The Impact of COVID-19 on Veterans in America

County-Level Data on Veteran Cases and Proportion of Population

About this dataset

Welcome to the Kaggle dataset on The Impact of COVID-19 on Veterans in the United States! This dataset contains data on confirmed cases of COVID-19 in counties across the United States, as well as information on the percentage of each county's population that are veterans. With this dataset, you can investigate how the pandemic has impacted veterans specifically, and compare veteran case rates to the general population. How do veteran cases differ across age groups? Are there any geographical patterns? What can we learn about risk factors for COVID-19 among veterans? Download the dataset and explore for yourself today!

How to use the dataset

This dataset includes information on the number of confirmed cases of COVID-19 by county, as well as the percentage of the population in each county that are veterans. This data can be used to examine the relationship between veteran cases and the proportion of population who are veterans.

To do this, simply look at the 'CASES' and 'VET_CASES' columns for each county. The 'CASES' column represents the total number of confirmed cases of COVID-19 in that county, while the 'VET_CASES' column represents the number of confirmed cases among veterans. To compare these two values, simply divide 'VET_CASES' by 'CASES'. This will give you a ratio of veteran cases to total cases for each county.

You can then use this ratio to compare counties and see which ones have a higher proportion of veteran cases. This data can be used to help understand where more outreach may be needed to support veterans during this pandemic

Research Ideas

• Find the correlation between the number of veterans in a county and the number of confirmed cases of COVID-19.
• Find the counties with the highest percentage of veterans and the lowest number of confirmed cases of COVID-19.
• Predict how many veterans in a county will contract COVID-19 based on the percentage of veterans in the population

Columns

File: CountyVACOVID.csv | Column name | Description | |:---------------------------|:-----------------------------------------------------------------------------------------------------------------------| | FIPS | Federal Information Processing Standards code that uniquely identifies counties within the USA. (String) | | COUNTY | County name. (String) | | STATE | State name. (String) | | POP | County population. (Integer) | | VETS | Number of veterans in the county. (Integer) | | VET_PERCENT | Percentage of the population that are veterans. (Float) | | CASES | Number of confirmed cases of COVID-19 in the county. (Integer) | | YESTER_CASES | Number of confirmed cases of COVID-19 in the county from the previous day. (Integer) | | VET_CASES | Number of confirmed cases of COVID-19 in veterans in the county. (Integer) | | VET_YESTER | Number of confirmed cases of COVID-19 in veterans in the county from the previous day. (Integer) | | LOWER_Hospitalizations | Lower bound of the 95% confidence interval for the number of hospitalizations due to COVID-19 in the county. (Integer) | | UPPER_Hospitalizations | Upper bound of the 95% confidence interval for the number of hospitalizations due to COVID-19 in the county. (Integer) | | DATE | Date of data. (Date) |

File: VAChart.csv | Column name | Description | |:------------------------|:----------------------------------------------------------------------------------| | DATE | Date of data. (Date) | | US Cases | The number of confirmed cases of COVID-19 in the United States. (Integer) | | **New US ...

Notes: "Total Number of Veterans" represents FY 2021 projected Veteran counts from VA's Veteran Population Projection Model 2020 (VetPop20). These projections represent living Veterans as of 9/30/2021 and are made with the assumption that Veterans are not missing information (e.g., sex, age, etc.). "Veteran VA Users" represents historical Veteran VA user counts from VA's United States Veterans Eligibility Trends and Statistics 2021 (USVETS 2021). These counts represent Veterans who used any VA benefit or service during FY 2021 (includes both living and deceased Veterans as of end of FY 2021). "Veteran VA Healthcare Users" represents historical Veteran VA healthcare user counts from VA's United States Veterans Eligibility Trends and Statistics 2021 (USVETS 2021). These counts represent Veterans who used VA healthcare during FY 2021 (includes both living and deceased Veterans as of end of FY 2021). "Veteran VA Users" includes Veteran users of VA healthcare or any other VA benefit or service. There are 1,458 Veteran VA Users not shown in the table below whose sex is missing. Of these, 1,360 are missing age. There are 1,387 Veteran VA Healthcare Users not shown in the table below whose sex is missing. Of these, 1,360 are missing age. Sources: USVETS 2021 and VetPop20 Effective Date: 9/30/2021

About this dataset

Context

The dataset tabulates the Veteran town 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 Veteran town 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 Veteran town was 3,235, a 0.61% decrease year-by-year from 2022. Previously, in 2022, Veteran town population was 3,255, a decline of 1.30% compared to a population of 3,298 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Veteran town decreased by 41. In this period, the peak population was 3,352 in the year 2011. 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 Veteran town is shown in this column.
• Year on Year Change: This column displays the change in Veteran town 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 Veteran town Population by Year. You can refer the same here

Notes: "Total Number of Veterans" represents FY 2021 projected Veteran counts from VA's Veteran Population Projection Model 2020 (VetPop20). These projections represent living Veterans as of 9/30/2021 and are made with the assumption that Veterans are not missing information (e.g., race, etc.). "Veteran VA Users" represents historical Veteran VA user counts from VA's United States Veterans Eligibility Trends and Statistics 2021 (USVETS 2021). These counts represent Veterans who used any VA benefit or service during FY 2021 (includes both living and deceased Veterans as of end of FY 2021). "Veteran VA Healthcare Users" represents historical Veteran VA healthcare user counts from VA's United States Veterans Eligibility Trends and Statistics 2021 (USVETS 2021). These counts represent Veterans who used VA healthcare during FY 2021 (includes both living and deceased Veterans as of end of FY 2021). "Veteran VA Users" includes Veteran users of VA healthcare or any other VA benefit or service. Sources: USVETS 2021 and VetPop20 Effective Date: 9/30/2021

This table provides state-level estimates of the percentage of Veterans who were VA pension recipients at the end of the fiscal years 2019, 2020, 2021, and 2023. Percents are rounded to the nearest tenth. Percents for fiscal year (FY) 2022 are not available by state. Prepared by the National Center for Veterans Analysis and Statistics. Sources: Department of Veterans Affairs, Office of Enterprise Integration, Veteran Population Projection Model (VetPop) 2020, Veteran Object FY 2023 data, United States Veterans Eligibility Trends & Statistics (USVETS) 2019, 2020, and 2021 data; Veterans Benefits Administration, VETSNET FY 2019, FY 2020, FY 2021, and FY 2023 pension data.

To show count of Post 9/11 Veterans (Living only) by County for the creation of a heat map to align with Wounded Warrior Projects’ programming.

This layer shows veteran status of adults (18+) broken down by age and sex. This is shown by tract, county, and state boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of adults who are veterans. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2019-2023ACS Table(s): B21001Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 12, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. For more information about ACS layers, visit the FAQ. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases, specifically, the National Sub-State Geography Database (named tlgdb_(year)_a_us_substategeo.gdb). Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines erased for cartographic and mapping purposes. For census tracts, the water cutouts are derived from a subset of the 2020 Areal Hydrography boundaries offered by TIGER. Water bodies and rivers which are 50 million square meters or larger (mid to large sized water bodies) are erased from the tract level boundaries, as well as additional important features. For state and county boundaries, the water and coastlines are derived from the coastlines of the 2023 500k TIGER Cartographic Boundary Shapefiles. These are erased to more accurately portray the coastlines and Great Lakes. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters).The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -4444...) have been set to null, with the exception of -5555... which has been set to zero. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small.

This comprehensive report chronicles the history of women in the military and as Veterans, profiles the characteristics of women Veterans in 2009, illustrates how women Veterans in 2009 utilized some of the major benefits and services offered by the Department of Veterans Affairs (VA), and discusses the future of women Veterans in relation to VA. The goal of this report is to gain an understanding of who our women Veterans are, how their military service affects their post-military lives, and how they can be better served based on these insights.

Note: "Total Number of Veterans" represents FY 2020 projected Veteran counts from VA's Veteran Population Projection Model 2018 (VetPop18). These projections are made with the assumption that Veterans are not missing information (e.g. age, sex, etc.). Note: "Veteran VA Users" and "Veteran VA Healthcare Users" represent historical Veteran counts from VA's United States Veterans Eligibility Trends and Statistics 2020 (USVETS 2020). Note: "Veteran VA Users" includes Veteran users of VA healthcare or any other VA benefit or service. Note: There are 4,214 Veteran VA Users not shown in the table below whose sex is missing. Of these, 4,126 are missing age. There are 4,158 Veteran VA Healthcare Users not shown in the table below whose sex is missing. Of these, 4,125 are missing age. Sources: USVETS 2020 and VetPop18

This service contains the 2018-2022 release of data from the American Community Survey (ACS) 5-year data about Veteran Status, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of the civilian population over the age of 18 that are Veterans.To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2018-2022ACS Table(s): DP02Data downloaded from: CensusBureau's API for American Community Survey Date of API call: January 18, 2024National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:Boundaries come from the Cartographic Boundaries via US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates, and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto Rico. The Counties (and equivalent) layer contains 3221 records - all counties and equivalent, Washington D.C., and Puerto Rico municipios. See Areas Published. Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells.Margin of error (MOE) values of -555555555 in the API (or "*****" (five asterisks) on data.census.gov) are displayed as 0 in this dataset. The estimates associated with these MOEs have been controlled to independent counts in the ACS weighting and have zero sampling error. So, the MOEs are effectively zeroes, and are treated as zeroes in MOE calculations. Other negative values on the API, such as -222222222, -666666666, -888888888, and -999999999, all represent estimates or MOEs that can't be calculated or can't be published, usually due to small sample sizes. All of these are rendered in this dataset as null (blank) values.

Context

Veteran Employment Outcomes (VEO) are new experimental U.S. Census Bureau statistics on labor market outcomes for recently discharged Army veterans. These statistics are tabulated by military specialization, service characteristics, employer industry (if employed), and veteran demographics. They are generated by matching service member information with a national database of jobs, using state-of-the-art confidentiality protection mechanisms to protect the underlying data.

https://lehd.ces.census.gov/data/veo_experimental.html

Content

"The VEO are made possible through data sharing partnerships between the U.S. Army, State Labor Market Information offices, and the U.S. Census Bureau. VEO data are currently available at the state and national level."

"Veteran Employment Outcomes (VEO) are experimental tabulations developed by the Longitudinal Employer-Household Dynamics (LEHD) program in collaboration with the U.S. Army and state agencies. VEO data provides earnings and employment outcomes for Army veterans by rank and military occupation, as well as veteran and employer characteristics. VEO are currently released as a research data product in "experimental" form."

"The source of veteran information in the VEO is administrative record data from the Department of the Army, Office of Economic and Manpower Analysis. This personnel data contains fields on service member characteristics, such as service start and end dates, occupation, pay grade, characteristics at entry (e.g. education and test scores), and demographic characteristics (e.g. sex, race, and ethnicity). Once service member records are transferred to the Census Bureau, personally-identifying information is stripped and veterans are assigned a Protected Identification Key (PIK) that allows for them to be matched with their employment outcomes in Census Bureau jobs data."

Earnings, and Employment Concepts

Earnings "Earnings are total annual earnings for attached workers from all jobs, converted to 2018 dollars using the CPI-U. For the annual earnings tabulations, we impose two labor force attachment restrictions. First, we drop veterans who earn less than the annual equivalent of full-time work at the prevailing federal minimum wage. Additionally, we drop veterans with two or more quarters with no earnings in the reference year. These workers are likely to be either marginally attached to the labor force or employed in non-covered employment."

Employment

"While most VEO tabulations include earnings from all jobs, tabulations by employer characteristics only consider the veteran's main job for that year. Main jobs are defined as the job for which veterans had the highest earnings in the reference year. To attach employer characteristics to that job, we assign industry and geography from the highest earnings quarter with that employer in the year. For multi-establishment firms, we use LEHD unit-to-worker imputations to assign workers to establishments, and then assign industry and geography."

https://lehd.ces.census.gov/data/veo_experimental.html

Acknowledgements

United States Census Bureau

https://lehd.ces.census.gov/data/veo_experimental.html

Photo by Robert Linder on Unsplash

Inspiration

U.S. Veterans.

SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES VETERAN STATUS - DP02 Universe - Civilian population 18 Year and over Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 Veteran status is used to identify people with active duty military service and service in the military Reserves and the National Guard. Veterans are men and women who have served (even for a short time), but are not currently serving, on active duty in the U.S. Army, Navy, Air Force, Marine Corps, or the Coast Guard, or who served in the U.S. Merchant Marine during World War II. People who served in the National Guard or Reserves are classified as veterans only if they were ever called or ordered to active duty, not counting the 4-6 months for initial training or yearly summer camps.

The Department of Veterans Affairs provides official estimates and projections of the Veteran population using the Veteran Population Projection Model (VetPop). Based on the latest model VetPop2023 and the most recent national survey estimates from the 2023 American Community Survey 1-Year (ACS) data, the projected number of Veterans living in the 50 states, DC and Puerto Rico for fiscal years, 2023 to 2025, are allocated to Urban and Rural areas. As defined by the Census Bureau, Rural encompasses all population, housing, and territory not included within an Urban area (https://www.census.gov/programs-surveys/geography/guidance/geo-areas/urban-rural.html). This table contains the Veteran estimates by urban/rural, sex and age group. Note: rounding to the nearest 1,000 is always appropriate for VetPop estimates.

Graph and download economic data for Population Level - Veterans, Vietnam-Era and Earlier Wartime Periods, 18 Years and over (LNU00077884) from Sep 2008 to Sep 2025 about korean war, Vietnam Era, World War, 18 years +, veterans, civilian, population, and USA.

This data set consists of one row per federal fiscal year (FY) from FY 2005 - FY 2019, and reports the number and percent of users each of seven VA programs for Veterans who were in service at any time between August 2, 1990, and September 10, 2001, the dates of the Pre-9/11 Gulf War era. The denominator of percent is the number of living Veterans in the FY. The number and percent of users is cumulative since FY 2005. Thus, for example FY 2006 data includes all Veterans who served in the era, were alive at some time during FY 2006 and participated in the program at any time during FY 2005 and FY 2006.

Data from America's War factsheet with only those who served and living

Number of life insurance policyholders for each administered life insurance program listed by state. Data is current as of 12/31/11. All programs are closed to new issues except for Service-Disabled Veterans' Insurance and Veterans' Mortgage Life Insurance. United States Government Life Insurance was issued to WWI military personnel and Veterans. National Service Life Insurance was established to meet the needs of WWII military personnel and Veterans. Veterans' Special Life Insurance was issued to Korean War-era Veterans. Veterans' Reopened Insurance provides coverage to certain classes of disabled Veterans from WWII and the Korean conflict who had dropped their government life insurance coverage. Service-Disabled Veterans' Insurance was established in 1951 and is available to Veterans with service-connected disabilities. Veterans' Mortgage Life Insurance was established in 1971 to provide mortgage protection life insurance to severely disabled Veterans who have received grants for the purchase of specially-adapted housing.

About this dataset

Context

The dataset tabulates the Iron Gate 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 Iron Gate 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 Iron Gate was 313, a 1.57% decrease year-by-year from 2021. Previously, in 2021, Iron Gate population was 318, a decline of 0.93% compared to a population of 321 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Iron Gate decreased by 83. In this period, the peak population was 396 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 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 Iron Gate is shown in this column.
• Year on Year Change: This column displays the change in Iron Gate 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 Iron Gate Population by Year. You can refer the same here

A dataset to advance the study of life-cycle interactions of biomedical and socioeconomic factors in the aging process. The EI project has assembled a variety of large datasets covering the life histories of approximately 39,616 white male volunteers (drawn from a random sample of 331 companies) who served in the Union Army (UA), and of about 6,000 African-American veterans from 51 randomly selected United States Colored Troops companies (USCT). Their military records were linked to pension and medical records that detailed the soldiers������?? health status and socioeconomic and family characteristics. Each soldier was searched for in the US decennial census for the years in which they were most likely to be found alive (1850, 1860, 1880, 1900, 1910). In addition, a sample consisting of 70,000 men examined for service in the Union Army between September 1864 and April 1865 has been assembled and linked only to census records. These records will be useful for life-cycle comparisons of those accepted and rejected for service. Military Data: The military service and wartime medical histories of the UA and USCT men were collected from the Union Army and United States Colored Troops military service records, carded medical records, and other wartime documents. Pension Data: Wherever possible, the UA and USCT samples have been linked to pension records, including surgeon''''s certificates. About 70% of men in the Union Army sample have a pension. These records provide the bulk of the socioeconomic and demographic information on these men from the late 1800s through the early 1900s, including family structure and employment information. In addition, the surgeon''''s certificates provide rich medical histories, with an average of 5 examinations per linked recruit for the UA, and about 2.5 exams per USCT recruit. Census Data: Both early and late-age familial and socioeconomic information is collected from the manuscript schedules of the federal censuses of 1850, 1860, 1870 (incomplete), 1880, 1900, and 1910. Data Availability: All of the datasets (Military Union Army; linked Census; Surgeon''''s Certificates; Examination Records, and supporting ecological and environmental variables) are publicly available from ICPSR. In addition, copies on CD-ROM may be obtained from the CPE, which also maintains an interactive Internet Data Archive and Documentation Library, which can be accessed on the Project Website. * Dates of Study: 1850-1910 * Study Features: Longitudinal, Minority Oversamples * Sample Size: ** Union Army: 35,747 ** Colored Troops: 6,187 ** Examination Sample: 70,800 ICPSR Link: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06836

About this dataset

Context

The dataset tabulates the James City County 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 James City County 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 James City County was 81,199, a 1.61% increase year-by-year from 2021. Previously, in 2021, James City County population was 79,914, an increase of 1.83% compared to a population of 78,478 in 2020. Over the last 20 plus years, between 2000 and 2022, population of James City County increased by 32,694. In this period, the peak population was 81,199 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 James City County is shown in this column.
• Year on Year Change: This column displays the change in James City County 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 James City County Population by Year. You can refer the same here