A listing of each accidental death associated with drug overdose in Connecticut from 2012 to June 2017. A "Y" value under the different substance columns indicates that particular substance was detected.

Data are derived from an investigation by the Office of the Chief Medical Examiner which includes the toxicity report, death certificate, as well as a scene investigation.

The “Morphine (Not Heroin)” values are related to the differences between how Morphine and Heroin are metabolized and therefor detected in the toxicity results. Heroin metabolizes to 6-MAM which then metabolizes to morphine. 6-MAM is unique to heroin, and has a short half-life (as does heroin itself). Thus, in some heroin deaths, the toxicity results will not indicate whether the morphine is from heroin or prescription morphine. In these cases the Medical Examiner may be able to determine the cause based on the scene investigation (such as finding heroin needles). If they find prescription morphine at the scene it is certified as “Morphine (not heroin).” Therefor, the Cause of Death may indicate Morphine, but the Heroin or Morphine (Not Heroin) may not be indicated.

“Any Opioid” – If the Medical Examiner cannot conclude whether it’s RX Morphine or heroin based morphine in the toxicity results, that column may be checked

Zip Code, Life expectancy; Cancer deaths per 100,000 people; Heart disease deaths per 100,000 people; Alzheimer’s disease deaths per 100,000 people; Stroke deaths per 100,000 people; Chronic lower respiratory disease deaths per 100,000 people; Unintentional injury deaths per 100,000 people; Diabetes deaths per 100,000 people; Influenza and pneumonia deaths per 100,000 people; Hypertension deaths per 100,000 people. Percentages unless otherwise noted. Source information provided at: https://www.sccgov.org/sites/phd/hi/hd/Documents/City%20Profiles/Methodology/Neighborhood%20profile%20methodology_082914%20final%20for%20web.pdf

BY USING THIS WEBSITE OR THE CONTENT THEREIN, YOU AGREE TO THE TERMS OF USE. A study was performed by the Oakland County Health Department to determine how many deaths in Oakland County (2016) could potentially be related to opioids. The number of potential opioid deaths were then summarized at the community level, and the average age of death in each community was calculated.

This digital geologic and tectonic database of the Death Valley ground-water model area, as well as its accompanying geophysical maps, are compiled at 1:250,000 scale. The map compilation presents new polygon, line, and point vector data for the Death Valley region. The map area is enclosed within a 3 degree X 3 degree area along the border of southern Nevada and southeastern California. In addition to the Death Valley National Park and Death Valley-Furnace Creek fault systems, the map area includes the Nevada Test Site, the southwest Nevada volcanic field, the southern end of the Walker Lane (from southern Esmeralda County, Nevada, to the Las Vegas Valley shear zone and Stateline fault system in Clark County, Nevada), the eastern California shear zone (in the Cottonwood and Panamint Mountains), the eastern end of the Garlock fault zone (Avawatz Mountains), and the southern basin and range (central Nye and western Lincoln Counties, Nevada). This geologic map improves on previous geologic mapping in the area by providing new and updated Quaternary and bedrock geology, new interpretation of mapped faults and regional structures, new geophysical interpretations of faults beneath the basins, and improved GIS coverages. The basic geologic database has tectonic interpretations imbedded within it through attributing of structure lines and unit polygons which emphasize significant and through-going structures and units. An emphasis has been put on features which have important impacts on ground-water flow. Concurrent publications to this one include a new isostatic gravity map (Ponce and others, 2001), a new aeromagnetic map (Ponce and Blakely, 2001), and contour map of depth to basement based on inversion of gravity data (Blakely and Ponce, 2001).

Bouguer Gravity Map Of California, Death Valley Sheet

The files linked to this reference are the geospatial data created as part of the completion of the baseline vegetation inventory project for the NPS park unit. Current format is ArcGIS file geodatabase but older formats may exist as shapefiles. Cogan Technology, Inc. (CTI) created the digital vegetation map layer for the Death Valley National Park project area that covered 3,430,818 acres (1,389,486 ha). The resulting spatial database and vegetation map layer were created using a combination of 2020 (California) and 2019 (Nevada) National Agriculture Imagery Program (NAIP) basemap data, ground-based verification efforts, and a two-step, or hybrid mapping approach that used both manual and automated techniques. By comparing the vegetation signatures on the imagery to the field data, 90 map units (74 vegetated and 16 land-use/land-cover) were developed and used to delineate the plant communities. The interpreted vegetation polygons were then digitized into a Geographic Information System (GIS) layer that was field-tested, reviewed, and revised. The final DEVA vegetation map layer was assessed for overall thematic accuracy at 82% with a Kappa value of 89%.

Learn about the impact of tuberculosis on 1800's America and modern society.

Rate of deaths by age/gender (per 100,000 population) for motor vehicle occupants killed in crashes, 2012 & 2014. 2012 Source: Fatality Analysis Reporting System (FARS). 2014 Source: National Highway Traffic Safety Administration's (NHTSA) Fatality Analysis Reporting System (FARS), 2014 Annual Report File Note: Blank cells indicate data are suppressed. Fatality rates based on fewer than 20 deaths are suppressed.

Thematic map on the causes of death in the circles. The data are offered absolute and per 100,000 inhabitants.:Deaths due to diseases of the digestive organs 2021, per 100,000 inhabitants, county level

description: The locations of principal faults and structural zones that may influence ground-water flow were compiled in support of a three-dimensional ground-water model for the Death Valley regional flow system (DVRFS), which covers 80,000 square km in southwestern Nevada and southeastern California. Faults include Neogene extensional and strike-slip faults and pre-Tertiary thrust faults. Emphasis was given to characteristics of faults and deformed zones that may have a high potential for influencing hydraulic conductivity. These include: (1) faulting that results in the juxtaposition of stratigraphic units with contrasting hydrologic properties, which may cause ground-water discharge and other perturbations in the flow system; (2) special physical characteristics of the fault zones, such as brecciation and fracturing, that may cause specific parts of the zone to act either as conduits or as barriers to fluid flow; (3) the presence of a variety of lithologies whose physical and deformational characteristics may serve to impede or enhance flow in fault zones; (4) orientation of a fault with respect to the present-day stress field, possibly influencing hydraulic conductivity along the fault zone; and (5) faults that have been active in late Pleistocene or Holocene time and areas of contemporary seismicity, which may be associated with enhanced permeabilities. The faults shown on maps A and B are largely from Workman and others (in press), and fit one or more of the following criteria: (1) faults that are more than 10 km in map length; (2) faults with more than 500 m of displacement; and (3) faults in sets that define a significant structural fabric that characterizes a particular domain of the DVRFS. The following fault types are shown: Neogene normal, Neogene strike-slip, Neogene low-angle normal, pre-Tertiary thrust, and structural boundaries of Miocene calderas. We have highlighted faults that have late Pleistocene to Holocene displacement (Piety, 1996). Areas of thick Neogene basin-fill deposits (thicknesses 1-2 km, 2-3 km, and >3 km) are shown on map A, based on gravity anomalies and depth-to-basement modeling by Blakely and others (1999). We have interpreted the positions of faults in the subsurface, generally following the interpretations of Blakely and others (1999). Where geophysical constraints are not present, the faults beneath late Tertiary and Quaternary cover have been extended based on geologic reasoning. Nearly all of these concealed faults are shown with continuous solid lines on maps A and B, in order to provide continuous structures for incorporation into the hydrogeologic framework model (HFM). Map A also shows the potentiometric surface, regional springs (25-35 degrees Celsius, D'Agnese and others, 1997), and cold springs (Turner and others, 1996).; abstract: The locations of principal faults and structural zones that may influence ground-water flow were compiled in support of a three-dimensional ground-water model for the Death Valley regional flow system (DVRFS), which covers 80,000 square km in southwestern Nevada and southeastern California. Faults include Neogene extensional and strike-slip faults and pre-Tertiary thrust faults. Emphasis was given to characteristics of faults and deformed zones that may have a high potential for influencing hydraulic conductivity. These include: (1) faulting that results in the juxtaposition of stratigraphic units with contrasting hydrologic properties, which may cause ground-water discharge and other perturbations in the flow system; (2) special physical characteristics of the fault zones, such as brecciation and fracturing, that may cause specific parts of the zone to act either as conduits or as barriers to fluid flow; (3) the presence of a variety of lithologies whose physical and deformational characteristics may serve to impede or enhance flow in fault zones; (4) orientation of a fault with respect to the present-day stress field, possibly influencing hydraulic conductivity along the fault zone; and (5) faults that have been active in late Pleistocene or Holocene time and areas of contemporary seismicity, which may be associated with enhanced permeabilities. The faults shown on maps A and B are largely from Workman and others (in press), and fit one or more of the following criteria: (1) faults that are more than 10 km in map length; (2) faults with more than 500 m of displacement; and (3) faults in sets that define a significant structural fabric that characterizes a particular domain of the DVRFS. The following fault types are shown: Neogene normal, Neogene strike-slip, Neogene low-angle normal, pre-Tertiary thrust, and structural boundaries of Miocene calderas. We have highlighted faults that have late Pleistocene to Holocene displacement (Piety, 1996). Areas of thick Neogene basin-fill deposits (thicknesses 1-2 km, 2-3 km, and >3 km) are shown on map A, based on gravity anomalies and depth-to-basement modeling by Blakely and others (1999). We have interpreted the positions of faults in the subsurface, generally following the interpretations of Blakely and others (1999). Where geophysical constraints are not present, the faults beneath late Tertiary and Quaternary cover have been extended based on geologic reasoning. Nearly all of these concealed faults are shown with continuous solid lines on maps A and B, in order to provide continuous structures for incorporation into the hydrogeologic framework model (HFM). Map A also shows the potentiometric surface, regional springs (25-35 degrees Celsius, D'Agnese and others, 1997), and cold springs (Turner and others, 1996).

Map shows numbers of deaths and injuries by district. White areas have zero numbers or no data. Map also shows epicentre.

Bouguer Anomaly Values Were Contoured With A 5 Mgal Interval And Are Overprinted On The Death Valley Sheet Of The Geologic Map Of California, Olaf P. Jenkins Edition. Egi Reference Number Gl03117

Registered charity 1126727; registered company limited by guarantee 6611408 (England and Wales)

This layer shows the location of the Births and Deaths Registries in Hong Kong. It is a subset of the geo-referenced public facility data made available by the Lands Department under the Government of Hong Kong Special Administrative Region (the “Government”) at https://DATA.GOV.HK/ (“DATA.GOV.HK”). The source data is in CSV format and processed and converted to Esri File Geodatabase format and then uploaded to Esri’s ArcGIS Online platform for sharing and reference purpose. The objectives are to facilitate our Hong Kong ArcGIS Online users to use the data in a spatial ready format and save their data conversion effort. For details about the data, source format and terms of conditions of usage, please refer to the website of DATA.GOV.HK (https://data.gov.hk).

This file contains death counts and death rates for drug overdose, suicide, homicide and firearm injuries at the United States national level (additional datasets exist for other levels of geography). The data is grouped by 3 different time periods including monthly, yearly, and trailing twelve months. Please see data dictionary for intents and mechanisms included in each measure.

The National Violent Death Reporting System (NVDRS) provides states and communities with a clearer understanding of violent deaths to guide local decisions about efforts to prevent violence and helps them track progress over time. To stop violent deaths, we must first understand all the facts. Created in 2002, the NVDRS is a surveillance system that pulls together data on violent deaths in 18 states (see map below), including information about homicides, such as homicides perpetrated by a intimate partner (e.g., boyfriend, girlfriend, wife, husband), child maltreatment (or child abuse) fatalities, suicides, deaths where individuals are killed by law enforcement in the line of duty, unintentional firearm injury deaths, and deaths of undetermined intent. These data are supported by WISQARS, an interactive query system that provides data on injury deaths, violent deaths, and nonfatal injuries.

Updates

• Notice of data discontinuation: Since the start of the pandemic, AP has reported case and death counts from data provided by Johns Hopkins University. Johns Hopkins University has announced that they will stop their daily data collection efforts after March 10. As Johns Hopkins stops providing data, the AP will also stop collecting daily numbers for COVID cases and deaths. The HHS and CDC now collect and visualize key metrics for the pandemic. AP advises using those resources when reporting on the pandemic going forward.

  • CDC Weekly case and death counts (national and state level)
  • CDC County level cases and deaths
  • HHS New hospital admissions
  • CDC NowCast COVID variant proportions (national and regional level)

• April 9, 2020

  • The population estimate data for New York County, NY has been updated to include all five New York City counties (Kings County, Queens County, Bronx County, Richmond County and New York County). This has been done to match the Johns Hopkins COVID-19 data, which aggregates counts for the five New York City counties to New York County.

• April 20, 2020

  • Johns Hopkins death totals in the US now include confirmed and probable deaths in accordance with CDC guidelines as of April 14. One significant result of this change was an increase of more than 3,700 deaths in the New York City count. This change will likely result in increases for death counts elsewhere as well. The AP does not alter the Johns Hopkins source data, so probable deaths are included in this dataset as well.

• April 29, 2020

  • The AP is now providing timeseries data for counts of COVID-19 cases and deaths. The raw counts are provided here unaltered, along with a population column with Census ACS-5 estimates and calculated daily case and death rates per 100,000 people. Please read the updated caveats section for more information.

• September 1st, 2020

  • Johns Hopkins is now providing counts for the five New York City counties individually.

• February 12, 2021

  • The Ohio Department of Health recently announced that as many as 4,000 COVID-19 deaths may have been underreported through the state’s reporting system, and that the "daily reported death counts will be high for a two to three-day period."
  • Because deaths data will be anomalous for consecutive days, we have chosen to freeze Ohio's rolling average for daily deaths at the last valid measure until Johns Hopkins is able to back-distribute the data. The raw daily death counts, as reported by Johns Hopkins and including the backlogged death data, will still be present in the new_deaths column.

• February 16, 2021

  - Johns Hopkins has reconciled Ohio's historical deaths data with the state.

  Overview

The AP is using data collected by the Johns Hopkins University Center for Systems Science and Engineering as our source for outbreak caseloads and death counts for the United States and globally.

The Hopkins data is available at the county level in the United States. The AP has paired this data with population figures and county rural/urban designations, and has calculated caseload and death rates per 100,000 people. Be aware that caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.

This data is from the Hopkins dashboard that is updated regularly throughout the day. Like all organizations dealing with data, Hopkins is constantly refining and cleaning up their feed, so there may be brief moments where data does not appear correctly. At this link, you’ll find the Hopkins daily data reports, and a clean version of their feed.

The AP is updating this dataset hourly at 45 minutes past the hour.

To learn more about AP's data journalism capabilities for publishers, corporations and financial institutions, go here or email kromano@ap.org.

Queries

Use AP's queries to filter the data or to join to other datasets we've made available to help cover the coronavirus pandemic

• Filter cases by state here

• Rank states by their status as current hotspots. Calculates the 7-day rolling average of new cases per capita in each state: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=481e82a4-1b2f-41c2-9ea1-d91aa4b3b1ac

• Find recent hotspots within your state by running a query to calculate the 7-day rolling average of new cases by capita in each county: https://data.world/associatedpress/johns-hopkins-coronavirus-case-tracker/workspace/query?queryid=b566f1db-3231-40fe-8099-311909b7b687&showTemplatePreview=true

• Join county-level case data to an earlier dataset released by AP on local hospital capacity here. To find out more about the hospital capacity dataset, see the full details.

• Pull the 100 counties with the highest per-capita confirmed cases here

• Rank all the counties by the highest per-capita rate of new cases in the past 7 days here. Be aware that because this ranks per-capita caseloads, very small counties may rise to the very top, so take into account raw caseload figures as well.

Interactive

The AP has designed an interactive map to track COVID-19 cases reported by Johns Hopkins.

@(https://datawrapper.dwcdn.net/nRyaf/15/)

Interactive Embed Code

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Caveats

• This data represents the number of cases and deaths reported by each state and has been collected by Johns Hopkins from a number of sources cited on their website.
• In some cases, deaths or cases of people who've crossed state lines -- either to receive treatment or because they became sick and couldn't return home while traveling -- are reported in a state they aren't currently in, because of state reporting rules.
• In some states, there are a number of cases not assigned to a specific county -- for those cases, the county name is "unassigned to a single county"
• This data should be credited to Johns Hopkins University's COVID-19 tracking project. The AP is simply making it available here for ease of use for reporters and members.
• Caseloads may reflect the availability of tests -- and the ability to turn around test results quickly -- rather than actual disease spread or true infection rates.
• Population estimates at the county level are drawn from 2014-18 5-year estimates from the American Community Survey.
• The Urban/Rural classification scheme is from the Center for Disease Control and Preventions's National Center for Health Statistics. It puts each county into one of six categories -- from Large Central Metro to Non-Core -- according to population and other characteristics. More details about the classifications can be found here.

Johns Hopkins timeseries data - Johns Hopkins pulls data regularly to update their dashboard. Once a day, around 8pm EDT, Johns Hopkins adds the counts for all areas they cover to the timeseries file. These counts are snapshots of the latest cumulative counts provided by the source on that day. This can lead to inconsistencies if a source updates their historical data for accuracy, either increasing or decreasing the latest cumulative count. - Johns Hopkins periodically edits their historical timeseries data for accuracy. They provide a file documenting all errors in their timeseries files that they have identified and fixed here

Attribution

This data should be credited to Johns Hopkins University COVID-19 tracking project

Infant death is defined as death occurring within the first year of life. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts. Data are not presented for geographies with number of infant deaths less than 11.Infant deaths are among the most tragic health events in a community, and sadly, they occur at a much greater frequency in some communities than in others. Chronic stress associated with both historical and ongoing racism are important contributing factors. Cities and communities can play an important role in addressing these inequities in reproductive health outcomes by examining their policies and practices with a racial equity lens, ensuring that all groups have the opportunities and resources needed to achieve optimal health.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

Death rate has been age-adjusted by the 2000 U.S. standard population. Single-year data are only available for Los Angeles County overall, Service Planning Areas, Supervisorial Districts, City of Los Angeles overall, and City of Los Angeles Council Districts.Lung cancer is a leading cause of cancer-related death in the US. People who smoke have the greatest risk of lung cancer, though lung cancer can also occur in people who have never smoked. Most cases are due to long-term tobacco smoking or exposure to secondhand tobacco smoke. Cities and communities can take an active role in curbing tobacco use and reducing lung cancer by adopting policies to regulate tobacco retail; reducing exposure to secondhand smoke in outdoor public spaces, such as parks, restaurants, or in multi-unit housing; and improving access to tobacco cessation programs and other preventive services.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.