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Early Model-based Provisional Estimates of Drug Overdose, Suicide, and Transportation-related Deaths
healthdata.gov | Last Updated 2023-07-25T18:41:21.000ZThis dataset provides model-based provisional estimates of the weekly numbers of drug overdose, suicide, and transportation-related deaths using “nowcasting” methods to account for the normal lag between the occurrence and reporting of these deaths. Estimates less than 10 are suppressed. These early model-based provisional estimates were generated using a multi-stage hierarchical Bayesian modeling process to generate smoothed estimates of the weekly numbers of death, accounting for reporting lags. These estimates are based on several assumptions about how the reporting lags have changed in recent months across different jurisdictions, and the resulting estimates differ from other sources of provisional mortality data. For now, these estimates should be considered highly uncertain until further evaluations can be done to determine the validity of these assumptions about timeliness. The true patterns in reporting lags will not be known until data are finalized, typically 11–12 months after the end of the calendar year. Importantly, these estimates are not a replacement for monthly provisional drug overdose death counts, or quarterly provisional mortality estimates. For more detail about the nowcasting methods and models, see: Rossen LM, Hedegaard H, Warner M, Ahmad FB, Sutton PD. Early provisional estimates of drug overdose, suicide, and transportation-related deaths: Nowcasting methods to account for reporting lags. Vital Statistics Rapid Release; no 11. Hyattsville, MD: National Center for Health Statistics. February 2021. DOI: https://doi.org/10.15620/ cdc:101132
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Road Traffic Injuries
healthdata.gov | Last Updated 2023-07-26T12:08:09.000ZThis table contains data on the annual number of fatal and severe road traffic injuries per population and per miles traveled by transport mode, for California, its regions, counties, county divisions, cities/towns, and census tracts. Injury data is from the Statewide Integrated Traffic Records System (SWITRS), California Highway Patrol (CHP), 2002-2010 data from the Transportation Injury Mapping System (TIMS) . The table is part of a series of indicators in the [Healthy Communities Data and Indicators Project of the Office of Health Equity]. Transportation accidents are the second leading cause of death in California for people under the age of 45 and account for an average of 4,018 deaths per year (2006-2010). Risks of injury in traffic collisions are greatest for motorcyclists, pedestrians, and bicyclists and lowest for bus and rail passengers. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience 4 times the death rate as Whites or Asians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Annual Miles Traveled
healthdata.gov | Last Updated 2023-07-26T12:25:17.000ZThis table contains data on the annual miles traveled by place of occurrence and by mode of transportation (vehicle, pedestrian, bicycle), for California, its regions, counties, and cities/towns. The ratio uses data from the California Department of Transportation, the U.S. Department of Transportation, and the U.S. Census Bureau. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Miles traveled by individuals and their choice of mode – car, truck, public transit, walking or bicycling – have a major impact on mobility and population health. Miles traveled by automobile offers extraordinary personal mobility and independence, but it is also associated with air pollution, greenhouse gas emissions linked to global warming, road traffic injuries, and sedentary lifestyles. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which has many documented health benefits. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Transportation to Work
healthdata.gov | Last Updated 2023-07-25T20:47:11.000ZThis table contains data on the percent of residents aged 16 years and older mode of transportation to work for California, its regions, counties, cities/towns, and census tracts. Data is from the U.S. Census Bureau, Decennial Census and American Community Survey. The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Commute trips to work represent 19% of travel miles in the United States. The predominant mode – the automobile - offers extraordinary personal mobility and independence, but it is also associated with health hazards, such as air pollution, motor vehicle crashes, pedestrian injuries and fatalities, and sedentary lifestyles. Automobile commuting has been linked to stress-related health problems. Active modes of transport – bicycling and walking alone and in combination with public transit – offer opportunities for physical activity, which is associated with lowering rates of heart disease and stroke, diabetes, colon and breast cancer, dementia and depression. Risk of injury and death in collisions are higher in urban areas with more concentrated vehicle and pedestrian activity. Bus and rail passengers have a lower risk of injury in collisions than motorcyclists, pedestrians, and bicyclists. Minority communities bear a disproportionate share of pedestrian-car fatalities; Native American male pedestrians experience four times the death rate Whites or Asian pedestrians, and African-Americans and Latinos experience twice the rate as Whites or Asians. More information about the data table and a data dictionary can be found in the About/Attachments section.
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Lead Testing in School Drinking Water Buildings with Lead-Free Plumbing: Compliance Year 2016
healthdata.gov | Last Updated 2023-07-25T17:57:57.000ZList of buildings for each NYS public school and Boards of Cooperative Educational Services (BOCES) reported as being lead-free for Compliance Year 2016. Schools are not required to test lead-free buildings for lead in drinking water. The definition of a lead-free building is any school building with internal plumbing that meets the new definition of "Lead Free," as defined in section 1417 of the Federal Safe Drinking Water Act. A building can be deemed lead-free if (1) it was built after January 4, 2014, or (2) a NYS licensed professional engineer or architect certifies the building's internal plumping is lead-free. School districts and BOCES are required to report the presence of lead-free buildings for each compliance year to parents, the NYS Department of Health, NY State Education Department, and local health departments. For more information see: http://www.health.ny.gov/environmental/water/drinking/lead/lead_testing_of_school_drinking_water.htm
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Hospital Building Data
healthdata.gov | Last Updated 2024-05-24T04:00:18.000ZProvides basic information for general acute care hospital buildings such as height, number of stories, the building code used to design the building, and the year it was completed. The data is sorted by counties and cities. Structural Performance Categories (SPC ratings) are also provided. SPC ratings range from 1 to 5 with SPC 1 assigned to buildings that may be at risk of collapse during a strong earthquake and SPC 5 assigned to buildings reasonably capable of providing services to the public following a strong earthquake. Where SPC ratings have not been confirmed by the Department of Health Care Access and Information (HCAI) yet, the rating index is followed by 's'. A URL for the building webpage in HCAI/OSHPD eServices Portal is also provided to view projects related to any building.
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SHIP Fall-Related Death Rate 2009-2021
healthdata.gov | Last Updated 2024-02-23T04:01:39.000ZFall-Related Death Rate - This indicator shows the rate of fall-related deaths per 100,000 population. Falls are a major cause of preventable death among the elderly and have increased across age groups in the past decade. Causes of fall-related deaths differ between the elderly and young and middle-aged populations, and require different prevention strategies. In 2009, falls accounted for 30% of accidental deaths. <a href="https://health.maryland.gov/pophealth/Documents/SHIP/SHIP%20Lite%20Data%20Details/Fall.pdf" > Link to Data Details </a>
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Vaccine Hesitancy for COVID-19: Public Use Microdata Areas (PUMAs)
healthdata.gov | Last Updated 2023-07-26T01:27:59.000ZDue 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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Program of All-Inclusive Care for the Elderly (PACE) Rates
healthdata.gov | Last Updated 2023-07-26T12:05:27.000ZThe datasets contain reimbursement rates paid to participating Program of All-Inclusive Care for the Elderly (PACE) organizations for calendar years 2015-2022. To be eligible for the PACE program, a person must be 55 years of age or older and reside in one of the following PACE service areas: Alameda, Contra Costa, Fresno, Humboldt, Los Angeles, Orange, Riverside, Sacramento, San Bernardino, San Diego, San Francisco, San Joaquin, Santa Clara, Stanislaus.
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Low Income Home Energy Assistance Program FY 2008 Household Data
healthdata.gov | Last Updated 2023-07-25T18:42:49.000Z<p>State-reported annual data collected on the presence of elderly, disabled, and young children in eligible households receiving Low Income Home Energy Assistance Program (LIHEAP) heating assistance, cooling assistance, crisis assistance or weatherization assistance.</p>