- Population
The population count of Beaverdale, PA was 830 in 2018. The population count of Falls Creek, PA was 1,019 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 Beaverdale, PA or Falls Creek, PA
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Counts and Rates of New HIV Diagnoses Among Individuals Using Injection Drugs January 2016 - Current Monthly County & Statewide Health
data.pa.gov | Last Updated 2023-09-19T14:46:53.000ZThis indicator includes the count and rate of new HIV diagnoses among individuals using injection drugs per 100,000 individuals estimated to have Drug Use Disorder.
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Estimated Accidental and Undetermined Drug Overdose Deaths with Demographics CY 2012-Current Statewide Health
data.pa.gov | Last Updated 2024-08-12T15:49:43.000ZView annual counts of Accidental or Undetermined overdose deaths for 2012 forward, including provisional estimates of annual counts of overdose deaths for recent years, as noted with an asterisk and the month the data was pulled.<br> NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9.<br> - Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include the following: <br> - R99 when the Injury Description indicates an overdose death.<br> - X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses<br> - X47 when substance indicated is difluoroethane, alone or in combination with other drugs<BR> - Source Pennsylvania Prescription Drug Monitoring Program*<br> * These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions.<br> - Estimates are broken down by type of drugs involved in the overdose <br> - Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths<br> - Opioid Overdose Death - any overdose death involving opioids, prescription or illegal
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Rate of Hospitalizations for Opioid Overdose per 100,000 Residents by Demographics CY 2016- 2017 Statewide Health Care Cost Containment Council (PHC4)
data.pa.gov | Last Updated 2022-10-17T20:22:39.000ZRate of hospitalization for opioid overdose per 100,000 PA Residents categorized by principal diagnosis of heroin or opioid pain medication overdose by year and demographic. This analysis is restricted to Pennsylvania residents age 15 and older who were hospitalized in Pennsylvania general acute care hospitals. Disclaimer: PHC4’s database contains statewide hospital discharge data submitted to PHC4 by Pennsylvania hospitals. Every reasonable effort has been made to ensure the accuracy of the information obtained from the Uniform Claims and Billing Form (UB-82/92/04) data elements. Computer collection edits and validation edits provide opportunity to correct specific errors that may have occurred prior to, during or after submission of data. The ultimate responsibility for data accuracy lies with individual providers. PHC4 agents and staff make no representation, guarantee, or warranty, expressed or implied that the data received from the hospitals are error-free, or that the use of this data will prevent differences of opinion or disputes with those who use published reports or purchased data. PHC4 will bear no responsibility or liability for the results or consequences of its use.
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Rate of Dependent Children Removed from their Home Where Parental Drug Use was Factor FFY 2017 - Current Human Services
data.pa.gov | Last Updated 2022-02-21T17:56:36.000ZThis dataset summarizes the number of dependent children (less than 18 years old) removed from households due to parental drug abuse. The data indicates if the dependent children were placed in kinship care or not. The total number of children in this data set are provided by the U.S. Census Bureau’s American Community Survey (ACS), which publishes 5 year estimates of the population. The most recent year of entries in this data set may be available before the corresponding ACS population estimates for that year are published. In that case, the data set uses values from the most recently published ACS estimates and notes the year from which those estimates are pulled. These values are updated once the Census Bureau releases the most recent estimates.” *Kinship care refers to the care of children by relatives or, in some jurisdictions, close family friends (often referred to as fictive kin). Relatives are the preferred resource for children who must be removed from their birth parents because it maintains the children's connections with their families. *The Adoption and Foster Care Analysis and Reporting System (AFCARS) definition of parental drug abuse is “Principal caretaker’s compulsive use of drugs that is not of a temporary nature.”
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Certified Vendors - Office of Supplier Diversity
data.delaware.gov | Last Updated 2024-10-30T05:15:19.000ZThis data set is of certified businesses owned and controlled 51% or more by minorities, women, veterans, and individuals with disabilities. The data set is updated daily and is searchable and exportable at this link: http://directory.osd.gss.omb.delaware.gov/index.shtml. The Office of Supplier Diversity's mission is to assist the entire supplier diversity community of minority, women, veteran, service disabled veteran, and individuals with disabilities owned businesses as well as small businesses of a unique size in competing for the provision of commodities, services, and construction to State departments, agencies, authorities, school districts, higher education institutions and all businesses. The Office of Supplier Diversity (OSD) sits within the Division of Small Business (DSB), a Division of the Department of State (DOS).
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Uninsured Population Census Data 5-year estimates for release years 2017-Current County Human Services and Insurance
data.pa.gov | Last Updated 2022-02-21T19:25:39.000ZThe American Community Survey (ACS) helps local officials, community leaders, and businesses understand the changes taking place in their communities. It is the premier source for detailed population and housing information about our nation. This dataset provides estimates by county for Health Insurance Coverage and is summarized from summary table S2701: SELECTED CHARACTERISTICS OF HEALTH INSURANCE COVERAGE IN THE UNITED STATES. The 5-year estimates are used to provide detail on every county in Pennsylvania and includes breakouts by Age, Gender, Race, Ethnicity, Household Income, and the Ratio of Income to Poverty. An blank cell within the dataset indicates that either no sample observations or too few sample observations were available to compute the statistic for that area. Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level. While an ACS 1-year estimate includes information collected over a 12-month period, an ACS 5-year estimate includes data collected over a 60-month period. In the case of ACS 1-year estimates, the period is the calendar year (e.g., the 2015 ACS covers the period from January 2015 through December 2015). In the case of ACS multiyear estimates, the period is 5 calendar years (e.g., the 2011–2015 ACS estimates cover the period from January 2011 through December 2015). Therefore, ACS estimates based on data collected from 2011–2015 should not be labeled “2013,” even though that is the midpoint of the 5-year period. Multiyear estimates should be labeled to indicate clearly the full period of time (e.g., “The child poverty rate in 2011–2015 was X percent.”). They do not describe any specific day, month, or year within that time period.
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National Immunization Survey Adult COVID Module (NIS-ACM): COVIDVaxViews| Data | Centers for Disease Control and Prevention (cdc.gov)
data.cdc.gov | Last Updated 2024-08-09T16:51:17.000Z• National Immunization Survey Adult COVID Module (NIS-ACM): CDC is providing information on the Updated 2023-24 COVID-19 vaccine confidence to supplement vaccine administration data. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics. • The data start in October 2023. • The archived data can be found here:
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National Immunization Survey Child COVID Module (NIS-CCM): COVIDVaxViews| Data | Centers for Disease Control and Prevention (cdc.gov)
data.cdc.gov | Last Updated 2024-01-24T15:15:26.000ZNational Immunization Survey Child COVID Module (NIS-CCM): CDC is providing information on COVID-19 vaccine uptake and confidence. These data represent trends in vaccination status and intent, and other behavioral indicators, by demographics and other characteristics.
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Uninsured Population Census Data CY 2009-2014 Human Services
data.pa.gov | Last Updated 2022-10-18T14:19:11.000ZThis data is pulled from the U.S. Census website. This data is for years Calendar Years 2009-2014. Product: SAHIE File Layout Overview Small Area Health Insurance Estimates Program - SAHIE Filenames: SAHIE Text and SAHIE CSV files 2009 – 2014 Source: Small Area Health Insurance Estimates Program, U.S. Census Bureau. Internet Release Date: May 2016 Description: Model‐based Small Area Health Insurance Estimates (SAHIE) for Counties and States File Layout and Definitions The Small Area Health Insurance Estimates (SAHIE) program was created to develop model-based estimates of health insurance coverage for counties and states. This program builds on the work of the Small Area Income and Poverty Estimates (SAIPE) program. SAHIE is only source of single-year health insurance coverage estimates for all U.S. counties. For 2008-2014, SAHIE publishes STATE and COUNTY estimates of population with and without health insurance coverage, along with measures of uncertainty, for the full cross-classification of: •5 age categories: 0-64, 18-64, 21-64, 40-64, and 50-64 •3 sex categories: both sexes, male, and female •6 income categories: all incomes, as well as income-to-poverty ratio (IPR) categories 0-138%, 0-200%, 0-250%, 0-400%, and 138-400% of the poverty threshold •4 races/ethnicities (for states only): all races/ethnicities, White not Hispanic, Black not Hispanic, and Hispanic (any race). In addition, estimates for age category 0-18 by the income categories listed above are published. Each year’s estimates are adjusted so that, before rounding, the county estimates sum to their respective state totals and for key demographics the state estimates sum to the national ACS numbers insured and uninsured. This program is partially funded by the Centers for Disease Control and Prevention's (CDC), National Breast and Cervical Cancer Early Detection ProgramLink to a non-federal Web site (NBCCEDP). The CDC have a congressional mandate to provide screening services for breast and cervical cancer to low-income, uninsured, and underserved women through the NBCCEDP. Most state NBCCEDP programs define low-income as 200 or 250 percent of the poverty threshold. Also included are IPR categories relevant to the Affordable Care Act (ACA). In 2014, the ACA will help families gain access to health care by allowing Medicaid to cover families with incomes less than or equal to 138 percent of the poverty line. Families with incomes above the level needed to qualify for Medicaid, but less than or equal to 400 percent of the poverty line can receive tax credits that will help them pay for health coverage in the new health insurance exchanges. We welcome your feedback as we continue to research and improve our estimation methods. The SAHIE program's age model methodology and estimates have undergone internal U.S. Census Bureau review as well as external review. See the SAHIE Methodological Review page for more details and a summary of the comments and our response. The SAHIE program models health insurance coverage by combining survey data from several sources, including: •The American Community Survey (ACS) •Demographic population estimates •Aggregated federal tax returns •Participation records for the Supplemental Nutrition Assistance Program (SNAP), formerly known as the Food Stamp program •County Business Patterns •Medicaid •Children's Health Insurance Program (CHIP) participation records •Census 2010 Margin of error (MOE). Some ACS products provide an MOE instead of confidence intervals. An MOE is the difference between an estimate and its upper or lower confidence bounds. Confidence bounds can be created by adding the margin of error to the estimate (for the upper bound) and subtracting the margin of error from the estimate (for the lower bound). All published ACS margins of error are based on a 90-percent confidence level.