Literature DB >> 36103457

Sensitivity analysis on the declining population in Japan: Effects of prefecture-specific fertility and interregional migration.

Ryo Oizumi1, Hisashi Inaba2, Takenori Takada3, Youichi Enatsu4, Kensaku Kinjo5.   

Abstract

Japan has been facing a population decline since 2010 due to low birth rates, interregional migration, and regional traits. In this study, we modeled the demographic dynamics of Japan using a transition matrix model. Then, from the mathematical structure of the model, we quantitatively evaluated the domestic factors of population decline. To achieve this, we constructed a multi-regional Leslie matrix model and developed a method for representing the reproductive value and stable age distribution using matrix entries. Our method enabled us to interpret the mathematical indices using the genealogies of the migration history of individuals and their ancestors. Furthermore, by combining our method with sensitivity analysis, we analyzed the effect of region-specific fertility rates and interregional migration rates on the population decline in Japan. We found that the sensitivity of the population growth rate to the migration rate from urban areas with large populations to prefectures with high fertility rates was greatest for people aged under 30. In addition, compared to other areas, the fertility rates of urban areas exhibited higher sensitivity for people aged over 30. Because this feature is robust in comparison with those in 2010 and 2015, it can be said to be a unique structure in Japan in recent years. We also established a method to represent the reproductive value and stable age distribution in an irreducible non-negative matrix population model by using the matrix entries. Furthermore, we show the effects of fertility and migration rates numerically in urban and non-urban areas on the population growth rates for each age group in a society with a declining population.

Entities:  

Mesh:

Year:  2022        PMID: 36103457      PMCID: PMC9473415          DOI: 10.1371/journal.pone.0273817

Source DB:  PubMed          Journal:  PLoS One        ISSN: 1932-6203            Impact factor:   3.752


  15 in total

1.  On the use of matrices in certain population mathematics.

Authors:  P H LESLIE
Journal:  Biometrika       Date:  1945-11       Impact factor: 2.445

2.  Correctly estimating how environmental stochasticity influences fitness and population growth.

Authors:  Daniel F Doak; William F Morris; Cathy Pfister; Bruce E Kendall; Emilio M Bruna
Journal:  Am Nat       Date:  2005-04-19       Impact factor: 3.926

3.  The type-reproduction number T in models for infectious disease control.

Authors:  J A P Heesterbeek; M G Roberts
Journal:  Math Biosci       Date:  2006-03-10       Impact factor: 2.144

4.  Patterns of variance in stage-structured populations: evolutionary predictions and ecological implications.

Authors:  C A Pfister
Journal:  Proc Natl Acad Sci U S A       Date:  1998-01-06       Impact factor: 11.205

5.  Life histories as adaptive strategies.

Authors:  J A León
Journal:  J Theor Biol       Date:  1976-08-07       Impact factor: 2.691

6.  Fitness response relation of a multitype age-structured population dynamics.

Authors:  Yuki Sughiyama; So Nakashima; Tetsuya J Kobayashi
Journal:  Phys Rev E       Date:  2019-01       Impact factor: 2.529

7.  Natural selection of life history attributes: an analytical approach.

Authors:  H M Taylor; R S Gourley; C E Lawrence; R S Kaplan
Journal:  Theor Popul Biol       Date:  1974-02       Impact factor: 1.570

8.  A new method for estimating the effort required to control an infectious disease.

Authors:  M G Roberts; J A P Heesterbeek
Journal:  Proc Biol Sci       Date:  2003-07-07       Impact factor: 5.349

9.  Age, stage and senescence in plants.

Authors:  Hal Caswell; Roberto Salguero-Gómez
Journal:  J Ecol       Date:  2013-04-24       Impact factor: 6.256

10.  Unification theory of optimal life histories and linear demographic models in internal stochasticity.

Authors:  Ryo Oizumi
Journal:  PLoS One       Date:  2014-06-19       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.