The population rate of change of San Leandro, CA was 0.21% in 2018.

Population

Population Change

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

1. ODN datasets and APIs are subject to change and may differ in format from the original source data in order to provide a user-friendly experience on this site.

2. To build your own apps using this data, see the ODN Dataset and API links.

3. If you use this derived data in an app, we ask that you provide a link somewhere in your applications to the Open Data Network with a citation that states: "Data for this application was provided by the Open Data Network" where "Open Data Network" links to http://opendatanetwork.com. Where an application has a region specific module, we ask that you add an additional line that states: "Data about REGIONX was provided by the Open Data Network." where REGIONX is an HREF with a name for a geographical region like "Seattle, WA" and the link points to this page URL, e.g. http://opendatanetwork.com/region/1600000US5363000/Seattle_WA

Demographics and Population Datasets Involving San Leandro, CA

  • API

    San Mateo County And California Crime Rates 2000-2014

    performance.smcgov.org | Last Updated 2016-08-31T20:40:07.000Z

    Violent 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.

  • API

    CHSA - ECON -- Food Insecurity --- 2-Year Dissected

    healthstat.dph.sbcounty.gov | Last Updated 2019-03-13T19:07:43.000Z

    Percent 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.

  • API

    COVID-19 Cases by Population Characteristics Over Time

    data.sfgov.org | Last Updated 2022-11-25T15:03:06.000Z

    Note: On September 12, 2021, a new case definition of COVID-19 was introduced that includes criteria for enumerating new infections after previous probable or confirmed infections (also known as reinfections). A reinfection is defined as a confirmed positive PCR lab test more than 90 days after a positive PCR or antigen test. The first reinfection case was identified on December 7, 2021. Some fluctuation in historic data may result when this change is implemented on July 15, 2022. Note: As of March 2022, the race/ethnicity label changed from Native American to American Indian or Alaska Native to align with the Census. Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change. Due to the changes, starting on January 22, 2022, the number of new cases reported daily will be higher than under the old system as cases that would have taken longer to process will be reported earlier. <strong>A. SUMMARY</strong> This dataset shows San Francisco COVID-19 cases by population characteristics and by specimen collection date. Cases are included on the date the positive test was collected. Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how cases have been distributed among different subgroups. This information can reveal trends and disparities among groups. Data is lagged by five days, meaning the most recent specimen collection date included is 5 days prior to today. Tests take time to process and report, so more recent data is less reliable. <strong>B. HOW THE DATASET IS CREATED</strong> Data on the population characteristics of COVID-19 cases and deaths are from: * Case interviews * Laboratories * Medical providers These multiple streams of data are merged, deduplicated, and undergo data verification processes. This data may not be immediately available for recently reported cases because of the time needed to process tests and validate cases. Daily case totals on previous days may increase or decrease. <u><a href="https://data.sfgov.org/s/nudz-9tg2/">Learn more</a></u>. Data are continually updated to maximize completeness of information and reporting on San Francisco residents with COVID-19. 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. * The population estimates for the "Other" or “Multi-racial” groups should be considered with caution. The Census definition is likely not exactly aligned with how the City collects this data. For that reason, we do not recommend calculating population rates for these groups. <u> Sexual orientation</u> * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to the California Department of Public Health, Virtual Assistant information gathering beginning December 2021. The Virtual Assistant is only sent to adults who are 18+ years old.<u><a href="https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf"> Learn more about our data collection guidelines pertaining to sexual orientation</a></u>. <u> Gender</u> * The City collects information on gender identity using <a href="https://www.sfdph.org/dph/files/PoliciesProcedures/COM5_SexGenderGuidelines.pdf">these guidelines</a>. <u> Comorbidities</u> * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death. <u> Transmission type</u> * Information on transmission of COVID-19 is based on ca

  • API

    Demographics For Unincorporated Areas In San Mateo County

    datahub.smcgov.org | Last Updated 2018-10-25T21:45:46.000Z

    Demographics, 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.

  • API

    COVID-19 Deaths Over Time

    data.sfgov.org | Last Updated 2022-11-25T15:03:29.000Z

    Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change. <strong>A. SUMMARY</strong> This dataset represents San Francisco COVID-19 related deaths by day. Deaths are included on the date the individual died. Data is lagged by five days, meaning the most date included is 5 days prior to today. All data update daily as more information becomes available. <strong>B. HOW THE DATASET IS CREATED</strong> COVID-19 deaths are suspected to be associated with COVID-19. This means COVID-19 is listed as a cause of death or significant condition on the death certificate. Deaths may be reported by: * Healthcare providers * The California Department of Public Health Vital Records * Case investigation or outbreak investigation * The Office of the Chief Medical Examiner It takes time to process this data. Because of this, data is lagged by 5 days and death totals for previous days may increase or decrease. More recent data is less reliable. Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. <strong>C. UPDATE PROCESS</strong> Updates automatically at 05:00 AM Pacific Time each day. Redundant runs are scheduled at 07:00 AM and 09:00 AM in case of pipeline failure. Dataset will not update on the business day following any federal holiday. <strong>D. HOW TO USE THIS DATASET</strong> This dataset shows new deaths and cumulative deaths by date of death. New deaths are the count of deaths on that specific date. Cumulative deaths are the running total of all San Francisco COVID-19 deaths up to the date listed. Use the <a href="https://data.sfgov.org/d/kkr3-wq7h">Deaths by Population Characteristics dataset</a> to see deaths by different subgroups including race/ethnicity, age, gender, and homelessness.

  • API

    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2022-11-09T20:24:29.000Z

    "ATSDR’s Geospatial Research, Analysis & Services Program (GRASP) created Centers for Disease Control and Prevention Social Vulnerability Index (CDC SVI or simply SVI, hereafter) to help public health officials and emergency response planners identify and map the communities that will most likely need support before, during, and after a hazardous event. SVI indicates the relative vulnerability of every U.S. Census tract. Census tracts are subdivisions of counties for which the Census collects statistical data. SVI ranks the tracts on 15 social factors, including unemployment, minority status, and disability, and further groups them into four related themes. Thus, each tract receives a ranking for each Census variable and for each of the four themes, as well as an overall ranking." For more see https://www.atsdr.cdc.gov/placeandhealth/svi/documentation/SVI_documentation_2018.html

  • API

    Vital Signs: Population – by region shares

    data.bayareametro.gov | Last Updated 2018-07-06T18:06:55.000Z

    VITAL 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

  • API

    Vital Signs: Jobs – by county

    data.bayareametro.gov | Last Updated 2020-04-13T23:20:49.000Z

    VITAL 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

  • API

    MPX Vaccinations Given to SF Residents by Demographics

    data.sfgov.org | Last Updated 2022-11-25T15:45:20.000Z

    <strong>A. SUMMARY </strong> This dataset represents doses of MPX 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.

  • API

    COVID-19 Deaths by Population Characteristics Over Time

    data.sfgov.org | Last Updated 2022-11-25T15:02:29.000Z

    Note: As of March 2022, the race/ethnicity label changed from Native American to American Indian or Alaska Native to align with the Census. Note: On January 22, 2022, system updates to improve the timeliness and accuracy of San Francisco COVID-19 cases and deaths data were implemented. You might see some fluctuations in historic data as a result of this change. <strong>A. SUMMARY</strong> This dataset shows San Francisco COVID-19 deaths by population characteristics and by date. Deaths are included on the date the individual died. 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. Data is lagged by five days, meaning the most date included is 5 days prior to today. All data update daily as more information becomes available. <strong>B. HOW THE DATASET IS CREATED</strong> COVID-19 deaths are suspected to be associated with COVID-19. This means COVID-19 is listed as a cause of death or significant condition on the death certificate. Data on the population characteristics of COVID-19 deaths are from: * Case interviews * Laboratories * Medical providers These multiple streams of data are merged, deduplicated, and undergo data verification processes. It takes time to process this data. Because of this, data is lagged by 5 days and death totals for previous days may increase or decrease. More recent data is less reliable. Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths. 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> Sexual orientation</u> * The City began asking adults 18 years old or older for their sexual orientation identification during case interviews as of April 28, 2020. Sexual orientation data prior to this date is unavailable. * The City doesn’t collect or report information about sexual orientation for persons under 12 years of age. * Case investigation interviews transitioned to Virtual Assistant information gathering starting December 2021. The California Department of Public Health, Virtual Assistant is only sent to adults who are 18+ years old.<u><a href="https://www.sfdph.org/dph/files/PoliciesProcedures/COM9_SexualOrientationGuidelines.pdf"> Learn more about our data collection guidelines pertaining to sexual orientation</a></u>. Gender * 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>. <u> Comorbidities</u> * Underlying conditions are reported when a person has one or more underlying health conditions at the time of diagnosis or death. <u> Transmission type</u> * Information on transmission of COVID-19 is based on case interviews with individuals who have a confirmed positive test. Individuals are asked if they have been in close contact with a known COVID-19 case. If they answer yes, transmission category is recorded as contact with a known case. If they report no contact with a known case, transmission category is recorded as community transmission. If the case is not interviewed or was not asked the question, they are counted as unknown. <u> Homelessness</u> Persons are identified as homeless based on several data sources: * self-reported living situation * the location at the time of testing * Department of Public Health homelessness and health databases * Residents in Single-Room Occupancy hotels are not included in these figures. These methods serve as an estimate of persons experiencing homelessness. They may not meet other homelessness definitions. <u> Skilled Nursing Facility (SNF) occupancy</u> * A Skilled Nursing Facility (SNF) is a type of lo