- Population
The population count of San Jose Metro Area (CA) was 1,981,616 in 2018.
Population
Population Change
Above charts are based on data from the U.S. Census American Community Survey | ODN Dataset | API -
Demographics and Population Datasets Involving San Jose Metro Area (CA)
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San Mateo County And California Crime Rates 2000-2014
performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000ZViolent and property crime rates per 100,000 population for San Mateo County and the State of California. The total crimes used to calculate the rates for San Mateo County include data from: Sheriff's Department Unincorporated, Atherton, Belmont, Brisbane, Broadmoor, Burlingame, Colma, Daly City, East Palo Alto, Foster City, Half Moon Bay, Hillsborough, Menlo Park, Millbrae, Pacifica, Redwood City, San Bruno, San Carlos, San Mateo, South San Francisco, Bay Area DPR, BART, Union Pacific Railroad, and CA Highway Patrol.
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CHSA - ECON -- Food Insecurity --- 2-Year Dissected
healthstat.dph.sbcounty.gov | Last Updated 2019-03-13T19:07:43.000ZPercent of People who Cannot Afford to Feed Themselves Sufficiently. U.S. Census Bureau, Current Population Survey, December Supplement (AKA USDA Food Security Supplement). Dissected by Year, Geographic Area, Age Category, and Race/Ethnicity.
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COVID-19 Deaths by Population Characteristics Over Time
data.sfgov.org | Last Updated 2023-09-28T13:31:30.000Z<strong>A. SUMMARY</strong> This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals for previous days may increase or decrease. More recent data is less reliable. Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups. <strong>B. HOW THE DATASET IS CREATED</strong> As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national <a href = "https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists</a>. Death certificates are maintained by the California Department of Public Health. Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. To protect resident privacy, we summarize COVID-19 data by only one characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more. Data notes on each population characteristic type is listed below. <u> Race/ethnicity</u> * We include all race/ethnicity categories that are collected for COVID-19 cases. <u>Gender</u> * The City collects information on gender identity using <u><a href="https://www.sfdph.org/dph/files/PoliciesProcedures/COM5_SexGenderGuidelines.pdf">these guidelines</a></u>. <strong>C. UPDATE PROCESS</strong> Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week. Dataset will not update on the business day following any federal holiday. <strong>D. HOW TO USE THIS DATASET</strong> Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a <a href="https://data.sfgov.org/d/cedd-86uf">view based on the San Francisco Population and Demographic Census dataset</a>. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). This dataset includes many different types of characteristics. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of deaths on each date. New deaths are the count of deaths within that characteristic group on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed. This data may not be immediately available for more recent deaths. Data updates as more information becomes available. To explore data on the total number of deaths, use <u><a href="https://data.sfgov.org/COVID-19/COVID-19-Deaths-Over-Time/g2di-xufg">the COVID-19 Deaths Over Time dataset</a></u>. <strong>E. CHANGE LOG</strong> <UL><LI>9/11/2023 - on this date, we began using an updated definition of a COVID-19 death to align with the California Department of Public Health. This change was applied to COVID-19 deaths retrospectively beginning on 1/1/2023. More information about the recommendation by the Council of State and Territorial Epidemiologists that motivated this change can be found <a href = "https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">here</a>. <LI>6/6/2023 - d
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Vital Signs: Jobs – by county
data.bayareametro.gov | Last Updated 2020-04-13T23:20:49.000ZVITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED October 2019 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/ U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/ U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/ Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma
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Vital Signs: Jobs – Bay Area
data.bayareametro.gov | Last Updated 2020-04-13T23:21:14.000ZVITAL SIGNS INDICATOR Jobs (LU2) FULL MEASURE NAME Employment estimates by place of work LAST UPDATED October 2019 DESCRIPTION Jobs refers to the number of employees in a given area by place of work. These estimates do not include self-employed and private household employees. DATA SOURCE California Employment Development Department: Current Employment Statistics 1990-2018 http://www.labormarketinfo.edd.ca.gov/ U.S. Census Bureau: LODES Data Longitudinal Employer-Household Dynamics Program (2005-2010) http://lehd.ces.census.gov/ U.S. Census Bureau: American Community Survey 5-Year Estimates, Tables S0804 (2010) and B08604 (2010-2017) https://factfinder.census.gov/ Bureau of Labor Statistics: Current Employment Statistics Table D-3: Employees on nonfarm payrolls (1990-2018) http://www.bls.gov/data/ METHODOLOGY NOTES (across all datasets for this indicator) The California Employment Development Department (EDD) provides estimates of employment, by place of employment, for California counties. The Bureau of Labor Statistics (BLS) provides estimates of employment for metropolitan areas outside of the Bay Area. Annual employment data are derived from monthly estimates and thus reflect “annual average employment.” Employment estimates outside of the Bay Area do not include farm employment. For the metropolitan area comparison, farm employment was removed from Bay Area employment totals. Both EDD and BLS data report only wage and salary jobs, not the self-employed. For measuring jobs below the county level, Vital Signs assigns collections of incorporated cities and towns to sub-county areas. For example, the cities of East Palo Alto, Menlo Park, Portola Valley, Redwood City and Woodside are considered South San Mateo County. Because Bay Area counties differ in footprint, the number of sub-county city groupings varies from one (San Francisco and San Jose counties) to four (Santa Clara County). Estimates for sub-county areas are the sums of city-level estimates from the U.S. Census Bureau: American Community Survey (ACS) 2010-2017. The following incorporated cities and towns are included in each sub-county area: North Alameda County – Alameda, Albany, Berkeley, Emeryville, Oakland, Piedmont East Alameda County - Dublin, Livermore, Pleasanton South Alameda County - Fremont, Hayward, Newark, San Leandro, Union City Central Contra Costa County - Clayton, Concord, Danville, Lafayette, Martinez, Moraga, Orinda, Pleasant Hill, San Ramon, Walnut Creek East Contra Costa County - Antioch, Brentwood, Oakley, Pittsburg West Contra Costa County - El Cerrito, Hercules, Pinole, Richmond, San Pablo Marin – all incorporated cities and towns Napa – all incorporated cities and towns San Francisco – San Francisco North San Mateo - Brisbane, Colma, Daly City, Millbrae, Pacifica, San Bruno, South San Francisco Central San Mateo - Belmont, Burlingame, Foster City, Half Moon Bay, Hillsborough, San Carlos, San Mateo South San Mateo - East Palo Alto, Menlo Park, Portola Valley, Redwood City, Woodside North Santa Clara - Los Altos, Los Altos Hills, Milpitas, Mountain View, Palo Alto, Santa Clara, Sunnyvale San Jose – San Jose Southwest Santa Clara - Campbell, Cupertino, Los Gatos, Monte Sereno, Saratoga South Santa Clara - Gilroy, Morgan Hill East Solano - Dixon, Fairfield, Rio Vista, Suisun City, Vacaville South Solano - Benicia, Vallejo North Sonoma - Cloverdale, Healdsburg, Windsor South Sonoma - Cotati, Petaluma, Rohnert Park, Santa Rosa, Sebastopol, Sonoma
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Demographics For Unincorporated Areas In San Mateo County
datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000ZDemographics, including median income, total population, race, ethnicity, and age for unincorporated areas in San Mateo County. This data comes from the 2012 American Community Survey 5 year estimates DP03 and DP05 files. They Sky Londa area is located within two Census Tracts. The data for Sky Londa is the sum of both of those Census Tracts. Users of this data should take this into account when using data for Sky Londa.
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Vital Signs: Economic Output Per Capita – by Subregion
data.bayareametro.gov | Last Updated 2019-10-25T20:14:25.000ZVITAL SIGNS INDICATOR Economic Output (EC14) FULL MEASURE NAME Per-capita gross regional product LAST UPDATED July 2019 DESCRIPTION Economic output is measured by the total and per-capita gross regional product and refers to the value of goods and services generated by workers and companies in a region. DATA SOURCE Bureau of Economic Analysis: Regional Economic Accounts 2001-2017 http://www.bea.gov/regional/ California Department of Finance: Population and Housing Estimates 2001-2009 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Note: Table E-8 California Department of Finance: Population and Housing Estimates 2010-2017 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Note: Table E-5 CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) As gross regional product data is only available on the MSA level, Bay Area data includes 10 counties (the nine core counties + San Benito County); this results in a slightly higher regional GRP as a result of additional population and business activity. Per-capita data reflects the additional population included as a result of San Benito County’s participation in the San Jose MSA. Data is inflation-adjusted by using both nominal and real data developed by BEA and appropriately escalating real GRP data in 2009 dollars to today’s dollars (2017). This inflation adjustment approach is specific to each MSA and is different from the CPI inflation approach used for other datasets on the Vital Signs website.
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Vital Signs: Economic Output Per Capita – By Metro
data.bayareametro.gov | Last Updated 2019-10-25T20:12:25.000ZVITAL SIGNS INDICATOR Economic Output (EC14) FULL MEASURE NAME Per-capita gross regional product LAST UPDATED July 2019 DESCRIPTION Economic output is measured by the total and per-capita gross regional product and refers to the value of goods and services generated by workers and companies in a region. DATA SOURCE Bureau of Economic Analysis: Regional Economic Accounts 2001-2017 http://www.bea.gov/regional/ California Department of Finance: Population and Housing Estimates 2001-2009 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Note: Table E-8 California Department of Finance: Population and Housing Estimates 2010-2017 http://www.dof.ca.gov/Forecasting/Demographics/Estimates/ Note: Table E-5 CONTACT INFORMATION vitalsigns.info@bayareametro.gov METHODOLOGY NOTES (across all datasets for this indicator) As gross regional product data is only available on the MSA level, Bay Area data includes 10 counties (the nine core counties + San Benito County); this results in a slightly higher regional GRP as a result of additional population and business activity. Per-capita data reflects the additional population included as a result of San Benito County’s participation in the San Jose MSA. Data is inflation-adjusted by using both nominal and real data developed by BEA and appropriately escalating real GRP data in 2009 dollars to today’s dollars (2017). This inflation adjustment approach is specific to each MSA and is different from the CPI inflation approach used for other datasets on the Vital Signs website.
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COVID-19 Vaccinations Given to SF Residents by Demographics Over Time
data.sfgov.org | Last Updated 2023-10-02T15:18:09.000Z<strong>A. SUMMARY</strong> This dataset represents the COVID-19 vaccinations given to residents of San Francisco over time. All vaccines given to SF residents are included, no matter where the vaccination took place (the vaccine may have been administered in San Francisco or outside of San Francisco). The data are broken down by multiple demographic stratifications. This dataset also includes COVID-19 vaccinations given to SF residents by the San Francisco Department of Public Health (SFDPH) over time. Data provides counts for residents who have received at least one dose, residents who have completed a primary vaccine series, residents who have received one or two monovalent (not bivalent) booster doses, and residents who have received a bivalent booster dose. A primary vaccine series is complete after an individual has received all intended doses of the initial series. There are one, two, and three dose primary vaccine series. <strong>B. HOW THE DATASET IS CREATED</strong> Information on doses administered to those who live in San Francisco is from the <a href="https://cdph.ca.gov/CAIR ">California Immunization Registry (CAIR2)</a>, run by the California Department of Public Health (CDPH). The information on individuals’ city of residence, age, race, and ethnicity are also recorded in CAIR and are self-reported at the time of vaccine administration. In order to estimate the percent of San Franciscans vaccinated, we provide the 2016-2020 American Community Survey (ACS) population estimates for each demographic group. <strong>C. UPDATE PROCESS</strong> Updated daily via automated process <strong>D. HOW TO USE THIS DATASET</strong> San Francisco population estimates for race/ethnicity and age groups can be found in a <a href=" https://data.sfgov.org/d/cedd-86uf">view based on the San Francisco Population and Demographic Census dataset</a>. These population estimates are from the 2016-2020 5-year American Community Survey (ACS). Before analysis, you must filter the dataset to the desired stratification of data using the "overall_segment" column. For example, filtering "overall_segment" to "All SF Residents by Age Bracket, Administered by All Providers" will filter the data to residents whose vaccinations were administered by any provider. You can then further segment the data and calculate percentages by Age Brackets. If you filter "overall_segment" to "All SF Residents by Race/Ethnicity, Administered by DPH Only", you will see the race/ethnicity breakdown for residents who received vaccinations from the San Francisco Department of Public Health (SFDPH). If you filter "overall_segment" to "All SF Residents by Age Group, Administered by All Providers" you will see vaccination counts of various age eligibility groups that were administered by any provider. To count the number of individuals vaccinated (with any primary series dose) for the first time on a given day, use the "new_recipients" column. To count the number of individuals who have completed their primary vaccine series on a given day, use the "new_series_completed" column. To count the number of primary series doses administered on a day (1st, 2nd, 3rd, or single doses), use the "new_primary_series_doses" column. To count the number of individuals who received their first or second monovalent (not bivalent) booster dose on a given day, use the "new_booster_recipients" and "new_2nd_booster_recipients" columns. To count the number of individuals who received their first bivalent booster dose on a given day, use the "new_bivalent_booster_recipients" column. To count the number of monovalent (not including bivalent) or bivalent booster doses administered on a given day, use the "new_booster_doses" or "new_bivalent_booster_doses" columns. To count the number of individuals who have received a vaccine up to a certain date, use the columns beginning with "cumulative_..." <strong>E. ARCHIVED DATA</strong> A previous version of this dataset
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Mpox Vaccinations Given to SF Residents by Demographics
data.sfgov.org | Last Updated 2023-05-24T15:55:41.000Z<strong>UPDATE 1/3/2023: Due to low case numbers, this page will no longer include vaccinations after 12/31/2022. </strong> <strong>A. SUMMARY </strong> This dataset represents doses of mpox vaccine (JYNNEOS) administered in California to residents of San Francisco ages 18 years or older. This dataset only includes doses of the JYNNEOS vaccine given on or after 5/1/2022. All vaccines given to people who live in San Francisco are included, no matter where the vaccination took place. The data are broken down by multiple demographic stratifications. <strong>B. HOW THE DATASET IS CREATED </strong> Information on doses administered to those who live in San Francisco is from the <a href="https://cdph.ca.gov/CAIR">California Immunization Registry (CAIR2)</a>, run by the California Department of Public Health (CDPH). Information on individuals’ city of residence, age, race, ethnicity, and sex are recorded in CAIR2 and are self-reported at the time of vaccine administration. Because CAIR2 does not include information on sexual orientation, we pull information from the San Francisco Department of Public Health’s Epic Electronic Health Record (EHR). The populations represented in our Epic data and the CAIR2 data are different. Epic data only include vaccinations administered at SFDPH managed sites to SF residents. Data notes for population characteristic types are listed below. <u>Age </u> * Data only include individuals who are 18 years of age or older. <u>Race/ethnicity </u> * The response option "Other Race" is categorized by the data source system, and the response option "Unknown" refers to a lack of data. <u>Sex </u> * The response option "Other" is categorized by the source system, and the response option "Unknown" refers to a lack of data. <u>Sexual orientation </u> * The response option “Unknown/Declined” refers to a lack of data or individuals who reported multiple different sexual orientations during their most recent interaction with SFDPH. For convenience, we provide <a href="https://data.sfgov.org/d/4qbq-hvtt"> the 2020 5-year American Community Survey population estimates</a>. <strong>C. UPDATE PROCESS </strong> Updated daily via automated process. <strong>D. HOW TO USE THIS DATASET </strong> This dataset includes many different types of demographic groups. Filter the “demographic_group” column to explore a topic area. Then, the “demographic_subgroup” column shows each group or category within that topic area and the total count of doses administered to that population subgroup.