This statistic shows the 20 countries with the highest population growth rate in 2024. In SouthSudan, the population grew by about 4.65 percent compared to the previous year, making it the country with the highest population growth rate in 2024. The global population Today, the global population amounts to around 7 billion people, i.e. the total number of living humans on Earth. More than half of the global population is living in Asia, while one quarter of the global population resides in Africa. High fertility rates in Africa and Asia, a decline in the mortality rates and an increase in the median age of the world population all contribute to the global population growth. Statistics show that the global population is subject to increase by almost 4 billion people by 2100. The global population growth is a direct result of people living longer because of better living conditions and a healthier nutrition. Three out of five of the most populous countries in the world are located in Asia. Ultimately the highest population growth rate is also found there, the country with the highest population growth rate is Syria. This could be due to a low infant mortality rate in Syria or the ever -expanding tourism sector.

All the African countries registered a positive population growth in 2023, except for Seychelles and Mauritius. Niger had the highest population growth rate at nearly 3.7 percent compared to the previous year. The Democratic Republic of Congo, Chad, Mali, Somalia, and Angola followed, recording over three percent growth each. The African population has been increasing considerably in the last decades and is expected to nearly double by 2050. This is due to several factors, including the rising life expectancy and the high fertility rates registered on the continent.

About this dataset

Context

The dataset tabulates the Rapid City 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 Rapid City 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 Rapid City was 79,404, a 0.87% increase year-by-year from 2022. Previously, in 2022, Rapid City population was 78,716, an increase of 2.57% compared to a population of 76,743 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Rapid City increased by 18,495. In this period, the peak population was 79,404 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. 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 Rapid City is shown in this column.
• Year on Year Change: This column displays the change in Rapid City 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 Rapid City Population by Year. You can refer the same here

Growth rates are highest in the Middle East, Africa, and parts of Latin America. Populations are actually declining in some developed countries, especially in eastern Europe.Source: World Bank

This statistic shows the top twenty-five fastest growing counties in the United States as of July 1, 2019, by change in population from April 1, 2010. On July 1, 2019, the fastest growing county with 10,000 or more population in the United States was Williams County in North Dakota with a growth rate of 67.8 percent.

Historical chart and dataset showing U.S. population growth rate by year from 1961 to 2023.

Theory suggests that the drivers of demographic variation and local adaptation are shared and may feedback on one other. Despite some evidence for these links in controlled settings, the relationship between local adaptation and demography remains largely unexplored in natural conditions. Using 10 years of demographic data and two reciprocal transplant experiments, we tested predictions about the relationship between the magnitude of local adaptation and demographic variation (population growth rates and their elasticities to vital rates) across 10 populations of a well-studied annual plant. In both years, we found a strong unimodal relationship between mean home-away local adaptation and stochastic population growth rates. Other predicted links were either weakly or not supported by our data. Our results suggest that declining and rapidly growing populations exhibit reduced local adaptation, potentially due to maladaptation and relaxed selection, respectively., This dataset includes long-term data collected using observations and environmetnal sensors, data on population dynamics derived from field census data, and data from 2 years of reciprocal transplants in field conditions. Data describing population dynamics have been processed from raw census data using matrix population models. All other data processing is performed using code that is archived along with the data., Annotated code necessary to reproduce the analyses and figures presented in the associated manuscript are included in this archive., # Data from: Local adaptation is highest in populations with stable long-term growth

Lauren N. Carley et al.

lauren.n.carley@gmail.com

STRUCTURE OF THIS ARCHIVE:

Details on the purpose of each file in these folders, and their subdirectories, is provided below, following the general outline:

• Clarkia-LTREB-transplant-archive/
  • README.txt
  • 1-data/
  • 2-analyses/
  • 2a-seed-prediction/
  • 2b-aster/
  • 2c-dist-calcs/
    • out/
  • 2d-dist-analyses/
  • 2e-permutation-tests/
    • Fdists/
  • 3-figures/
  • supplemental/

NOTE: Throughout the whole directory, variables in datasets are unitless unless otherwise defined, and "NA" values represent missing data unless otherwise defined.

Clarkia-LTREB-transplant-archive-R2/

This directory contains all of the other subdirectories, which take you through data processing, modeling, and analysis step by step.

It also contains one file:

README.txt

You are curren...

Over the period from 2019 to 2021, the population of the Ingushetia Republic in Russia increased by nearly 5.4 percent. Furthermore, the number of inhabitants in the Chechen Republic rose by approximately 4.1 percent.

In 2023, it is estimated that the BRICS countries have a combined population of 3.25 billion people, which is over 40 percent of the world population. The majority of these people live in either China or India, which have a population of more than 1.4 billion people each, while the other three countries have a combined population of just under 420 million. Comparisons Although the BRICS countries are considered the five foremost emerging economies, they are all at various stages of the demographic transition and have different levels of population development. For all of modern history, China has had the world's largest population, but rapidly dropping fertility and birth rates in recent decades mean that its population growth has slowed. In contrast, India's population growth remains much higher, and it is expected to overtake China in the next few years to become the world's most populous country. The fastest growing population in the BRICS bloc, however, is that of South Africa, which is at the earliest stage of demographic development. Russia, is the only BRICS country whose population is currently in decline, and it has been experiencing a consistent natural decline for most of the past three decades. Growing populations = growing opportunities Between 2000 and 2026, the populations of the BRICS countries is expected to grow by 625 million people, and the majority of this will be in India and China. As the economies of these two countries grow, so too do living standards and disposable income; this has resulted in the world's two most populous countries emerging as two of the most profitable markets in the world. China, sometimes called the "world's factory" has seen a rapid growth in its middle class, increased potential of its low-tier market, and its manufacturing sector is now transitioning to the production of more technologically advanced and high-end goods to meet its domestic demand.

This statistics shows the top 20 fastest growing large-metropolitan areas in the United States between July 1st, 2022 and July 1st, 2023. The total population in the Wilmington, North Carolina, metropolitan area increased by 0.05 percent from 2022 to 2023.

India population growth rate for 2023 was 0.88%, a 0.09% increase from 2022.

<ul style='margin-top:20px;'>

<li>India population growth rate for 2022 was <strong>0.79%</strong>, a <strong>0.03% decline</strong> from 2021.</li>
<li>India population growth rate for 2021 was <strong>0.82%</strong>, a <strong>0.15% decline</strong> from 2020.</li>
<li>India population growth rate for 2020 was <strong>0.97%</strong>, a <strong>0.07% decline</strong> from 2019.</li>
</ul>Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.

Historical chart and dataset showing World population growth rate by year from 1961 to 2023.

This table shows the tract-level change in population for all Tennessee census tracts between two 5-year American Community Survey releases: 2007-2011 and 2012-2016. Each tract is also ranked to indicate its change in growth compared to all other census tracts in the state; the largest growth being ranked one and tracts with the largest declines ranked lowest.A test of statistical significance is included. Tracts with statistically significant changes in population at the 90% confidence level are noted in the 'Statistically Significant' field (STAT_SIGNIFICANT) as being "TRUE". Tracts with population change that could fall within the survey's margin of error are categorized as "FALSE".

Historical chart and dataset showing Nigeria population growth rate by year from 1961 to 2023.

This table shows the tract-level change in population for all Tennessee census tracts between two 5-year American Community Survey releases: 2007-2011 and 2012-2016. Each tract is also ranked to indicate its change in growth compared to all other census tracts in the state; the largest growth being ranked one and tracts with the largest declines ranked lowest.A test of statistical significance is included. Tracts with statistically significant changes in population at the 90% confidence level are noted in the 'Statistically Significant' field (STAT_SIGNIFICANT) as being "TRUE". Tracts with population change that could fall within the survey's margin of error are categorized as "FALSE".

The methodology used to produce these projections differs from ICLUS v2.0 (https://cfpub.epa.gov/ncea/iclus/recordisplay.cfm?deid=322479). The demographic components of change (i.e., rates of fertility and mortality) for ICLUS v2.1 were taken directly from the Wittgenstein Centre Data Explorer (http://witt.null2.net/shiny/wic/). These projections were produced more recently than the Census projections used in ICLUS v2.0, and incorporate more recent observations of population change. SSP2 is a “middle-of-the-road” projection, where social, economic and technological trends do not shift markedly from historical patterns, resulting in a U.S. population of 455 million people by 2100. Domestic migration trends remain largely consistent with the recent past, however the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. The SSP5 narrative describes a rapidly growing and flourishing global economy that remains heavily dependent on fossil fuels, and a U.S. population that exceeds 730 million by 2100. ICLUS v2.1 land use projections under SSP5 result in a considerably larger expansion of developed lands relative to SSP2. The the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. RCP4.5 assumes that global greenhoue gas emissions increase into the latter part of the century, before leveling off and eventually stabilizing by 2100 as a result of various climate change policies. RCP8.5 assumes that global greenhoue gas emissions increase through the year 2100.

About this dataset

Context

The dataset tabulates the Rapid River township 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 Rapid River township 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 2022, the population of Rapid River township was 1,268, a 1.52% increase year-by-year from 2021. Previously, in 2021, Rapid River township population was 1,249, an increase of 0.24% compared to a population of 1,246 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Rapid River township increased by 262. In this period, the peak population was 1,268 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. 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 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Rapid River township is shown in this column.
• Year on Year Change: This column displays the change in Rapid River township 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 Rapid River township Population by Year. You can refer the same here

BackgroundSouth Asians are a rapidly growing population in the United States. Breast cancer is a major concern among South Asian American women, who are an understudied population. We established the South Asian Breast Cancer (SABCa) study in New Jersey during early 2020 to gain insights into their breast cancer-related health attitudes. Shortly after we started planning for the study, the COVID-19 disease spread throughout the world. In this paper, we describe our experiences and lessons learned from recruiting study participants by partnering with New Jersey’s community organizations during the COVID-19 pandemic.MethodsWe used a cross-sectional design. We contacted 12 community organizations and 7 (58%) disseminated our study information. However, these organizations became considerably busy with pandemic-related needs. Therefore, we had to pivot to alternative recruitment strategies through community radio, Rutgers Cancer Institute of New Jersey’s Community Outreach and Engagement Program, and Rutgers Cooperative Extension’s community health programs. We recruited participants through these alternative strategies, obtained written informed consent, and collected demographic information using a structured survey.ResultsTwenty five women expressed interest in the study, of which 22 (88%) participated. Nine (41%) participants learned about the study through the radio, 5 (23%) through these participants, 1 (4.5%) through a non-radio community organization, and 7 (32%) through community health programs. Two (9%) participants heard about the study from their spouse. All participants were born outside the US, their average age was 52.4 years (range: 39–72 years), and they have lived in the US for an average of 26 years (range: 5–51 years).ConclusionPivoting to alternative strategies were crucial for successful recruitment. Findings suggest the significant potential of broadcast media for community-based recruitment. Family dynamics and the community’s trust in our partners also encouraged participation. Such strategies must be considered when working with understudied populations.

As the contemporary economy continues to become ever more focused on services, and incomes in the developing world rise, a rising majority of the global population are becoming urban dwellers. Read More

The West Africa Coastal Vulnerability Mapping: Population Projections, 2030 and 2050 data set is based on an unreleased working version of the Gridded Population of the World (GPW), Version 4, year 2010 population count raster but at a coarser 5 arc-minute resolution. Bryan Jones of Baruch College produced country-level projections based on the Shared Socioeconomic Pathway 4 (SSP4). SSP4 reflects a divided world where cities that have relatively high standards of living, are attractive to internal and international migrants. In low income countries, rapidly growing rural populations live on shrinking areas of arable land due to both high population pressure and expansion of large-scale mechanized farming by international agricultural firms. This pressure induces large migration flow to the cities, contributing to fast urbanization, although urban areas do not provide many opportUnities for the poor and there is a massive expansion of slums and squatter settlements. This scenario may not be the most likely for the West Africa region, but it has internal coherence and is at least plausible.