The population count of Napa County, CA was 140,530 in 2018. The population count of Solano County, CA was 438,530 in 2018. The population count of Washoe County, NV was 450,486 in 2018.

Population

Population Change

Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API - Notes:

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Demographics and Population Datasets Involving Napa County, CA or Solano County, CA or Washoe County, NV

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    Napa County and California Population Totals 2011-2020

    data.countyofnapa.org | Last Updated 2023-07-26T16:19:55.000Z

    Data Source: CA Department of Finance Data: Population estimates for January 1, 2011, through January 1, 2020. The population estimates benchmark for April 1, 2010 is also provided. Citation: State of California, Department of Finance, E-4 Population Estimates for Cities, Counties, and the State, 2011-2020, with 2010 Census Benchmark. Sacramento, California, May 2022. For detailed information on methodology and other data considerations, visit: https://dof.ca.gov/Forecasting/Demographics/Estimates/e-4-population-estimates-for-cities-counties-and-the-state-2011-2020-with-2010-census-benchmark-new/

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    Population Projections for Napa County

    data.countyofnapa.org | Last Updated 2024-02-21T23:24:18.000Z

    Data Source: CA Department of Finance, Demographic Research Unit Report P-3: Population Projections, California, 2010-2060 (Baseline 2019 Population Projections; Vintage 2020 Release). Sacramento: California. July 2021. This data biography shares the how, who, what, where, when, and why about this dataset. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org. Data dashboard featuring this data: Napa County Demographics https://data.countyofnapa.org/stories/s/bu3n-fytj How was the data collected? Population projections use the following demographic balancing equation: Current Population = Previous Population + (Births - Deaths) +Net Migration Previous Population: the starting point for the population projection estimates is the 2020 US Census, informed by the Population Estimates Program data. Births and Deaths: birth and death totals came from the California Department of Public Health, Vital Statistics Branch, which maintains birth and death records for California. Net Migration: multiple sources of administrative records were used to estimate net migration, including driver’s license address changes, IRS tax return data, Medicare and Medi-Cal enrollment, federal immigration reports, elementary school enrollments, and group quarters population. Who was included and excluded from the data? Previous Population: The goal of the US Census is to reflect all populations residing in a given geographic area. Results of two analyses done by the US Census Bureau showed that the 2020 Census total population counts were consistent with recent counts despite the challenges added by the pandemic. However, some populations were undercounted (the Black or African American population, the American Indian or Alaska Native population living on a reservation, the Hispanic or Latino population, and people who reported being of Some Other Race), and some were overcounted (the Non-Hispanic White population and the Asian population). Children, especially children younger than 4, were also undercounted. Births and Deaths: Birth records include all people who are born in California as well as births to California residents that happened out of state. Death records include people who died while in California, as well as deaths of California residents that occurred out of state. Because birth and death record data comes from a registration process, the demographic information provided may not be accurate or complete. Net Migration: each of the multiple sources of administrative records that were used to estimate net migration include and exclude different groups. For details about methodology, see https://dof.ca.gov/wp-content/uploads/sites/352/2023/07/Projections_Methodology.pdf. Where was the data collected?  Data is collected throughout California. This subset of data includes Napa County. When was the data collected? This subset of Napa County data is from Report P-3: Population Projections, California, 2010-2060 (Baseline 2019 Population Projections; Vintage 2020 Release). Sacramento: California. July 2021. These 2019 baseline projections incorporate the latest historical population, birth, death, and migration data available as of July 1, 2020. Historical trends from 1990 through 2020 for births, deaths, and migration are examined. County populations by age, sex, and race/ethnicity are projected to 2060. Why was the data collected?  The population projections were prepared under the mandate of the California Government Code (Cal. Gov't Code § 13073, 13073.5). Where can I learn more about this data? https://dof.ca.gov/Forecasting/Demographics/Projections/ https://dof.ca.gov/wp-content/uploads/sites/352/Forecasting/Demographics/Documents/P3_Dictionary.txt https://dof.ca.gov/wp-content/uploads/sites/352/2023/07/Proj

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    Voter Participation in Statewide General Elections

    data.countyofnapa.org | Last Updated 2024-02-07T18:38:27.000Z

    Data Source: CA Secretary of State This data biography shares the how, who, what, where, when, and why about this dataset. We, the epidemiology team at Napa County Health and Human Services Agency, Public Health Division, created it to help you understand where the data we analyze and share comes from. If you have any further questions, we can be reached at epidemiology@countyofnapa.org. Data dashboard featuring this data: Demographics https://data.countyofnapa.org/stories/s/bu3n-fytj How was the data collected? The California Secretary of State's Elections Division is responsible for maintaining a database of all registered voters as well as coordinating the counting of votes after elections. Voter participation is defined here as the percentage of eligible voters who actually voted. Who was included and excluded from the data? The term "eligible voters" refers to the population of US citizens aged 18 years or older who currently reside in the voting jurisdiction and who are not in prison or on parole for a felony and who have not been declared mentally incompetent. Where was the data collected?  Voter registration data and election results are collected throughout California. This subset of data includes Napa County and California. How often is the data collected? Statewide General Elections are held the Tuesday after the first Monday in November on even years. Where can I learn more about this data? https://www.sos.ca.gov/elections/prior-elections/statewide-election-results

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    Vital Signs: Migration - Bay Area

    data.bayareametro.gov | Last Updated 2019-10-25T20:40:04.000Z

    VITAL SIGNS INDICATOR Migration (EQ4) FULL MEASURE NAME Migration flows LAST UPDATED December 2018 DESCRIPTION Migration refers to the movement of people from one location to another, typically crossing a county or regional boundary. Migration captures both voluntary relocation – for example, moving to another region for a better job or lower home prices – and involuntary relocation as a result of displacement. The dataset includes metropolitan area, regional, and county tables. DATA SOURCE American Community Survey County-to-County Migration Flows 2012-2015 5-year rolling average http://www.census.gov/topics/population/migration/data/tables.All.html CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) Data for migration comes from the American Community Survey; county-to-county flow datasets experience a longer lag time than other standard datasets available in FactFinder. 5-year rolling average data was used for migration for all geographies, as the Census Bureau does not release 1-year annual data. Data is not available at any geography below the county level; note that flows that are relatively small on the county level are often within the margin of error. The metropolitan area comparison was performed for the nine-county San Francisco Bay Area, in addition to the primary MSAs for the nine other major metropolitan areas, by aggregating county data based on current metropolitan area boundaries. Data prior to 2011 is not available on Vital Signs due to inconsistent Census formats and a lack of net migration statistics for prior years. Only counties with a non-negligible flow are shown in the data; all other pairs can be assumed to have zero migration. Given that the vast majority of migration out of the region was to other counties in California, California counties were bundled into the following regions for simplicity: Bay Area: Alameda, Contra Costa, Marin, Napa, San Francisco, San Mateo, Santa Clara, Solano, Sonoma Central Coast: Monterey, San Benito, San Luis Obispo, Santa Barbara, Santa Cruz Central Valley: Fresno, Kern, Kings, Madera, Merced, Tulare Los Angeles + Inland Empire: Imperial, Los Angeles, Orange, Riverside, San Bernardino, Ventura Sacramento: El Dorado, Placer, Sacramento, Sutter, Yolo, Yuba San Diego: San Diego San Joaquin Valley: San Joaquin, Stanislaus Rural: all other counties (23) One key limitation of the American Community Survey migration data is that it is not able to track emigration (movement of current U.S. residents to other countries). This is despite the fact that it is able to quantify immigration (movement of foreign residents to the U.S.), generally by continent of origin. Thus the Vital Signs analysis focuses primarily on net domestic migration, while still specifically citing in-migration flows from countries abroad based on data availability.

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    Displacement Risk

    data.bayareametro.gov | Last Updated 2023-07-27T19:10:55.000Z

    Displacement Typologies, developed by the University of California, Berkeley's Urban Displacement Project (UDP), use housing and demographic data from the United States Census, as well as real estate market data from Zillow to classify a metropolitan area's census tracts into eight distinct categories. Each category represents a stage of neighborhood change, although should not be taken to represent a linear trajectory or to predetermine neighborhood outcomes. Instead, typologies allow practitioners and researchers to see patterns in their regions over a specified time period, and are meant to start conversations about how policy interventions and investment could respond and support more equitable development. It is important to note that in considering the entire metropolitan region, UDP's typologies classify both low- and middle-income neighborhoods at risk of or experiencing displacement or gentrification, as well as high-income neighborhoods where housing markets are becoming increasingly 'exclusive' to low income residents. UDP believes that classifying tracts in such a way allows practitioners to get a broader picture of neighborhood dynamics, specifically the concentration of poverty and wealth within a region. UDP's Typologies have evolved over time in response to community and partner feedback and the availability of new data sources. This code represents the code's most recent iteration. It makes use of data from the 2014-2018 American Community Survey; 1990, 2010 and 2000 Decennial Census; and 2012-2017 Zillow Home Value and Rent Indices. For more information: ● Displacement typology data (includes graphic with category criteria) - https://github.com/urban-displacement/displacement-typologies ● Urban Displacement Project - https://www.urbandisplacement.org/

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    equity_priority_communities_2020_acs2018

    data.bayareametro.gov | Last Updated 2024-07-15T21:22:16.000Z

    gis.plan.equity_priority_communities_2020_acs2018