Subnational Population Research Articles

Parametric Subnational Population Volatility: The Importance of Abnormal Fluctuations

Parametric Subnational Population Volatility: The Importance of Abnormal Fluctuations

The Demographic Causes of European Sub-National Population Declines

Population decline is now established at the continental scale in Europe, occurring in abundance across sub-national areas and outweighing population growth. This represents an unfamiliar pathway of demographic change and is set to present unique challenges to the functioning of societies and economies. The nature of these challenges will be influenced by the demographic cause of population decline. Typically, low fertility is cited as the primary instigator, though it remains unclear of the ways in which unique interactions between fertility, mortality and migration have shaped contemporary population decline outcomes. This study empirically analyses the demographic causes of population decline in 732 sub-national areas extending across 33 European countries. Drawing on data derived from national statistics from 2000–2018, we employ a novel methodological approach consisting of decomposition, multivariate functional principal component analysis, and k-medoid clustering to identify the dominant demographic processes underpinning European depopulation. Our analysis reveals five unique signatures, encoding nuanced contributions from fertility, mortality and migration changes. Population decline is found to be a multi-causal process, with natural deficits and negative rates of net-migration both operating depopulations in most instances. We conclude that natural deficits are ubiquitous in causing sub-national population declines with net-migration patterns responsible for determining annual rates of population loss. We model the relationship between these signatures and wider demographic, socio-economic and geo-spatial attributes, finding that a distinct combination of contextual factors are associated with different demographic causes of population decline.

Cardiac Surgery to Manage Rheumatic Heart Disease in Africa Is Complex - a Geographic Perspective.

Rheumatic heart disease (RHD) is the most common form of acquired heart disease in Africa, often requiring surgical intervention. Previous studies have demonstrated the need for more cardiac surgeons in Africa but have not outlined their distribution relative to populations and incident cases. We estimate rheumatic heart disease incidence and cardiac surgical capacity to manage RHD in Africa. By characterizing geographic catchment areas served by the nearest cardiac surgeon(s), we estimate patient travel distance and the unmet surgical need. Subnational population, RHD incidence, cardiac surgeon, and geographic data were collected from credible, publicly accessible sources. Quantum Geographic Information System (QGIS 3.32) was used to create a subnational map of Africa and conduct nearest neighbor analyses to determine the location and distance of each subnational region's nearest cardiac surgeon. Catchment areas were defined and characterized. Incident RHD case-to-capacity ratios (ICCR) and surgical need were calculated. Incident RHD and surgical need were mapped at the subnational level across Africa. The human development index (HDI) of each region was then incorporated to assess the impact of socioeconomic disparities. A total of 779 subnational regions from 54 countries were included in the analysis. The African continent has an estimated 509 cardiac surgeons practicing in 74 subnational regions (corresponding to 74 catchment areas) and 1,027,974 incident cases of RHD annually. The average distance to travel for care by a cardiac surgeon was found to be 312.01 km (193.87 miles). The ICCR due to RHD for the African continent was 10.64. Access to cardiac surgical care is limited across Africa despite the high incidence of RHD. While nearly all areas of the continent would benefit from increasing cardiac surgical capacity, attention should be paid towards strategic development of geographically accessible cardiac surgical centers to equitize care for RHD.

A Bayesian Approach to Produce Subnational Population Estimates Using a Population Base Statistical Register

Subnational Population Estimates (SPE) in Latin America are useful to implement new public policies in subnational areas with internal armed conflicts or difficult to access. In this work, we propose to combine a Population Base Statistical Register (PBSR) and the Official Population Projections (OPP) using a Bayesian approach to produce SPE. Our proposed procedures are useful for computing SPE of the population size or the SPE of the population size in percentage SPE (%). However, we focused on SPE (%) due to some data restrictions and to ensure data confidentiality. In this article, the PBSR is constructed using multiple administrative sources with registers from the health, education, vital statistics systems, tax registration, and, more importantly, the registers of the victims of the current internal armed conflict in Colombia. We also propose new fast Markov chain Monte Carlo algorithms to produce SPE (%) using data augmentation procedures to address the complications caused by the resulting joint posterior containing gamma functions. We implement our proposal to compute SPE (%) by age and sex groups in the municipality of Jamundí in Colombia which is currently affected by poverty, forced displacement, and the internal armed conflict and evaluate the accuracy with a Population Census.

Future Subnational Population Change in Germany: The Role of Internal and International Migration

ABSTRACTPopulation change in Germany at the subnational level is particularly driven by changes in net international migration and shifts in internal migration flows between urbanisation, suburbanisation and counter‐urbanisation. Official population projections at the county level use a single scenario, thereby omitting uncertainty that arises from changing patterns in the assumed components of demographic change. We use a cohort‐component model that incorporates the spatial distribution of a net number of international migrants and internal migration matrices to provide population projections for 401 counties in Germany until 2070, encompassing nine total international and internal migration scenario combinations. Our results show a full potential outcome space of future subnational population change in Germany and highlight the variability in this possible change in terms of population structure, size, and spatial distribution. Across the scenarios, the total population of Germany is projected to be between 74.25 and 86.84 million people in 2040 (83.4 in 2023). There are also considerable differences in how the total population and its distribution might change spatially, both between urban and rural areas and in age structure. Thus, depending on the assumed absolute level of net international migration and the direction of internal migratory patterns we, highlight how internal and international migration patterns will continue to play a large role in future population development in Germany at the county level.

Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data, 2010–23

Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data, 2010–23

Sub-National Population Projections for Mexico Under the Shared Socioeconomic Pathways (SSPs) in the Context of Climate Change

Sub-National Population Projections for Mexico Under the Shared Socioeconomic Pathways (SSPs) in the Context of Climate Change

Population Fusion Transformer for Subnational Population Forecasting

Forecasting the subnational population accurately is needed for sustainable development, including planning for the future, allocating resources, or providing health services. Two approaches are used for forecasting subnational populations: local forecasting where a model is trained for each area, and global forecasting, where one model is trained with all areas. Local forecasting (e.g., statistical models) is limited to capturing the population growth patterns in a single area. Machine learning models, such as the light gradient boosting model (LGBM), are considered a more suitable approach for global forecasting, but it is limited to one-step predictions, leading to error accumulation. Also, combining several models into one ensemble model are used which helped in reduce forecasting errors. However, the nature of population growth is nonlinear, and there is a need to reduce error accumulation. This study overcomes these issues and proposes a population fusion transformer (PFT) as a global forecasting model for population forecasting, which outputs multi-step predictions. The PFT is based on a temporal fusion transformer (TFT) proposing a novel deep gated residual network (DGRN) block to capture data nonlinearity. This study also incorporates the proposed PFT model into various ensemble models to reduce forecasting errors using different prediction and learning approaches. The proposed models are applied to four subnational population datasets from several countries. The PFT model outperforms the LGBM and TFT with lower forecasting errors in three and two datasets. More importantly, combining the PFT with other models in ensemble models reduced errors further.

Future Blood Debt: Projecting Blood Supply and Demand of Korea Based on Subnational Population Projections (2021-2050).

South Korea faces a critical challenge with its rapidly declining fertility rates and an increasingly aging population, which significantly impacts the country's blood supply and demand. Despite these nationwide trends, regional disparities in blood supply and demand have not been thoroughly studied. This research utilized blood donation data from the Korean Red Cross and blood transfusion data from the Health Insurance Review and Assessment Service. We analyzed these datasets in conjunction with regional population projections to simulate blood supply and demand from 2021 to 2050 across South Korea. Sensitivity analyses were conducted to assess the impact of various factors, including the number of donors, age eligibility criteria for donations, frequency of donations, and blood discard rates. Our projections indicate a decreasing trend in blood supply, from 2.6 million units in 2021 to 1.4 million units by 2050, while demand is expected to peak at 5.1 million units by 2045 before declining. Metropolitan areas, particularly Gyeonggi Province, are projected to experience the most severe shortages. Sensitivity analyses suggest that increasing the donation frequency of existing donors and relaxing age eligibility criteria are more effective strategies in addressing these imbalances than merely increasing the number of new donors. Blood discard rates showed minimal impact on the overall blood shortage. The findings emphasize the urgent need for targeted strategies to mitigate national and regional blood supply shortages in South Korea. Encouraging frequent donations from experienced donors and broadening eligibility criteria are critical steps toward stabilizing the blood supply amidst demographic shifts. These strategies must be prioritized to address the impending regional disparities in blood availability.

What are the real populations of Chinese cities? On mistakes in city border defi nition and data interpretation in popular internet sources

Economic growth and intensive metropolisation processes in the PRC have increased interest in information on the size of the country’s cities. Chinese institutions apply population data to administrative units which is considerably larger than its urban area. The publicly available data are often divergent; according to Gibson & Li (2017) hundreds of studies in economics misinterpret China’s subnational population and over 80% of articles use these data erroneously. Few specialists are able to use data directly from original Chinese sources (see Chan, 2007; Chan & Wan, 2017), most of them use publicly available sources. Scientists and other users often have at their disposal estimates published by international institutions. A comparative analysis of those data exposes marked dissimilarities. The article is to identify differences between particular sources and to establish their causes. I assume that the reason for the discrepancy in the assessment of the city's population is not a difference in method of defining the city, but rather the fact that the authors of the studies do not apply established criteria and do not provide accurate calculations. Finally, guidelines are created that, if followed, should result in smaller discrepancies between data published by various sources.

Assistive technology usage, unmet needs and barriers to access: a sub-population-based study in India.

Assistive technology usage, unmet needs and barriers to access: a sub-population-based study in India.

Probabilistic County-Level Population Projections

Population projections provide predictions of future population sizes for an area. Historically, most population projections have been produced using deterministic or scenario-based approaches and have not assessed uncertainty about future population change. Starting in 2015, however, the United Nations (UN) has produced probabilistic population projections for all countries using a Bayesian approach. There is also considerable interest in subnational probabilistic population projections, but the UN's national approach cannot be used directly for this purpose, because within-country correlations in fertility and mortality are generally larger than between-country ones, migration is not constrained in the same way, and there is a need to account for college and other special populations, particularly at the county level. We propose a Bayesian method for producing subnational population projections, including migration and accounting for college populations, by building on but modifying the UN approach. We illustrate our approach by applying it to the counties of Washington State and comparing the results with extant deterministic projections produced by Washington State demographers. Out-of-sample experiments show that our method gives accurate and well-calibrated forecasts and forecast intervals. In most cases, our intervals were narrower than the growth-based intervals issued by the state, particularly for shorter time horizons.

Heat and Drought Reduce Subnational Population Growth in the Global Tropics.

In recent decades, the possibility that climate change will lead to depopulation of vulnerable areas in the global tropics via migration, mortality, or collapsing fertility has generated significant concern. We address this issue by using data on subnational population growth from 1,809 subnational units across the global tropics and linked data on climate exposures to examine how decadal temperature and precipitation anomalies influence population-weighted intercensal growth rates. Our fixed effects regression analysis reveals that the lowest predicted population growth rates occur under hot and dry conditions. The effects of heat and drought are strongest in districts that, at baseline, have high population densities, high precipitation rates, or high educational attainment. These patterns are contrary to common assumptions about these processes, and even the rare combination of hot and dry conditions, occurring in less than 7% of our sample, does not lead to local depopulation. Taken together with previous findings, this suggests that depopulation narratives do not have a strong evidentiary basis.

Nowcasting Daily Population Displacement in Ukraine through Social Media Advertising Data

AbstractIn times of crisis, real‐time data mapping population displacements are invaluable for targeted humanitarian response. The Russian invasion of Ukraine on February 24, 2022, forcibly displaced millions of people from their homes including nearly 6 million refugees flowing across the border in just a few weeks, but information was scarce regarding displaced and vulnerable populations who remained inside Ukraine. We leveraged social media data from Facebook's advertising platform in combination with preconflict population data to build a real‐time monitoring system to estimate subnational population sizes every day disaggregated by age and sex. Using this approach, we estimated that 5.3 million people had been internally displaced away from their baseline administrative region in the first three weeks after the start of the conflict. Results revealed four distinct displacement patterns: large‐scale evacuations, refugee staging areas, internal areas of refuge, and irregular dynamics. While the use of social media provided one of the only quantitative estimates of internal displacement in the conflict setting in virtual real time, we conclude by acknowledging risks and challenges of these new data streams for the future.

The levels and trends of diabetes prevalence at national and sub-national levels in Iran (1990 - 2016).

The increasing trends in Diabetes prevalence and its attributed burden emphasized as an important issue that needs serious and urgent attention, all over the word. We estimated the mean Fasting Plasma Glucose (FPG) and the prevalence of Diabetes in aged 25years or older Iranian adults, by sex, age, province, and year through the time period of 1990 to 2016. In order to access the most comprehensive relevant data at the same time the systematic data searched added to the data of 5 national surveys and 7 sub-national population based investigations. Two round of modeling, including the Age-Spatio-Temporal and Gaussian Process Regression were used for estimation of mean FPG trend and uncertainties. To estimate Diabetes estimations in target groups, a crosswalk model was applies to the FPG estimates. The model reiterated separately for women and men. All of estimations standardized based on the Iran national census population of 2016 by year, age groups and sexes at national and sub-national levels. In 2016, the number of the diabetic population was 4.43 (3.93-4.99) million (2.38 million women). Between 1990 and 2016, the age-standardized mean of FPG increased from 84.69mg/dl (79.8-89.8) to 100.5mg/dl (97.9-103.3) in women and from 82.7mg/dl (78.3-87.5) to 98.8mg/dl (96.2-101.4) in men. Simultaneously, with considerable difference, the Diabetes prevalence, has increased from 6.1% (4.7-7.8) to 9.8% (8.7-11.1) in women and from 5.0% 18 (3.8-6.3) to 8.1% (7.2-9.2) in men (75% attributed to population growth). Considering the geographical patterns, the greatest increment in the prevalence of Diabetes detected in the northwestern and the central provinces. Significant increasing trends of Diabetes led to alarming threat, which can make the strategies and goals of our prevention programs out of control. We should plan for more effective communicative interventions for prevention and management of Diabetes, to be designed, implemented and monitored based on the updated scientific evidence. The online version contains supplementary material available at 10.1007/s40200-023-01197-2.

Frameworks to envision equitable urban futures in a changing climate: A multi-level, multidisciplinary case study of New York City

Cities are at the forefront of climate change action and planning for futures that are concomitantly more resilient and equitable, making local goals imperative for global sustainability. Under the multiple challenges of changing climatic, ecological and socio-economic conditions, cities need the means to meet these goals. We know cities are and will continue to be points of concentrated and diverse populations, socioeconomic vulnerability, amplified exposure, transformed ecosystems and are responsible for the bulk of the world’s greenhouse gas emissions. Yet, much is also unknown and intrinsically uncertain about urban futures: there is a range of potential plausible futures which have differing implications for both potential mitigation and adaptation actions. To better assess these plausible futures, the “global change” research community developed a framework including scenarios that are applicable for global and regional policy, entitled the Shared Socio-economic Pathways (SSPs) and scenarios exploring future emissions that will drive climate change, entitled Representative Concentration Pathways (RCPs). Importantly, this global scale framework does not include specific city-level perspectives or data at the spatial scales necessary to address questions of local relevance. While the SSPs address many of the key population and socioeconomic drivers of climate change, they do not address important concerns that are particularly relevant to cities, such as racial justice, ecosystem change or migration. Nevertheless, city-level impacts will evolve, in part, as a function of the global scale change characterized by the SSPs, and in part based on demographic and social processes already underway. As such, applying a modification of this framework to cities has the potential to help limit local climate impacts, and create a more resilient, equitable city. To address these needs and respond to city and regional stakeholders, we propose a framework for science-based narratives and quantitative projections for cities and metropolitan areas, such as Greater New York City. In this paper, we review a wide-range of existing approaches to generate estimates of future populations and identify their vulnerabilities to climate-change hazards, ranging from subnational population projections or the spatially-explicit allocation of populations linked to SSPs for the US and selected cities, city-specific population forecasting without climate considerations, and participatory approaches to future scenario development and fine-scale, within-city land use change models. By showcasing the strengths and limitations of various approaches and modeling efforts, their spatial and temporal scales, and thematic breadth, we propose a novel framework that leverages state-of-the art quantitative approaches and couples it with stakeholder engagement that can help cities plan equitably under uncertainty.

Intercensal Updating Using Structure-Preserving Methods and Satellite Imagery

Abstract Censuses are fundamental building blocks of most modern-day societies, yet collected every 10 years at best. We propose an extension of the widely popular census updating technique structure-preserving estimation by incorporating auxiliary information in order to take ongoing subnational population shifts into account. We apply our method by incorporating satellite imagery as additional source to derive annual small-area updates of multidimensional poverty indicators from 2013 to 2020 for a population at risk: female-headed households in Senegal. We evaluate the performance of our proposal using data from two different census periods.

Short- to medium-run forecasting of mobility with dynamic linear models

Long-term projections of mobility are key inputs to sub-national population projections. These long-term projections are based on extrapolations of long-term trends. In cases of strong, potentially temporal, fluctuations it is informative to analyse the sho

Why were there 231707 more deaths than expected in England between 2010 and 2018? An ecological analysis of mortality records.

BackgroundPolicy responses to the Global Financial Crisis emphasized wide-ranging fiscal austerity measures, many of which have been found to negatively impact health outcomes. This paper investigates change in patterns of mortality at local authority level in England (2010–11 to 2017–18) and the relation with fiscal austerity measures.MethodsData from official local authority administrative records are used to quantify the gap between observed deaths and what was anticipated in the 2010-based subnational population projections. Regression analyses are used to explore the relation between excess deaths, austerity and wider process of population change at local authority level.ResultsWe estimate 231 707 total excess deaths, the majority of which occurred since 2014–15 (89%) across the majority of local authorities (91%). Austerity is positively associated with excess deaths. For working age adults, there is a clear gradient to the impact of austerity, whereas for older adults, the impact is more uniform.ConclusionsFiscal austerity policies contributed to an excess of deaths for older people and widened social inequalities for younger populations. These results call for an end to all austerity measures and require further research into areas with the highest total excess deaths as a priority following the COVID-19 pandemic.

Regional characteristics of children's blood lead levels in China: A systematic synthesis of national and subnational population data

Regional characteristics of children's blood lead levels in China: A systematic synthesis of national and subnational population data