The population count of Madison County, KY was 89,700 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 Madison County, KY
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Bronx Zip Population and Density
bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z2010 Census Data on population, pop density, age and ethnicity per zip code
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NYSERDA Low- to Moderate-Income New York State Census Population Analysis Dataset: Average for 2013-2015
data.ny.gov | Last Updated 2019-11-15T22:30:02.000ZHow does your organization use this dataset? What other NYSERDA or energy-related datasets would you like to see on Open NY? Let us know by emailing OpenNY@nyserda.ny.gov. The Low- to Moderate-Income (LMI) New York State (NYS) Census Population Analysis dataset is resultant from the LMI market database designed by APPRISE as part of the NYSERDA LMI Market Characterization Study (https://www.nyserda.ny.gov/lmi-tool). All data are derived from the U.S. Census Bureau’s American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS) files for 2013, 2014, and 2015. Each row in the LMI dataset is an individual record for a household that responded to the survey and each column is a variable of interest for analyzing the low- to moderate-income population. The LMI dataset includes: county/county group, households with elderly, households with children, economic development region, income groups, percent of poverty level, low- to moderate-income groups, household type, non-elderly disabled indicator, race/ethnicity, linguistic isolation, housing unit type, owner-renter status, main heating fuel type, home energy payment method, housing vintage, LMI study region, LMI population segment, mortgage indicator, time in home, head of household education level, head of household age, and household weight. The LMI NYS Census Population Analysis dataset is intended for users who want to explore the underlying data that supports the LMI Analysis Tool. The majority of those interested in LMI statistics and generating custom charts should use the interactive LMI Analysis Tool at https://www.nyserda.ny.gov/lmi-tool. This underlying LMI dataset is intended for users with experience working with survey data files and producing weighted survey estimates using statistical software packages (such as SAS, SPSS, or Stata).
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COVID-19 Vaccinations by Town - ARCHIVE
data.ct.gov | Last Updated 2023-08-02T14:53:12.000ZNOTE: As of 4/15/2021, this dataset will no longer be updated and will be replaced by two new datasets: 1) "COVID-19 Vaccinations by Town" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town/x7by-h8k4) and "COVID-19 Vaccinations by Town and Age Group" (https://data.ct.gov/Health-and-Human-Services/COVID-19-Vaccinations-by-Town-and-Age-Group/gngw-ukpw). A summary of COVID-19 vaccination coverage in Connecticut by town. Records without an address could not be included in town vaccine coverage estimates. Total population estimates are based on 2019 data. A person who has received one dose of any vaccine is considered to have received at least one dose. A person is considered fully vaccinated if they have received 2 doses of the Pfizer or Moderna vaccines or 1 dose of the Johnson & Johnson vaccine. The fully vaccinated are a subset of the number who have received at least one dose. The number with At Least One Dose and the number Fully Vaccinated add up to more than the total number of doses because people who received the Johnson & Johnson vaccine fit into both categories. SVI refers to the CDC's Social Vulnerability Index - a measure that combines 15 demographic variables to identify communities most vulnerable to negative health impacts from disasters and public health crises. Measures of social vulnerability include socioeconomic status, household composition, disability, race, ethnicity, language, and transportation limitations - among others. Towns with a "yes" in the "Has SVI tract >0.75" field are those that have at least one census tract that is in the top quartile of vulnerability (e.g., a high-need area). 34 towns in Connecticut have at least one census tract in the top quartile for vulnerability. All data in this report are preliminary; data for previous dates will be updated as new reports are received and data errors are corrected.
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Social Vulnerability Index 2018 - United States, county
data.cdc.gov | Last Updated 2022-02-14T14:19:58.000ZATSDR’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. In addition to tract-level rankings, SVI 2018 also has corresponding rankings at the county level. Notes below that describe “tract” methods also refer to county methods.
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Social Vulnerability Index 2018 - United States, tract
data.cdc.gov | Last Updated 2022-02-14T14:22:44.000ZATSDR’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. In addition to tract-level rankings, SVI 2018 also has corresponding rankings at the county level. Notes below that describe “tract” methods also refer to county methods.
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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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2010 Census/ACS Basic Block Group Data
data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Zbasic characteristics of people and housing for individual 2010 census block groups
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Workforce Demographic Characteristics by Commuting Mode Split : 2012 - 2016
data.cambridgema.gov | Last Updated 2024-02-02T21:50:48.000ZThis data set provides demographic and journey to work characteristics of the Cambridge Workforce by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time arriving at work, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Workforce consist of all persons who work in Cambridge, regardless of home location. For more information on Journey to Work data in Cambridge, please see the report Moving Forward: 2020 - https://www.cambridgema.gov/-/media/Files/CDD/FactsandMaps/profiles/demo_moving_forward_2020.pdf
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Labor Force Demographic Characteristics by Commuting Mode Split: 2012 - 2016
data.cambridgema.gov | Last Updated 2024-02-02T21:52:10.000ZThis data set provides demographic and journey to work characteristics of the Cambridge Labor Force by primary mode of their journey to work. Attributes include age, presence of children, racial and ethnic minority status, vehicles available, time leaving home, time spent traveling, and annual household income. The data set originates from a special tabulation of the American Community Survey - the 2012 - 2016 version of the Census Transportation Planning Products (CTPP). The Cambridge Labor Force consist of all persons who live in Cambridge who work or are actively seeking employment. For more information on Journey to Work data in Cambridge, please see the report Moving Forward: 2020 - https://www.cambridgema.gov/-/media/Files/CDD/FactsandMaps/profiles/demo_moving_forward_2020.pdf
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COVID-19 Case Surveillance Public Use Data
data.cdc.gov | Last Updated 2024-04-05T23:47:25.000Z<b>Note:</b> Authorizations to collect certain public health data expired at the end of the U.S. public health emergency declaration on May 11, 2023. The following jurisdictions discontinued COVID-19 case notifications to CDC: Iowa (11/8/21), Kansas (5/12/23), Kentucky (1/1/24), Louisiana (10/31/23), New Hampshire (5/23/23), and Oklahoma (5/2/23). Please note that these jurisdictions will not routinely send new case data after the dates indicated. As of 7/13/23, case notifications from Oregon will only include pediatric cases resulting in death. This case surveillance public use dataset has 12 elements for all COVID-19 cases shared with CDC and includes demographics, any exposure history, disease severity indicators and outcomes, presence of any underlying medical conditions and risk behaviors, and no geographic data. <h4><b>CDC has three COVID-19 case surveillance datasets:</b></h4><ul><li><a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Public-Use-Data-with-Ge/n8mc-b4w4">COVID-19 Case Surveillance Public Use Data with Geography</a>: Public use, patient-level dataset with clinical data (including symptoms), demographics, and county and state of residence. (19 data elements)</li><li><a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Public-Use-Data/vbim-akqf">COVID-19 Case Surveillance Public Use Data</a>: Public use, patient-level dataset with clinical and symptom data and demographics, with no geographic data. (12 data elements)</li><li><a href="https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Restricted-Access-Detai/mbd7-r32t">COVID-19 Case Surveillance Restricted Access Detailed Data</a>: Restricted access, patient-level dataset with clinical and symptom data, demographics, and state and county of residence. Access requires a registration process and a data use agreement. (33 data elements)</li></ul> The following apply to all three datasets: <ul><li>Data elements can be found on the COVID-19 case report form located at <a href="https://www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf">www.cdc.gov/coronavirus/2019-ncov/downloads/pui-form.pdf</a>.</li><li>Data are considered provisional by CDC and are subject to change until the data are reconciled and verified with the state and territorial data providers.</li><li>Some data cells are suppressed to protect individual privacy.</li><li>The datasets will include all cases with the earliest date available in each record (date received by CDC or date related to illness/specimen collection) at least 14 days prior to the creation of the current datasets. This 14-day lag allows case reporting to be stabilized and ensures that time-dependent outcome data are accurately captured.</li><li>Datasets are updated monthly.</li><li>Datasets are created using CDC’s <a href="https://www.cdc.gov/grants/additional-requirements/ar-25.html">Policy on Public Health Research and Nonresearch Data Management and Access</a> and include protections designed to protect individual privacy.</li><li>For more information about data collection and reporting, please see <a href="https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html">https://www.cdc.gov/coronavirus/2019-ncov/covid-data/about-us-cases-deaths.html.</a></li><li>For more information about the COVID-19 case surveillance data, please see <a href="https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html"> https://www.cdc.gov/coronavirus/2019-ncov/covid-data/faq-surveillance.html</a><br></li></ul> <h4><b>Overview</b></h4> The COVID-19 case surveillance database includes individual-level data reported to U.S. states and autonomous reporting entities, including New York City and the District of Columbia (D.C.), as well as U.S. territories and affiliates. On April 5, 2020, COVID-19 was added to the <a href="https://ndc.services.cdc.gov/search-results-year/">Nationally Notifiable Condition List</a> and classified as “immediately not