life to ultimately prevent premature mortality and promote a healthier and more active lifestyle in older individuals.

Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada 18071 Spain

Biomedical Research Centre University Hospital Hradec Kralove Hradec Kralove 50005 Czech Republic

Faculty of Informatics and Management University of Hradec Kralove Rokitanského 62 Hradec Kralove 50003 Czech Republic

Slovak University of Technology Bratislava 81237 Slovakia

References provided by Crossref.org