Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study

作者：Stein Emil Vollset, Emily Goren, Chun-Wei Yuan, Jackie Cao, Amanda Smith, Thomas Hsiao, Catherine Bisignano, Gulrez Shah Azhar, Emma Castro, Julian Chalek, Andrew J. Dolgert, Tahvi Frank, Kai Fukutaki, Simon I Hay, Rafael Lozano, Ali H. Mokdad, Vishnu Nandakumar, Maxwell Pierce, Martin A Pletcher, Toshana Robalik, Krista M. Steuben, Han Yong Wunrow, Bianca S Zlavog, Christopher J L Murray · 发表于：The Lancet · 年份：2020 · DOI：10.1016/s0140-6736(20)30677-2 · 被引用次数：1524 · 研究领域：Insurance, Mortality, Demography, Risk Management、Global Maternal and Child Health、Health and Conflict Studies

BACKGROUND: Understanding potential patterns in future population levels is crucial for anticipating and planning for changing age structures, resource and health-care needs, and environmental and economic landscapes. Future fertility patterns are a key input to estimation of future population size, but they are surrounded by substantial uncertainty and diverging methodologies of estimation and forecasting, leading to important differences in global population projections. Changing population size and age structure might have profound economic, social, and geopolitical impacts in many countries. In this study, we developed novel methods for forecasting mortality, fertility, migration, and population. We also assessed potential economic and geopolitical effects of future demographic shifts. METHODS: We modelled future population in reference and alternative scenarios as a function of fertility, migration, and mortality rates. We developed statistical models for completed cohort fertility at age 50 years (CCF50). Completed cohort fertility is much more stable over time than the period measure of the total fertility rate (TFR). We modelled CCF50 as a time-series random walk function of educational attainment and contraceptive met need. Age-specific fertility rates were modelled as a function of CCF50 and covariates. We modelled age-specific mortality to 2100 using underlying mortality, a risk factor scalar, and an autoregressive integrated moving average (ARIMA) model. Net migra...