Population Forecasting with Alzheimer's Disease in Iran Using a System Dynamic Model

Vahidreza  Borhaninejad; Milad Ahmadi  Gohari; Yunes  Jahani; Saber Amirzadeh  Googhari; Nazanin  Jannati; Moghaddameh  Mirzaee

doi:10.18502/ijph.v54i5.18641

Vahidreza Borhaninejad Social Determinants of Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
Milad Ahmadi Gohari Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
Yunes Jahani Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran
Saber Amirzadeh Googhari School of Public Health, University of Saskatchewan, Saskatoon, SK, Canada
Nazanin Jannati Department of Community Health & Epidemiology, College of Medicine, University Saskatchewan, Saskatoon, SK, Canada
Moghaddameh Mirzaee Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran

DOI: https://doi.org/10.18502/ijph.v54i5.18641

Keywords: Alzheimer's disease (AD); Aging population; Older adults

Abstract

Background: The prevalence of Alzheimer's disease in Iran, attributed to the demographic shift towards an aging population, holds considerable importance. We aimed to estimate the prevalence and number of Alzheimer's disease in Iran by 2029.

Methods: Dynamic modeling techniques were employed to project the number of Alzheimer's disease (AD) among the elderly population in Iran by the year 2029. Two interconnected models were developed to facilitate this estimation. The initial model is a demographic model that captures the aging population's growth dynamics. The subsequent model, an AD evaluation model, that assess potential impacts on disease. This approach enables a comprehensive analysis of the factors influencing AD trends within the context of Iran's aging demographic.

Results: The results show the number of individuals aged over 60 is expected to rise from approximately 9.1 million in 2020 to around 13.7 million in 2029. As the older adult population grows, the number of AD is also anticipated to increase. The number of Alzheimer's patients is predicted to grow from about 464,400 in 2020 to roughly 729,900 by 2029.

Conclusion: Forecasting future trends in AD, especially in developing countries, is crucial for policymakers because of its growing impact on healthcare systems and economies globally. The findings of this study can aid in assessing the economic burdens associated with treating Alzheimer's patients, providing valuable insights for planning and resource allocation.