Modeling and prediction of age-specific mortality rates using the Lee-Carter model
Bibliographic Data
| ID | 5968644 |
|---|---|
| Authors | Evgenii L Borschuk (0000-0002-3617-5908, Orenburg State Medical Academy), Dmitrii N Begun (0000-0002-8920-6675, Orenburg State Medical Academy), Irina P Bolodurina (0000-0003-0096-2587, Orenburg State University), Larisa I Menshikova (0000-0002-1525-2003, Northern State Medical University), Svetlana V Kolesnik (0009-0009-3008-0308, Orenburg State University), Aislu N Duisembaeva (0000-0001-5762-4277, Orenburg State University) |
| Year | 2024 |
| Volume | 31 |
| Issue | 1 |
| Pages | 61-76 |
| Publication date | 2024-09-13 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Ekologiya Cheloveka (Human Ecology (JOURNAL) |
| Journal identifiers | ISSN: 1728-0869 • E-ISSN: 2949-1444 |
| Publisher | ECO-Vector LLC (PUBLISHER • RU) |
| DOI | 10.17816/humeco611099 |
| OpenAlex | W4401203621 |
| Language | EN |
| References cited | 12 |
BACKGROUND: High mortality remains one of the most significant health concerns in Russia. One of the priorities of the state policy is to reduce mortality rates among the working-age population and increase life expectancy. Predicting population mortality rates serves as a valuable tool for effectively allocating the available resources.AIM: To perform mathematical modeling and prediction of mortality rates of the population of the Orenburg region using the Lee-Carter model.MATERIAL AND METHODS: The age- and sex-specific mortality rates and the population size of the Orenburg region for the period 1991-2020 was used as a study base. The Lee-Carter method was applied to model and predict population mortality. By deriving key parameters, a random walk model with drift was developed, and an accuracy assessment was performed.RESULTS: The Lee-Carter model has been utilized to analyze the mortality rates of the male population in the Orenburg region. Through this modeling process, an accuracy rate of 87% was achieved, providing a reliable basis for long-term prediction. Mortality forecasts have been generated up to the year 2035, allowing for a comprehensive evaluation of future trends in the region.CONCLUSION: The analysis of the results indicates that the pandemic's impact on population mortality is expected to be short-term. In the upcoming years, the mortality rate of the male population in the Orenburg region is projected to continue decreasing
Geography · Life expectancy · Mortality rate · Population · Population growth · Population model · Population projection · Statistics · Demography · Global Health Care Issues · Health disparities and outcomes · Insurance, Mortality, Demography, Risk Management · Mathematics
| Highly cited | No |
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