The impact of Covid-19 on demographic components in Spain, 2020-31: A scenario approach

While considerable attention has been paid to the impact of Covid-19 on mortality and fertility, few studies have attempted to evaluate the pandemic's effect on international migration. We analyse the impact of Covid-19 on births, deaths, and international migration in Spain during 2020, comparing observed data with estimated values assuming there had been no pandemic. We also assess the consequences of three post-pandemic scenarios on the size and structure of the population to 2031. Results show that in 2020, excess mortality equalled 16.2 per cent and births were 6.5 per cent lower than expected. Immigration was the most affected component, at 36.0 per cent lower than expected, while emigration was reduced by 23.8 per cent. If net migration values recover to pre-pandemic levels in 2022, the size and structure of the population in 2031 will be barely affected. Conversely, if levels do not recover until 2025, there will be important changes to Spain's age structure.

Contrasting seasonal effects of climate change influence density in a cold-adapted species

Many ecological processes are profoundly influenced by abiotic factors, such as temperature and snow. However, despite strong evidence linking shifts in these ecological processes to corresponding shifts in abiotic factors driven by climate change, the mechanisms connecting population size to season-specific climate drivers are little understood. Using a 21-year dataset and a Bayesian state space model, we identified biologically informed seasonal climate covariates that influenced densities of snowshoe hares (Lepus americanus), a cold-adapted boreal herbivore. We found that snow and temperature had strong but conflicting season-dependent effects. Reduced snow duration in spring and fall and warmer summers were associated with lowered hare density, whereas warmer winters were associated with increased density. When modeled simultaneously and under two climate change scenarios, the negative effects of reduced fall and spring snow duration and warmer summers overwhelm the positive effect of warmer winters, producing projected population declines. Ultimately, the contrasting population-level impacts of climate change across seasons emphasize the critical need to examine the entire annual climate cycle to understand potential long-term population consequences of climate change.

Projections of dependency and associated social care expenditure for the older population in England to 2038: effect of varying disability progression

Objectives

to assess the effect of recent stalling of life expectancy and various scenarios for disability progression on projections of social care expenditure between 2018 and 2038, and the likelihood of reaching the Ageing Society Grand Challenge mission of five extra healthy, independent years at birth.

Design

two linked projections models: the Population Ageing and Care Simulation (PACSim) model and the Care Policy and Evaluation Centre long-term care projections model, updated to include 2018-based population projections.

Population

PACSim: about 303,589 individuals aged 35 years and over (a 1% random sample of the England population in 2014) created from three nationally representative longitudinal ageing studies.

Main outcome measures

Total social care expenditure (public and private) for older people, and men and women’s independent life expectancy at age 65 (IndLE65) under five scenarios of changing disability progression and recovery with and without lower life expectancy.

Results

between 2018 and 2038, total care expenditure was projected to increase by 94.1%–1.25% of GDP; men’s IndLE65 increasing by 14.7% (range 11.3–16.5%), exceeding the 8% equivalent of the increase in five healthy, independent years at birth, although women’s IndLE65 increased by only 4.7% (range 3.2–5.8%). A 10% reduction in disability progression and increase in recovery resulted in the lowest increase in total care expenditure and increases in both men’s and women’s IndLE65 exceeding 8%.

Conclusions

interventions that slow down disability progression, and improve recovery, could significantly reduce social care expenditure and meet government targets for increases in healthy, independent years.

Demographic perspectives in research on global environmental change

The human population is at the centre of research on global environmental change. On the one hand, population dynamics influence the environment and the global climate system through consumption-based carbon emissions. On the other hand, the health and well-being of the population are already being affected by climate change. A knowledge of population dynamics and population heterogeneity is thus fundamental to improving our understanding of how population size, composition, and distribution influence global environmental change and how these changes affect population subgroups differentially by demographic characteristics and spatial distribution. The increasing relevance of demographic research on the topic, coupled with availability of theoretical concepts and advancement in data and computing facilities, has contributed to growing engagement of demographers in this field. In the past 25 years, demographic research has enriched climate change research-with the key contribution being in moving beyond the narrow view that population matters only in terms of population size-by putting a greater emphasis on population composition and distribution, through presenting both empirical evidence and advanced population forecasting to account for demographic and spatial heterogeneity. What remains missing in the literature is research that investigates how global environmental change affects current and future demographic processes and, consequently, population trends. If global environmental change does influence fertility, mortality, and migration, then population estimates and forecasts need to adjust for climate feedback in population projections. Indisputably, this is the area of new research that directly requires expertise in population science and contribution from demographers.

Undocumented Older Latino Immigrants in the United States: Population Projections and Share of Older Undocumented Latinos by Health Insurance Coverage and Chronic Health Conditions, 2018-2038

OBJECTIVES

This paper focuses on the older Latino undocumented population and anticipates how their current demographic characteristics and health insurance coverage might impact future population size and health insurance trends.

METHODS

We use the 2013-2018 American Community Survey as a baseline to project growth in the Latino 55+ undocumented population over the next 20 years. We use the cohort component method to estimate population size across different migration scenarios and distinguish between aging in place and new in-migration. We also examine contemporary health insurance coverage and chronic health conditions among 55+ undocumented Latinos from the 2003-2014 California Health Interview Survey. We then project health insurance rates in 2038 among Latino immigrants under different migration and policy scenarios.

RESULTS

If current mortality, migration, and policy trends continue, projections estimate that 40% of undocumented Latino immigrants will be 55 years or older by 2038 - nearly all of whom will have aged in place. Currently, 40% of older Latino undocumented immigrants do not have insurance. Without policies that increase access to insurance, projections estimate that the share who are uninsured among all older Latinos immigrants will rise from 15% to 21%, and the share that is both uninsured and living with a chronic health condition will rise from 5% to 9%.

DISCUSSION

Without access health care, older undocumented immigrants may experience delayed care and more severe morbidity. Our projections highlight the need to develop and enact policies that can address impending health access concerns for an increasingly older undocumented Latino population.

The call of the emperor penguin: Legal responses to species threatened by climate change

Species extinction risk is accelerating due to anthropogenic climate change, making it urgent to protect vulnerable species through legal frameworks in order to facilitate conservation actions that help mitigate risk. Here, we discuss fundamental concepts for assessing climate change risks to species using the example of the emperor penguin (Aptenodytes forsteri), currently being considered for protection under the US Endangered Species Act (ESA). This species forms colonies on Antarctic sea ice, which is projected to significantly decline due to ongoing greenhouse gas (GHG) emissions. We project the dynamics of all known emperor penguin colonies under different GHG emission scenarios using a climate-dependent meta-population model including the effects of extreme climate events based on the observational satellite record of colonies. Assessments for listing species under the ESA require information about how species resiliency, redundancy and representation (3Rs) will be affected by threats within the foreseeable future. Our results show that if sea ice declines at the rate projected by climate models under current energy system trends and policies, the 3Rs would be dramatically reduced and almost all colonies would become quasi-extinct by 2100. We conclude that the species should be listed as threatened under the ESA.

How does increasing mast seeding frequency affect population dynamics of seed consumers? Wild boar as a case study

Mast seeding in temperate oak populations shapes the dynamics of seed consumers and numerous communities. Mast seeding responds positively to warm spring temperatures and is therefore expected to increase under global warming. We investigated the potential effects of changes in oak mast seeding on wild boar population dynamics, a widespread and abundant consumer species. Using long-term monitoring data, we showed that abundant acorn production enhances the proportion of breeding females. With a body-mass-structured population model and a fixed hunting rate of 0.424, we showed that high acorn production over time would lead to an average wild boar population growth rate of 1.197 whereas non-acorn production would lead to a stable population. Finally, using climate projections and a mechanistic model linking weather data to oak reproduction, we predicted that mast seeding frequency might increase over the next century, which would lead to increase in both wild boar population size and the magnitude of its temporal variation. Our study provides rare evidence that some species could greatly benefit from global warming thanks to higher food availability and therefore highlights the importance of investigating the cascading effects of changing weather conditions on the dynamics of wild animal populations to reliably assess the effects of climate change.

Using future age profiles to improve immigration projections

Young adults migrate more than older people. As populations in many countries get older, this may affect out-migration-and thus immigration to other countries. This is not usually accounted for in projections of future immigration, even though considerable ageing is expected globally. We show how United Nations projections of future age profiles in origin regions can be combined with those regions' emigration rates by age group to improve national projections of immigration to a destination country, exemplified by Norway. Using various methods for projecting future migration, we show that projected immigration tends to be lower when taking expected ageing in origin regions into account. This may have a considerable effect on population projections: for Norway, taking changing age profiles in origin regions into account in immigration projections would have an effect on the projected population of Norway equivalent to that of reducing the fertility assumptions by 0.1 children per woman.

Ageing of the Aboriginal and Torres Strait Islander population: numerical, structural, timing and spatial aspects

OBJECTIVES

To assess levels of numerical, structural, timing and spatial aspects of ageing of the Aboriginal and Torres Strait Islander population.

METHODS

Population projections for 15 Australian regions were created by a multi-state cohort-component model.

RESULTS

The older (45-plus) population grew from 29,815 in 1986 to 167,259 in 2016. In the subsequent 30 years, we project growth to 448,785 people. Growth rates of the older population vary: from 200% in the 60-64-year-old group to 800% growth in the 85-plus age group by mid-century. This strong numerical ageing is reflected in a shift in structural ageing by about six percentage points. Selected areas outside of capital cities are structurally older than many cities. Numerical ageing is strongest in capital cities and New South Wales. Cohort flow is the primary driver of ageing.

CONCLUSIONS

Numerical and structural ageing is projected to increase significantly to mid-century with important spatial variations. Population ageing is largely irreversible. Implications for public health: High numerical growth in the older Aboriginal and Torres Strait Islander population poses implications for increased demand for a range of health and care services. Variations in spatial and timing aspects of ageing indicate demand will peak earlier in some geographical locations relative to others.

Stalls in Africa's fertility decline partly result from disruptions in female education

The future pace of fertility decline in sub-Saharan Africa is the main determinant of future world population growth and will have massive implications for Africa and the rest of the world, not least through international migration pressure and difficulties in meeting the sustainable development goals. In this context, there have been concerns about recent stalls in the fertility decline in some African countries. Our findings suggest that these stalls are in part explained by earlier stalls in female education and that less-educated women are more vulnerable to adverse period conditions. This has important implications for setting policy priorities.

Population projections for sub-Saharan Africa have, over the past decade, been corrected upwards because in a number of countries, the earlier declining trends in fertility stalled around 2000. While most studies so far have focused on economic, political, or other factors around 2000, here we suggest that in addition to those period effects, the phenomenon also matched up with disruptions in the cohort trends of educational attainment of women after the postindependence economic and political turmoil. Disruptions likely resulted in a higher proportion of poorly educated women of childbearing age in the late 1990s and early 2000s than there would have been otherwise. In addition to the direct effects of education on lowering fertility, these less-educated female cohorts were also more vulnerable to adverse period effects around 2000. To explore this hypothesis, we combine individual-level data from Demographic and Health Surveys for 18 African countries with and without fertility stalls, thus creating a pooled dataset of more than two million births to some 670,000 women born from 1950 to 1995 by level of education. Statistical analyses indicate clear discontinuities in the improvement of educational attainment of subsequent cohorts of women and stronger sensitivity of less-educated women to period effects. We assess the magnitude of the effect of educational discontinuity through a comparison of the actual trends with counterfactual trends based on the assumption of no education stalls, resulting in up to half a child per woman less in 2010 and 13 million fewer live births over the 1995–2010 period.

Inferring forest fate from demographic data: from vital rates to population dynamic models

As population-level patterns of interest in forests emerge from individual vital rates, modelling forest dynamics requires making the link between the scales at which data are collected (individual stems) and the scales at which questions are asked (e.g. populations and communities). Structured population models (e.g. integral projection models (IPMs)) are useful tools for linking vital rates to population dynamics. However, the application of such models to forest trees remains challenging owing to features of tree life cycles, such as slow growth, long lifespan and lack of data on crucial ontogenic stages. We developed a survival model that accounts for size-dependent mortality and a growth model that characterizes individual heterogeneity. We integrated vital rate models into two types of population model; an analytically tractable form of IPM and an individual-based model (IBM) that is applied with stochastic simulations. We calculated longevities, passage times to, and occupancy time in, different life cycle stages, important metrics for understanding how demographic rates translate into patterns of forest turnover and carbon residence times. Here, we illustrate the methods for three tropical forest species with varying life-forms. Population dynamics from IPMs and IBMs matched a 34 year time series of data (albeit a snapshot of the life cycle for canopy trees) and highlight differences in life-history strategies between species. Specifically, the greater variation in growth rates within the two canopy species suggests an ability to respond to available resources, which in turn manifests as faster passage times and greater occupancy times in larger size classes. The framework presented here offers a novel and accessible approach to modelling the population dynamics of forest trees.

How science and technology developments impact employment and education

A better understanding of how developments in science and technology influence the creation of new occupations and subsequent changes in educational programs can help decision makers at all levels of our society. As a result of research and development efforts, innovations are achieved, resulting in the creation of new occupations and the demand for employees with expertise in these new areas. To fulfill the demand, universities and colleges often revise their programs to address these needs. Several data sources are described in this paper that might help us to explore the relationship between advancements in industry, emerging occupations, and educational changes over time.

The demographic impact and development benefits of meeting demand for family planning with modern contraceptive methods

Background: Meeting demand for family planning can facilitate progress towards all major themes of the United Nations Sustainable Development Goals (SDGs): people, planet, prosperity, peace, and partnership. Many policymakers have embraced a benchmark goal that at least 75% of the demand for family planning in all countries be satisfied with modern contraceptive methods by the year 2030.

Objective: This study examines the demographic impact (and development implications) of achieving the 75% benchmark in 13 developing countries that are expected to be the furthest from achieving that benchmark.

Methods: Estimation of the demographic impact of achieving the 75% benchmark requires three steps in each country: 1) translate contraceptive prevalence assumptions (with and without intervention) into future fertility levels based on biometric models, 2) incorporate each pair of fertility assumptions into separate population projections, and 3) compare the demographic differences between the two population projections. Data are drawn from the United Nations, the US Census Bureau, and Demographic and Health Surveys.

Results: The demographic impact of meeting the 75% benchmark is examined via projected differences in fertility rates (average expected births per woman’s reproductive lifetime), total population, growth rates, age structure, and youth dependency. On average, meeting the benchmark would imply a 16 percentage point increase in modern contraceptive prevalence by 2030 and a 20% decline in youth dependency, which portends a potential demographic dividend to spur economic growth.

Conclusions: Improvements in meeting the demand for family planning with modern contraceptive methods can bring substantial benefits to developing countries. To our knowledge, this is the first study to show formally how such improvements can alter population size and age structure. Declines in youth dependency portend a demographic dividend, an added bonus to the already well-known benefits of meeting existing demands for family planning.

Future population and human capital in heterogeneous India

Within the next decade India is expected to surpass China as the world's most populous country due to still higher fertility and a younger population. Around 2025 each country will be home to around 1.5 billion people. India is demographically very heterogeneous with some rural illiterate populations still having more than four children on average while educated urban women have fewer than 1.5 children and with great differences between states. We show that the population outlook greatly depends on the degree to which this heterogeneity is explicitly incorporated into the population projection model used. The conventional projection model, considering only the age and sex structures of the population at the national level, results in a lower projected population than the same model applied at the level of states because over time the high-fertility states gain more weight, thus applying the higher rates to more people. The opposite outcome results from an explicit consideration of education differentials because over time the proportion of more educated women with lower fertility increases, thus leading to lower predicted growth than in the conventional model. To comprehensively address this issue, we develop a five-dimensional model of India's population by state, rural/urban place of residence, age, sex, and level of education and show the impacts of different degrees of aggregation. We also provide human capital scenarios for all Indian states that suggest that India will rapidly catch up with other more developed countries in Asia if the recent pace of education expansion is maintained.

Conservation status of polar bears (Ursus maritimus) in relation to projected sea-ice declines

Loss of Arctic sea ice owing to climate change is the primary threat to polar bears throughout their range. We evaluated the potential response of polar bears to sea-ice declines by (i) calculating generation length (GL) for the species, which determines the timeframe for conservation assessments; (ii) developing a standardized sea-ice metric representing important habitat; and (iii) using statistical models and computer simulation to project changes in the global population under three approaches relating polar bear abundance to sea ice. Mean GL was 11.5 years. Ice-covered days declined in all subpopulation areas during 1979-2014 (median -1.26 days year-1). The estimated probabilities that reductions in the mean global population size of polar bears will be greater than 30%, 50% and 80% over three generations (35-41 years) were 0.71 (range 0.20-0.95), 0.07 (range 0-0.35) and less than 0.01 (range 0-0.02), respectively. According to IUCN Red List reduction thresholds, which provide a common measure of extinction risk across taxa, these results are consistent with listing the species as vulnerable. Our findings support the potential for large declines in polar bear numbers owing to sea-ice loss, and highlight near-term uncertainty in statistical projections as well as the sensitivity of projections to different plausible assumptions.

: Probabilistic Population Projections

We describe bayesPop, an R package for producing probabilistic population projections for all countries. This uses probabilistic projections of total fertility and life expectancy generated by Bayesian hierarchical models. It produces a sample from the joint posterior predictive distribution of future age- and sex-specific population counts, fertility rates and mortality rates, as well as future numbers of births and deaths. It provides graphical ways of summarizing this information, including trajectory plots and various kinds of probabilistic population pyramids. An expression language is introduced which allows the user to produce the predictive distribution of a wide variety of derived population quantities, such as the median age or the old age dependency ratio. The package produces aggregated projections for sets of countries, such as UN regions or trading blocs. The methodology has been used by the United Nations to produce their most recent official population projections for all countries, published in the World Population Prospects.

Locally adaptive, spatially explicit projection of US population for 2030 and 2050

Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census's projection methodology, with the US Census's official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

The world population explosion: causes, backgrounds and -projections for the future

At the beginning of the nineteenth century, the total world population crossed the threshold of 1 billion people for the first time in the history of the homo sapiens sapiens. Since then, growth rates have been increasing -exponentially, reaching staggeringly high peaks in the 20th century and slowing down a bit thereafter. Total world population reached 7 billion just after 2010 and is expected to count 9 billion by 2045. This paper first charts the differences in population growth between the world regions. Next, the mechanisms behind unprecedented population growth are explained and plausible scenarios for future developments are discussed. Crucial for the long term trend will be the rate of decline of the number of births per woman, called total fertility. Improvements in education, reproductive health and child survival will be needed to speed up the decline of total fertility, particularly in Africa. But in all scenarios, world population will continue to grow for some time due to population momentum. Finally, the paper outlines the debate about the consequences of the population explosion, involving poverty and food security, the impact on the natural environment, and migration flows.

KEY WORDS

Fertility, family planning, world population, population growth, demographic transition, urbanization, population momentum, population projections.

Variation in estimated ozone-related health impacts of climate change due to modeling choices and assumptions

BACKGROUND

Future climate change may cause air quality degradation via climate-induced changes in meteorology, atmospheric chemistry, and emissions into the air. Few studies have explicitly modeled the potential relationships between climate change, air quality, and human health, and fewer still have investigated the sensitivity of estimates to the underlying modeling choices.

OBJECTIVES

Our goal was to assess the sensitivity of estimated ozone-related human health impacts of climate change to key modeling choices.

METHODS

Our analysis included seven modeling systems in which a climate change model is linked to an air quality model, five population projections, and multiple concentration-response functions. Using the U.S. Environmental Protection Agency's (EPA's) Environmental Benefits Mapping and Analysis Program (BenMAP), we estimated future ozone (O(3))-related health effects in the United States attributable to simulated climate change between the years 2000 and approximately 2050, given each combination of modeling choices. Health effects and concentration-response functions were chosen to match those used in the U.S. EPA's 2008 Regulatory Impact Analysis of the National Ambient Air Quality Standards for O(3).

RESULTS

Different combinations of methodological choices produced a range of estimates of national O(3)-related mortality from roughly 600 deaths avoided as a result of climate change to 2,500 deaths attributable to climate change (although the large majority produced increases in mortality). The choice of the climate change and the air quality model reflected the greatest source of uncertainty, with the other modeling choices having lesser but still substantial effects.

CONCLUSIONS

Our results highlight the need to use an ensemble approach, instead of relying on any one set of modeling choices, to assess the potential risks associated with O(3)-related human health effects resulting from climate change.

The dynamics of mass migration

We specify a set of equations defining a dynamic model of international migration and estimate its parameters by using data specially collected in Mexico. We then used it to project the a hypothetical Mexican community population forward in time. Beginning with a stable population of 10,000 people, we project ahead 50 years under three different assumptions: no international migration; constant probabilities of in- and out-migration, and dynamic schedules of out- and in-migration that change as migratory experience accumulates. This exercise represents an attempt to model the self-feeding character of international migration noted by prior observers and theorists. Our model quantifies the mechanisms of cumulative causation predicted by social capital theory and illustrates the shortcomings of standard projection methodologies. The failure to model dynamically changing migration schedules yields a 5% overstatement of the projected size of the Mexican population after 50 years, an 11% understatement of the total number of U.S. migrants, a 15% understatement of the prevalence of U.S. migratory experience in the Mexican population, and an 85% understatement of the size of the Mexican population living in the United States.