The population density of Livermore, CA was 3,537 in 2018. The population density of Sandy, UT was 4,173 in 2018.
Population Density
Population Density is computed by dividing the total population by Land Area Per Square Mile.
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Geographic and Population Datasets Involving Livermore, CA or Sandy, UT
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Vital Signs: Population – by region shares
data.bayareametro.gov | Last Updated 2018-07-06T18:06:55.000ZVITAL SIGNS INDICATOR Population (LU1) FULL MEASURE NAME Population estimates LAST UPDATED September 2016 DESCRIPTION Population is a measurement of the number of residents that live in a given geographical area, be it a neighborhood, city, county or region. DATA SOURCES U.S. Census Bureau 1960-1990 Decennial Census http://factfinder2.census.gov California Department of Finance 1961-2016 Population and Housing Estimates http://www.dof.ca.gov/research/demographic/ CONTACT INFORMATION vitalsigns.info@mtc.ca.gov METHODOLOGY NOTES (across all datasets for this indicator) All legal boundaries and names for Census geography (metropolitan statistical area, county, city, tract) are as of January 1, 2010, released beginning November 30, 2010 by the U.S. Census Bureau. A priority development area (PDA) is a locally-designated infill area with frequent transit service, where a jurisdiction has decided to concentrate most of its housing and jobs growth for development in the foreseeable future. PDA boundaries are as current as July 2016. Population estimates for PDAs were derived from Census population counts at the block group level for 2000-2014 and at the tract level for 1970-1990. Population estimates for Bay Area counties and cities are from the California Department of Finance, which are as of January 1st of each year. Population estimates for non-Bay Area regions are from the U.S. Census Bureau. Decennial Census years reflect population as of April 1st of each year whereas population estimates for intercensal estimates are as of July 1st of each year. Population estimates for Bay Area tracts are from the decennial Census (1970 -2010) and the American Community Survey (2008-2012 5-year rolling average; 2010-2014 5-year rolling average). Population estimates for Bay Area PDAs are from the decennial Census (1970 - 2010) and the American Community Survey (2006-2010 5 year rolling average; 2010-2014 5-year rolling average. Estimates of density for tracts and PDAs use gross acres as the denominator. Annual population estimates for metropolitan areas outside the Bay Area are from the Census and are benchmarked to each decennial Census. The annual estimates in the 1990s were not updated to match the 2000 benchmark. The following is a list of cities and towns by geographical area: Big Three: San Jose, San Francisco, Oakland Bayside: Alameda, Albany, Atherton, Belmont, Belvedere, Berkeley, Brisbane, Burlingame, Campbell, Colma, Corte Madera, Cupertino, Daly City, East Palo Alto, El Cerrito, Emeryville, Fairfax, Foster City, Fremont, Hayward, Hercules, Hillsborough, Larkspur, Los Altos, Los Altos Hills, Los Gatos, Menlo Park, Mill Valley, Millbrae, Milpitas, Monte Sereno, Mountain View, Newark, Pacifica, Palo Alto, Piedmont, Pinole, Portola Valley, Redwood City, Richmond, Ross, San Anselmo, San Bruno, San Carlos, San Leandro, San Mateo, San Pablo, San Rafael, Santa Clara, Saratoga, Sausalito, South San Francisco, Sunnyvale, Tiburon, Union City, Vallejo, Woodside InlandCoastalDelta: American Canyon, Benicia, Clayton, Concord, Cotati, Danville, Dublin, Lafayette, Martinez, Moraga, Napa, Novato, Orinda, Petaluma, Pleasant Hill, Pleasanton, Rohnert Park, San Ramon, Santa Rosa, Sebastopol, Walnut Creek, Antioch, Brentwood, Calistoga, Cloverdale, Dixon, Fairfield, Gilroy, Half Moon Bay, Healdsburg, Livermore, Morgan Hill, Oakley, Pittsburg, Rio Vista, Sonoma, St. Helena, Suisun City, Vacaville, Windsor, Yountville Unincorporated: all unincorporated towns
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MCAH Birth File
data.countyofnapa.org | Last Updated 2024-02-07T17:45:49.000ZData Source: CA Department of Public Health, Maternal Child and Adolescent Health Division This data biography includes information about who created this data, and how, where, when, and why it was collected. 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. How was the data collected? This data product is the result of the merging of two data files spanning different time periods. The California Birth Statistical Master File from 2007 to 2017 and the California Comprehensive Master Birth File from 2018 to 2021 that replaced the Master File. Additional metrics were included from the calculations off the source datasets. Population Density data from the US Census Bureau American Community Survey 5-year estimates: Poverty States in the past 12 months & Population density data from the California Department of Health Care Access and Information: Healthcare Workforce were included as metrics or to calculate new metrics. Who was included and excluded from the data? Birth records from all live births of birthing parent resident of California collected by vital statistics offices throughout the state. Where was the data collected? Data was collected for all California counties as well as for the state of California. When was the data collected? 2007-2021 Where can I learn more about this data? Data dictionary for the source files used to build the data product can be found here. Detailed definitions assumed for this data product as well as comments on some of the methodologies applied can be found here. For more information overall, please refer to https://www.cdph.ca.gov/Programs/CFH/DMCAH/surveillance/CDPH%20Document%20Library/Data-Dashboards/About-the-Data-Prenatal-Care.pdf.
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Weekly COVID-19 cases among persons ≥5 years old among unvaccinated and vaccinated with a BNT162b2 (Pfizer-BioNTech) primary series by age group — 22 U.S. jurisdictions, January 16 to May 28, 2022
data.cdc.gov | Last Updated 2023-08-02T22:51:45.000ZReported numbers of SARS-CoV-2 infections by age group (5–11, 12–17, 18–49, 50–64, ≥65 years of age) from 22 U.S. jurisdictions (AR, AZ, CA, CO, CT, DC, FL, GA, IN, KS, MI, MA, MN, NC, NE, NJ, NM, NYC, PHL, TN, UT, WI ); ~53% of the U.S. population) with routine linkages between COVID-19 case surveillance and immunization information system (IIS) data reported to CDC during January 16, 2022 – May 28, 2022. Vaccine administration (coverage) data reported to CDC were aggregated by U.S. reporting jurisdiction, MMWR week of vaccination (≥14 days after completing the primary vaccine series), FDA-approved vaccine products, and age group (5–11, 12–17, 18–49, 50–64, ≥65 years). Vaccination status: A person vaccinated with at least a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing BNT162b2 (Pfizer-BioNTech) primary series. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. To estimate the number of unvaccinated persons in each MMWR week, the 2019 U.S. Census population estimates by jurisdiction and age group were used (except for California, where State Department of Finance 2021 population projections were determined to be more accurate). The number of unvaccinated persons each MMWR week was estimated by subtracting the cumulative number of vaccinated (all products) and partially vaccinated persons (all products) from the respective population totals for each jurisdiction and age group. Continuity correction: A continuity correction has been applied to the denominators by capping the percent population coverage at 95%. To do this, we assumed that at least 5% of each age group would always be unvaccinated in each jurisdiction. Adding this correction ensures that there is always a reasonable denominator for the unvaccinated population that would prevent rates from growing unrealistically large due to potential overestimates of vaccination coverage.