In the Cook Islands in 2024, the population decreased by about 2.24 percent compared to the previous year, making it the country with the highest population decline rate in 2024. Of the 20 countries with the highest rate of population decline, the majority are island nations, where emigration rates are high (especially to Australia, New Zealand, and the United States), or they are located in Eastern Europe, which suffers from a combination of high emigration rates and low birth rates.

This web map indicates the annual compound rate of total population change in the United States from 2000 to 2010. Total Population is the total number of residents in an area. Residence refers to the "usual place" where a person lives. Total Population for 2000 is from the U.S. Census 2000. The 2010 Total Population variable is estimated by Esri's proven annual demographic update methodology that blends GIS with statistical technology and a unique combination of data sources.The map is symbolized so that you can easily distinguish areas of population growth (i.e. shades of green) from areas of population decline (i.e. shades of red). It uses a 3 D effect to further emphasize those trends. The map reveals interesting patterns of recent population change in various regions and communities across the United States.The map shows population change at the County and Census Tract levels. The geography depicts Counties at 25m to 750k scale, Census Tracts at 750k to 100k scale.Esri's Updated Demographics (2010/2015) – Population, age, income, sex, race, marital status and other variables are among the variables included in the database. Each year, Esri's data development team employs its proven methodologies to update more than 2,000 demographic variables for a variety of geographies. See Updated Demographics for more information.

For most of the past two centuries, falling birth rates have been associated with societal progress. During the demographic transition, where pre-industrial societies modernize in terms of fertility and mortality, falling death rates, especially among infants and children, are the first major change. In response, as more children survive into adulthood, women have fewer children as the need to compensate for child mortality declines. This transition has happened at different times across the world and is an ongoing process, with early industrial countries being the first to transition, and Sub-Saharan African countries being the most recent to do so. Additionally, some Asian countries (particularly China through government policy) have gone through their demographic transitions at a much faster pace than those deemed more developed. Today, in countries such as Japan, Italy, and Germany, birth rates have fallen well below death rates; this is no longer considered a positive demographic trend, as it leads to natural population decline, and may create an over-aged population that could place a burden on healthcare systems.

Population growth drives increasing demand for housing, jobs, food, education, transportation and many services. Population decline is the flip side of that dynamic, creating its own pressures on local business, government, housing and people.This map shows which areas are under significant pressure from population growth or decline. As the population of the U.S. continues to grow, the cities and the suburbs are experiencing changes in their population density. This map shows areas of declining density in brown, and high growth in dark green.Red areas will lose population by 2015, while green areas will grow. Darker green areas will grow more than 1.25% per year. Click on the map for details about an area. Use this map as a backdrop for your organization's locations, services areas, or other subjects. There is also a simple app showing this web map.You candownload the data from this map package.

The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolongued development arc in Sub-Saharan Africa.

This study examines how population change is associated with changes in sociodemographics and economic outcomes across diverse geographic contexts in the United States from 2000 to 2020. Using Census Tract-level data and generalized additive models (GAMs), we found that communities experiencing population growth showed significant improvements in socioeconomic indicators: for example, a 50% population increase in Northeast metropolitan non-coastal areas was associated with a $10,062 rise [95% confidence interval (CI) = $9,181, $10,944] in median household income. Conversely, areas with population decline faced increasing challenges to community composition: communities experiencing a 50% population decline in West coastal metropolitan areas saw their median age increase by 2.556 years (95% CI = 2.23, 2.89 years), indicating an accelerated aging population. We observed a positive relationship between population growth and local economic growth, with areas experiencing population decline or slow growth showing below-average economic growth. While population change alone explained 10.1% of the variance in county-level GDP growth, incorporating sociodemographic shifts alongside population change using a partial least squares regression (PLSR) more than doubled the explanatory power to 21.4%. Overall, we often found the strength of relationships and sometimes the direction varied by geographic context: coastal areas showed distinct patterns from inland regions, and metropolitan areas responded differently than rural ones. For instance, the percentage of owner-occupied housing was negatively associated with population growth in metropolitan areas, but positively associated in non-metropolitan areas. Our research provides valuable insights for policymakers and planners working to address community changes, particularly in the context of anticipated climate-induced migration. The results suggest that strategies for maintaining economic vitality need to consider not just population retention, but also demographic profiles and socioeconomic opportunities across different geographic contexts.

Prior to the arrival of European explorers in the Americas in 1492, it is estimated that the population of the continent was around sixty million people. Over the next two centuries, most scholars agree that the indigenous population fell to just ten percent of its pre-colonization level, primarily due to the Old World diseases (namely smallpox) brought to the New World by Europeans and African slaves, as well as through violence and famine.

Distribution

It is thought that the most densely populated region of the Americas was in the fertile Mexican valley, home to over one third of the entire continent, including several Mesoamerican civilizations such as the Aztec empire. While the mid-estimate shows a population of over 21 million before European arrival, one estimate suggests that there were just 730,000 people of indigenous descent in Mexico in 1620, just one hundred years after Cortes' arrival. Estimates also suggest that the Andes, home to the Incas, was the second most-populous region in the Americas, while North America (in this case, the region north of the Rio Grande river) may have been the most sparsely populated region. There is some contention as to the size of the pre-Columbian populations in the Caribbean, as the mass genocides, forced relocation, and pandemics that followed in the early stages of Spanish colonization make it difficult to predict these numbers.

Varying estimates Estimating the indigenous populations of the Americas has proven to be a challenge and point of contention for modern historians. Totals from reputable sources range from 8.4 million people to 112.55 million, and while both of these totals were published in the 1930s and 1960s respectively, their continued citation proves the ambiguity surrounding this topic. European settlers' records from the 15th to 17th centuries have also created challenges, due to their unrealistic population predictions and inaccurate methodologies (for example, many early settlers only counted the number of warriors in each civilization). Nonetheless, most modern historians use figures close to those given in the "Middle estimate" shown here, with similar distributions by region.

The world's population first reached one billion people in 1803, and reach eight billion in 2023, and will peak at almost 11 billion by the end of the century. Although it took thousands of years to reach one billion people, it did so at the beginning of a phenomenon known as the demographic transition; from this point onwards, population growth has skyrocketed, and since the 1960s the population has increased by one billion people every 12 to 15 years. The demographic transition sees a sharp drop in mortality due to factors such as vaccination, sanitation, and improved food supply; the population boom that follows is due to increased survival rates among children and higher life expectancy among the general population; and fertility then drops in response to this population growth. Regional differences The demographic transition is a global phenomenon, but it has taken place at different times across the world. The industrialized countries of Europe and North America were the first to go through this process, followed by some states in the Western Pacific. Latin America's population then began growing at the turn of the 20th century, but the most significant period of global population growth occurred as Asia progressed in the late-1900s. As of the early 21st century, almost two thirds of the world's population live in Asia, although this is set to change significantly in the coming decades. Future growth The growth of Africa's population, particularly in Sub-Saharan Africa, will have the largest impact on global demographics in this century. From 2000 to 2100, it is expected that Africa's population will have increased by a factor of almost five. It overtook Europe in size in the late 1990s, and overtook the Americas a decade later. In contrast to Africa, Europe's population is now in decline, as birth rates are consistently below death rates in many countries, especially in the south and east, resulting in natural population decline. Similarly, the population of the Americas and Asia are expected to go into decline in the second half of this century, and only Oceania's population will still be growing alongside Africa. By 2100, the world's population will have over three billion more than today, with the vast majority of this concentrated in Africa. Demographers predict that climate change is exacerbating many of the challenges that currently hinder progress in Africa, such as political and food instability; if Africa's transition is prolonged, then it may result in further population growth that would place a strain on the region's resources, however, curbing this growth earlier would alleviate some of the pressure created by climate change.

The introduced fungal pathogen Pseudogymnoascus destructans is causing decline of several species of bats in North America, with some even at risk of extinction or extirpation. The severity of the epidemic of white-nose syndrome caused by P. destructans has prompted investigation of the transmission and virulence of infection at multiple scales, but linking these scales is necessary to quantify the mechanisms of transmission and assess population-scale declines. We build a model connecting within-cave disease dynamics of little brown bats to regional scale dispersal, reproduction, and disease spread, including multiple plausible mechanisms of transmission. We parameterize the model using the approach of plausible parameter sets, by comparing stochastic simulation results to statistical probes from empirical data on within-cave prevalence and survival, as well as between-cave spread across a region. Our results are consistent with frequency-dependent transmission between bats, support an important role of environmental transmission, and show very little effect of dispersal among colonies on metapopulation survival. The model also offers a generalizable method to assess hypotheses about cave-to-cave transmission and to identify gaps in knowledge about key processes, and could be expanded to include additional mechanisms or bat species as research on this detrimental fungus progresses.

Population: VR: Orenburg Region data was reported at 1,815,655.000 Person in 2024. This records a decrease from the previous number of 1,828,656.000 Person for 2023. Population: VR: Orenburg Region data is updated yearly, averaging 2,061,795.500 Person from Dec 1989 (Median) to 2024, with 36 observations. The data reached an all-time high of 2,218,082.000 Person in 1997 and a record low of 1,815,655.000 Person in 2024. Population: VR: Orenburg Region data remains active status in CEIC and is reported by Federal State Statistics Service. The data is categorized under Global Database’s Russian Federation – Table RU.GA002: Population: by Region.

About this dataset

Context

The dataset tabulates the Aleutians West Census Area population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Aleutians West Census Area across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Aleutians West Census Area was 5,160, a 1.38% increase year-by-year from 2022. Previously, in 2022, Aleutians West Census Area population was 5,090, a decline of 1.11% compared to a population of 5,147 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Aleutians West Census Area decreased by 301. In this period, the peak population was 5,825 in the year 2014. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Aleutians West Census Area is shown in this column.
• Year on Year Change: This column displays the change in Aleutians West Census Area population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Aleutians West Census Area Population by Year. You can refer the same here

The total increase (decrease) of the population is the sum of the natural increase (decrease) of the population and the migration increase (decrease) of the population. The natural increase (decrease) of the population is the difference between the number of live births and the number of deaths. Migration increase (decrease) of the population - the difference between the number of arrivals to a certain territory and the number of departed outside it.

About this dataset

Context

The dataset tabulates the Petersburg Census Area population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Petersburg Census Area across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Petersburg Census Area was 3,427, a 1.69% increase year-by-year from 2022. Previously, in 2022, Petersburg Census Area population was 3,370, a decline of 0.33% compared to a population of 3,381 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Petersburg Census Area decreased by 781. In this period, the peak population was 4,208 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Petersburg Census Area is shown in this column.
• Year on Year Change: This column displays the change in Petersburg Census Area population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Petersburg Census Area Population by Year. You can refer the same here

After a dramatic population decline, Steller sea lions have begun to recover throughout most of their range. However, Steller sea lions in the Western Aleutians and Commander Islands are continuing to decline. Comparing survival rates between regions with different population trends may provide insights into the factors driving the dynamics, but published data on vital rates have been extremely scarce, especially in regions where the populations are still declining. Fortunately, an unprecedented dataset of marked Steller sea lions at rookeries in the Russian Far East is available, allowing us to determine age and sex specific survival in sea lions up to 22 years old. We focused on survival rates in three areas in the Russian range with differing population trends: the Commander Islands (Medny Island rookery), Eastern Kamchatka (Kozlov Cape rookery) and the Kuril Islands (four rookeries). Survival rates differed between these three regions, though not necessarily as predicted by population trends. Pup survival was higher where the populations were declining (Medny Island) or not recovering (Kozlov Cape) than in all Kuril Island rookeries. The lowest adult (> 3 years old) female survival was found on Medny Island and this may be responsible for the continued population decline there. However, the highest adult survival was found at Kozlov Cape, not in the Kuril Islands where the population is increasing, so we suggest that differences in birth rates might be an important driver of these divergent population trends. High pup survival on the Commander Islands and Kamchatka Coast may be a consequence of less frequent (e.g. biennial) reproduction there, which may permit females that skip birth years to invest more in their offspring, leading to higher pup survival, but this hypothesis awaits measurement of birth rates in these areas. Resight history of Steller sea lions in the Russian Far EastData file contains annual resight history of Steller sea lions branded as pups between 1989 and 2008 and resighted between 1996 and 2011 at 6 major rookeries in the Russian Far East. Detailed information on data structure provided in read me file.data.csv

Globally, about 25 percent of the population is under 15 years of age and 10 percent is over 65 years of age. Africa has the youngest population worldwide. In Sub-Saharan Africa, more than 40 percent of the population is below 15 years, and only three percent are above 65, indicating the low life expectancy in several of the countries. In Europe, on the other hand, a higher share of the population is above 65 years than the population under 15 years. Fertility rates The high share of children and youth in Africa is connected to the high fertility rates on the continent. For instance, South Sudan and Niger have the highest population growth rates globally. However, about 50 percent of the world’s population live in countries with low fertility, where women have less than 2.1 children. Some countries in Europe, like Latvia and Lithuania, have experienced a population decline of one percent, and in the Cook Islands, it is even above two percent. In Europe, the majority of the population was previously working-aged adults with few dependents, but this trend is expected to reverse soon, and it is predicted that by 2050, the older population will outnumber the young in many developed countries. Growing global population As of 2025, there are 8.1 billion people living on the planet, and this is expected to reach more than nine billion before 2040. Moreover, the global population is expected to reach 10 billions around 2060, before slowing and then even falling slightly by 2100. As the population growth rates indicate, a significant share of the population increase will happen in Africa.

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy affecting white-tailed deer (Odocoileus virginianus), mule deer (Odocoileus hemionus), Rocky Mountain elk (Cervus elaphus nelsoni), and moose (Alces alces shirasi) in North America. In southeastern Wyoming average annual CWD prevalence in mule deer exceeds 20% and appears to contribute to regional population declines. We determined the effect of CWD on mule deer demography using age-specific, female-only, CWD transition matrix models to estimate the population growth rate (λ). Mule deer were captured from 2010–2014 in southern Converse County Wyoming, USA. Captured adult (≥ 1.5 years old) deer were tested ante-mortem for CWD using tonsil biopsies and monitored using radio telemetry. Mean annual survival rates of CWD-negative and CWD-positive deer were 0.76 and 0.32, respectively. Pregnancy and fawn recruitment were not observed to be influenced by CWD. We estimated λ = 0.79, indicating an annual population decline of 21% under current CWD prevalence levels. A model derived from the demography of only CWD-negative individuals yielded; λ = 1.00, indicating a stable population if CWD were absent. These findings support CWD as a significant contributor to mule deer population decline. Chronic wasting disease is difficult or impossible to eradicate with current tools, given significant environmental contamination, and at present our best recommendation for control of this disease is to minimize spread to new areas and naïve cervid populations.

This resource is a member of a series. The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2020 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.

Ukraine Population: Resident: Region: Chernihiv data was reported at 1,001,659.000 Person in Sep 2018. This records a decrease from the previous number of 1,003,313.000 Person for Aug 2018. Ukraine Population: Resident: Region: Chernihiv data is updated monthly, averaging 1,087,600.500 Person from Aug 2003 (Median) to Sep 2018, with 182 observations. The data reached an all-time high of 1,204,946.000 Person in Aug 2003 and a record low of 1,001,659.000 Person in Sep 2018. Ukraine Population: Resident: Region: Chernihiv data remains active status in CEIC and is reported by State Statistics Service of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.G003: Population: Resident: by Region.

Report of the Independent Review into the Decline of Koala Populations in Key Areas of NSW Report of the Independent Review into the Decline of Koala Populations in Key Areas of NSW

The TIGER/Line shapefiles and related database files (.dbf) are an extract of selected geographic and cartographic information from the U.S. Census Bureau's Master Address File / Topologically Integrated Geographic Encoding and Referencing (MAF/TIGER) Database (MTDB). The MTDB represents a seamless national file with no overlaps or gaps between parts, however, each TIGER/Line shapefile is designed to stand alone as an independent data set, or they can be combined to cover the entire nation. Census tracts are small, relatively permanent statistical subdivisions of a county or equivalent entity, and were defined by local participants as part of the 2010 Census Participant Statistical Areas Program. The Census Bureau delineated the census tracts in situations where no local participant existed or where all the potential participants declined to participate. The primary purpose of census tracts is to provide a stable set of geographic units for the presentation of census data and comparison back to previous decennial censuses. Census tracts generally have a population size between 1,200 and 8,000 people, with an optimum size of 4,000 people. When first delineated, census tracts were designed to be homogeneous with respect to population characteristics, economic status, and living conditions. The spatial size of census tracts varies widely depending on the density of settlement. Physical changes in street patterns caused by highway construction, new development, and so forth, may require boundary revisions. In addition, census tracts occasionally are split due to population growth, or combined as a result of substantial population decline. Census tract boundaries generally follow visible and identifiable features. They may follow legal boundaries such as minor civil division (MCD) or incorporated place boundaries in some States and situations to allow for census tract-to-governmental unit relationships where the governmental boundaries tend to remain unchanged between censuses. State and county boundaries always are census tract boundaries in the standard census geographic hierarchy. In a few rare instances, a census tract may consist of noncontiguous areas. These noncontiguous areas may occur where the census tracts are coextensive with all or parts of legal entities that are themselves noncontiguous. For the 2010 Census, the census tract code range of 9400 through 9499 was enforced for census tracts that include a majority American Indian population according to Census 2000 data and/or their area was primarily covered by federally recognized American Indian reservations and/or off-reservation trust lands; the code range 9800 through 9899 was enforced for those census tracts that contained little or no population and represented a relatively large special land use area such as a National Park, military installation, or a business/industrial park; and the code range 9900 through 9998 was enforced for those census tracts that contained only water area, no land area.