The population count of Cooper County, MO was 17,622 in 2018.

Population

Population Change

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

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Demographics and Population Datasets Involving Cooper County, MO

  • API

    Hospital Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by County (SPARCS): Beginning 2009

    health.data.ny.gov | Last Updated 2020-11-16T17:30:46.000Z

    This is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. This dataset is at the county level. The Agency for Healthcare Research and Quality (AHRQ) Prevention Quality Indicators (PQIs) are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. All PQIs apply only to adult populations (over the age of 18 years). The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

  • API

    Hospital Inpatient Prevention Quality Indicators (PQI) for Adult Discharges by Zip Code (SPARCS): Beginning 2009

    health.data.ny.gov | Last Updated 2020-11-16T17:30:46.000Z

    This dataset is one of two datasets that contain observed and expected rates for Agency for Healthcare Research and Quality Prevention Quality Indicators – Adult (AHRQ PQI) beginning in 2009. The observed rates and expected rates for each AHRQ PQI is presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

  • API

    All Payer Potentially Preventable Emergency Visit (PPV) Rates by Patient County (SPARCS): Beginning 2011

    health.data.ny.gov | Last Updated 2018-01-24T16:43:17.000Z

    The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up. The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient and outpatient data and Claritas population information. The observed, expected and risk adjusted rates for PPV are presented by either resident county (including a statewide total) or resident zip code (including a statewide total).

  • API

    All Payer Potentially Preventable Emergency Visit (PPV) Rates by Patient Zip Code (SPARCS): Beginning 2011

    health.data.ny.gov | Last Updated 2018-01-24T16:46:31.000Z

    The datasets contain Potentially Preventable Visit (PPV) observed, expected, and risk-adjusted rates for all payer beneficiaries by patient county and patient zip code beginning in 2011. The Potentially Preventable Visits (PPV), obtained from software created by 3M Health Information Systems, are emergency visits that may result from a lack of adequate access to care or ambulatory care coordination. These ambulatory sensitive conditions could be reduced or eliminated with adequate patient monitoring and follow up.

  • API

    Hospital Inpatient Prevention Quality Indicators (PDI) for Pediatric Discharges by Patient County (SPARCS): Beginning 2009

    health.data.ny.gov | Last Updated 2018-03-22T19:10:41.000Z

    The dataset contains observed, expected, and risk-adjusted rates for the Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) beginning in 2009. The AHRQ PDIs are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years. The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed, expected, risk-adjusted rates, and difference in rates, for each AHRQ PDI are presented by resident county (including a statewide total).

  • API

    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

  • API

    Hospital Inpatient Prevention Quality Indicators (PDI) for Pediatric Discharges by Patient Zip Code: Beginning 2009

    health.data.ny.gov | Last Updated 2018-03-22T19:11:22.000Z

    The dataset contains observed, expected, and risk-adjusted rates for the Agency for Healthcare Research and Quality Pediatric Quality Indicators – Pediatric (AHRQ PDI) beginning in 2009. The AHRQ PDIs are a set of population based measures that can be used with hospital inpatient discharge data to identify ambulatory care sensitive conditions. These are conditions where 1) the need for hospitalization is potentially preventable with appropriate outpatient care, or 2) conditions that could be less severe if treated early and appropriately. Both the Urinary Tract Infection and Gastroenteritis PDIs include admissions for patients aged 3 months through 17 years. The asthma PDI includes admissions for patients aged 2 through 17 years. Eligible admissions for the Diabetes Short-term Complications PDI includes admissions for patients aged 6 through 17 years. The rates were calculated using Statewide Planning and Research Cooperative System (SPARCS) inpatient data and Claritas population information. The observed, expected, risk-adjusted rates, and difference in rates, for each AHRQ PDI are presented by resident zip code (including a statewide total).

  • API

    COVID-19 Vaccinations by Town - ARCHIVE

    data.ct.gov | Last Updated 2022-08-18T20:47:48.000Z

    NOTE: 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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    Bronx Zip Population and Density

    bronx.lehman.cuny.edu | Last Updated 2012-10-21T14:06:17.000Z

    2010 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 2019-11-15T22:30:02.000Z

    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).