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The population rate of change of Providence County, RI was 0.13% 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.

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Demographics and Population Datasets Involving Providence County, RI

  • API

    Veteran Population Projection Model 2016 (VetPop2016)

    data.michigan.gov | Last Updated 2019-12-06T19:24:54.000Z

    2015-2045. Veteran population projections by county for US counties. From va.gov: "The Veteran Population Projection Model 2016 (VetPop2016) provides the latest official Veteran population projection from the Department of Veterans Affairs (VA). VetPop2016 is a deterministic actuarial projection model developed by the office of Predictive Analytics and Actuary (PAA) to estimate and project the Veteran Population from Fiscal Year (FY) 2015 to FY2045. Using the best available Veteran data at the end of FY2015 as the base population. VetPop2016 projects living and deceased Veteran counts by key demographic characteristics such as age, gender, period of service, and race/ethnicity at various geographic levels for the next 30 years." ***NOTE: Current upload to data.mi excludes location information for Puerto Rico, American Samoa, Guam, Northern Mariana Islands, Virgin Islands, and Foreign Countries projections. This is because of a geocoding error between the VetPop2016 and the county location file from the US Census Bureau. Point locations for the above mentioned geographies will be added to this dataset once the error is resolved.

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    Census Tracts

    data.princegeorgescountymd.gov | Last Updated 2015-06-12T13:57:20.000Z

    Prince George's County population figures by demographics for 2013. Figures are provided by the U.S. Census Bureau. This dataset gets updated as new figures are published by the U.S. Census Bureau (census.gov).

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    Vaccine Hesitancy for COVID-19: County and local estimates

    data.cdc.gov | Last Updated 2021-06-17T20:27:47.000Z

    Due to the change in the survey instrument regarding intention to vaccinate, our estimates for “hesitant or unsure” or “hesitant” derived from April 14-26, 2021, are not directly comparable with prior Household Pulse Survey data and should not be used to examine trends in hesitancy. To support state and local communication and outreach efforts, ASPE developed state, county, and sub-state level predictions of hesitancy rates (https://aspe.hhs.gov/pdf-report/vaccine-hesitancy) using the most recently available federal survey data. We estimate hesitancy rates at the state level using the U.S. Census Bureau’s Household Pulse Survey (HPS) (https://www.census.gov/programs-surveys/household-pulse-survey.html) data and utilize the estimated values to predict hesitancy rates at the Public Use Microdata Areas (PUMA) level using the Census Bureau’s 2019 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS)(https://www.census.gov/programs-surveys/acs/microdata.html). To create county-level estimates, we used a PUMA-to-county crosswalk from the Missouri Census Data Center(https://mcdc.missouri.edu/applications/geocorr2014.html). PUMAs spanning multiple counties had their estimates apportioned across those counties based on overall 2010 Census populations. The HPS is nationally representative and includes information on U.S. residents’ intentions to receive the COVID-19 vaccine when available, as well as other sociodemographic and geographic (state, region and metropolitan statistical areas) information. The ACS is a nationally representative survey, and it provides key sociodemographic and geographic (state, region, PUMAs, county) information. We utilized data for the survey collection period May 26, 2021 – June 7, 2021, which the HPS refers to as Week 31.. PUMA COVID-19 Hesitancy Data - https://data.cdc.gov/Vaccinations/Vaccine-Hesitancy-for-COVID-19-Public-Use-Microdat/djj9-kh3p

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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 2019-11-15T22:30:02.000Z

    How 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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    Vaccine Hesitancy for COVID-19: Public Use Microdata Areas (PUMAs)

    data.cdc.gov | Last Updated 2021-06-17T19:56:28.000Z

    Due to the change in the survey instrument regarding intention to vaccinate, our estimates for “hesitant or unsure” or “hesitant” derived from April 14-26, 2021, are not directly comparable with prior Household Pulse Survey data and should not be used to examine trends in hesitancy. To support state and local communication and outreach efforts, ASPE developed state, county, and sub-state level predictions of hesitancy rates(https://aspe.hhs.gov/pdf-report/vaccine-hesitancy) using the most recently available federal survey data. We estimate hesitancy rates at the state level using the U.S. Census Bureau’s Household Pulse Survey (HPS)(https://www.census.gov/programs-surveys/household-pulse-survey.html) data and utilize the estimated values to predict hesitancy rates in more granular areas using the Census Bureau’s 2019 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS)(https://www.census.gov/programs-surveys/acs/microdata.html). Public Use Microdata Areas (PUMA) level – PUMAs are geographic areas within each state that contain no fewer than 100,000 people. PUMAs can consist of part of a single densely populated county or can combine parts or all of multiple counties that are less densely populated. The HPS is nationally representative and includes information on U.S. residents’ intentions to receive the COVID-19 vaccine when available, as well as other sociodemographic and geographic (state, region and metropolitan statistical areas) information. The ACS is a nationally representative survey, and it provides key sociodemographic and geographic (state, region, PUMAs, county) information. We utilized data for the survey collection period May 26, 2021 – June 7, 2021, which the HPS refers to as Week 31. County and State Hesitancy Data - https://data.cdc.gov/Vaccinations/Vaccine-Hesitancy-for-COVID-19-County-and-local-es/q9mh-h2tw

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    Social Vulnerability Index for Virginia by Census Tract, 2018

    data.virginia.gov | Last Updated 2023-05-22T14:49:26.000Z

    "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

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    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.

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2012

    health.data.ny.gov | Last Updated 2019-09-13T16:29:09.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-Identified dataset contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data contains basic record level detail regarding the discharge; however, the data does not contain protected health information (PHI) under Health Insurance Portability and Accountability Act (HIPAA). The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.

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    Hospital Inpatient Discharges (SPARCS De-Identified): 2013

    health.data.ny.gov | Last Updated 2019-09-13T19:04:24.000Z

    The Statewide Planning and Research Cooperative System (SPARCS) Inpatient De-identified File contains discharge level detail on patient characteristics, diagnoses, treatments, services, and charges. This data file contains basic record level detail for the discharge. The de-identified data file does not contain data that is protected health information (PHI) under HIPAA. The health information is not individually identifiable; all data elements considered identifiable have been redacted. For example, the direct identifiers regarding a date have the day and month portion of the date removed.

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    2010 Census/ACS Basic Block Group Data

    data.kcmo.org | Last Updated 2021-11-12T14:15:42.000Z

    basic characteristics of people and housing for individual 2010 census block groups