National provisional drug overdose deaths by month and 2013 NCHS Urban–Rural Classification Scheme for Counties. Drug overdose deaths are identified using underlying cause-of-death codes from the Tenth Revision of ICD (ICD–10): X40–X44 (unintentional), X60–X64 (suicide), X85 (homicide), and Y10–Y14 (undetermined). Deaths are based on the county of residence in the United States. Death counts provided are for “12-month ending periods,” defined as the number of deaths occurring in the 12-month period ending in the month indicated. Estimates for 2020 are based on provisional data. Estimates for 2018 and 2019 are based on final data. For more information on NCHS urban-rural classification, see: https://www.cdc.gov/nchs/data/series/sr_02/sr02_166.pdf

A. SUMMARY This dataset includes data from the Office of the Chief Medical Examiner on the number of preliminary unintentional fatal drug overdoses per month.

B. HOW THE DATASET IS CREATED The Office of the Chief Medical Examiner releases a monthly report containing the previous month’s preliminary count of unintentional fatal drug overdoses. This dataset is manually updated based on that report.

The San Francisco Office of the Chief Medical Examiner (OCME) investigates any unknown cause of death for deaths that occur in San Francisco. OCME uses drug testing, death scene investigation, autopsy, medical record, and informant information to determine the cause of death. Preliminary determinations are generally based on drug testing and death scene investigations.

Preliminary deaths reported by the medical examiner consist of two categories: (a) cases that are still under investigation and involve suspected acute toxicity from opioids, cocaine, or methamphetamine; and (b) cases that have been finalized and were attributed to acute toxicity from any substance (including prescribed medication and over-the-counter medication).

C. UPDATE PROCESS This dataset is updated monthly following the release of the monthly accidental fatal drug overdose report from the Office of the Chief Medical Examiner. Department of Public Health staff manually copy data from the Office of the Chief Medical Examiner’s report to update this dataset.

D. HOW TO USE THIS DATASET This dataset is updated each month to include the most recent month’s preliminary accidental fatal drug overdose count. Counts from previous months are often also updated as it can take more than a month for the Office of the Chief Medical Examiner to finish reviewing cases.

E. RELATED DATASETS San Francisco Department of Public Health Substance Use Services Overdose-Related 911 Responses by Emergency Medical Services (EMS) Unintentional Drug Overdose Death Rate by Race/Ethnicity

This data visualization presents county-level provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. County-level provisional counts include deaths occurring within the 50 states and the District of Columbia, as of the date specified and may not include all deaths that occurred during a given time period. Provisional counts are often incomplete and causes of death may be pending investigation resulting in an underestimate relative to final counts (see Technical Notes). The provisional data presented on the dashboard below include reported 12 month-ending provisional counts of death due to drug overdose by the decedent’s county of residence and the month in which death occurred. Percentages of deaths with a cause of death pending further investigation and a note on historical completeness (e.g. if the percent completeness was under 90% after 6 months) are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts (see Technical Notes). Counts between 1-9 are suppressed in accordance with NCHS confidentiality standards. Provisional data presented on this page will be updated on a quarterly basis as additional records are received. Technical Notes Nature and Sources of Data Provisional drug overdose death counts are based on death records received and processed by the National Center for Health Statistics (NCHS) as of a specified cutoff date. The cutoff date is generally the first Sunday of each month. National provisional estimates include deaths occurring within the 50 states and the District of Columbia. NCHS receives the death records from the state vital registration offices through the Vital Statistics Cooperative Program (VSCP). The timeliness of provisional mortality surveillance data in the National Vital Statistics System (NVSS) database varies by cause of death and jurisdiction in which the death occurred. The lag time (i.e., the time between when the death occurred and when the data are available for analysis) is longer for drug overdose deaths compared with other causes of death due to the time often needed to investigate these deaths (1). Thus, provisional estimates of drug overdose deaths are reported 6 months after the date of death. Provisional death counts presented in this data visualization are for “12 month-ending periods,” defined as the number of deaths occurring in the 12 month period ending in the month indicated. For example, the 12 month-ending period in June 2020 would include deaths occurring from July 1, 2019 through June 30, 2020. The 12 month-ending period counts include all seasons of the year and are insensitive to reporting variations by seasonality. These provisional counts of drug overdose deaths and related data quality metrics are provided for public health surveillance and monitoring of emerging trends. Provisional drug overdose death data are often incomplete, and the degree of completeness varies by jurisdiction and 12 month-ending period. Consequently, the numbers of drug overdose deaths are underestimated based on provisional data relative to final data and are subject to random variation. Cause of Death Classification and Definition of Drug Deaths Mortality statistics are compiled in accordance with the World Health Organizations (WHO) regulations specifying that WHO member nations classify and code causes of death with the current revision of the International Statistical Classification of Diseases and Related Health Problems (ICD). ICD provides the basic guidance used in virtually all countries to code and classify causes of death. It provides not only disease, injury, and poisoning categories but also the rules used to select the single underlying cause of death for tabulation from the several diagnoses that may be reported on a single death certificate, as well as definitions, tabulation lists, the format of the death certificate, and regul

A. SUMMARY This dataset includes unintentional drug overdose death rates by race/ethnicity by year. This dataset is created using data from the California Electronic Death Registration System (CA-EDRS) via the Vital Records Business Intelligence System (VRBIS). Substance-related deaths are identified by reviewing the cause of death. Deaths caused by opioids, methamphetamine, and cocaine are included. Homicides and suicides are excluded. Ethnic and racial groups with fewer than 10 events are not tallied separately for privacy reasons but are included in the “all races” total.

Unintentional drug overdose death rates are calculated by dividing the total number of overdose deaths by race/ethnicity by the total population size for that demographic group and year and then multiplying by 100,000. The total population size is based on estimates from the US Census Bureau County Population Characteristics for San Francisco, 2022 Vintage by age, sex, race, and Hispanic origin.

These data differ from the data shared in the Preliminary Unintentional Drug Overdose Death by Year dataset since this dataset uses finalized counts of overdose deaths associated with cocaine, methamphetamine, and opioids only.

B. HOW THE DATASET IS CREATED This dataset is created by copying data from the Annual Substance Use Trends in San Francisco report from the San Francisco Department of Public Health Center on Substance Use and Health.

C. UPDATE PROCESS This dataset will be updated annually, typically at the end of the year.

D. HOW TO USE THIS DATASET N/A

E. RELATED DATASETS Overdose-Related 911 Responses by Emergency Medical Services Preliminary Unintentional Drug Overdose Deaths San Francisco Department of Public Health Substance Use Services

F. CHANGE LOG

• 12/16/2024 - Updated with 2023 data. Asian/Pacific Islander race/ethnicity group was changed to Asian.
• 12/16/2024 - Past year totals by race/ethnicity were revised after obtaining accurate race/ethnicity for some decedents that were previously marked as “unknown” race/ethnicity.

Drug-related mortality is a complex phenomenon, which accounts for a considerable percentage of deaths among young people in many European countries. The EMCDDA, in collaboration with national experts, has defined an epidemiological indicator with two components at present: deaths directly caused by illegal drugs (drug-induced deaths) and mortality rates among problem drug users. These two components can fulfil several public health objectives, notably as an indicator of the overall health impact of drug use and the components of this impact, identify particularly risky patterns of use, and potentially identify new risks.

There are around 50 statistical tables in this dataset. Each data table may be viewed as an HTML table or downloaded in spreadsheet (Excel format).

Analysis of ‘Accidental Drug Related Deaths 2012-2020’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://catalog.data.gov/dataset/1b7f2866-87a3-43d7-ba26-1ad82a3f3424 on 12 February 2022.

--- Dataset description provided by original source is as follows ---

A listing of each accidental death associated with drug overdose in Connecticut from 2012 to 2020. 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

--- Original source retains full ownership of the source dataset ---

We collect data and report statistics on opioid, stimulant, and other substance use and their impact on health and well-being.

This dataset tracks the updates made on the dataset "Provisional Drug Overdose Deaths by Urban/Rural Classification Scheme for 12 month-ending December 2018-December 2020" as a repository for previous versions of the data and metadata.

Annual number of deaths registered related to drug poisoning in England and Wales by sex, region and whether selected substances were mentioned anywhere on the death certificate, with or without other drugs or alcohol, and involvement in suicides.

"Using ED data to track trends in nonfatal drug overdoses is a critical strategy for expanding overdose surveillance and tailoring prevention resources to populations most affected, including initiation of medication-assisted treatment in ED settings and subsequent linkage to care for substance use disorders." - Nonfatal Drug Overdoses Treated in Emergency Departments — United States, 2016–2017, CDC MMWR Weekly / April 3, 2020 / 69(13);371–376 - https://www.cdc.gov/mmwr/volumes/69/wr/mm6913a3.htmNotes:As of April 2019, this map contains the most recent data available at the sub-county level for deaths (2012-2016), hospitalizations (2012-2015) and emergency room visits (2011-2015).All data comes from the New Mexico Department of Health Indicator Based Information System (NM-IBIS)Click on individual map layer items below ("Layers") for information about sources and methods for each data set.For Hospitalization and Emergency Room data, three NM hospitals do not report: 2 Indian Health Service Hospitals in northwestern New Mexico, and the Veteran's Administration Hospital in Albuquerque.

ObjectiveOur study analyzed the impact of civil commitment (CC) laws for substance use disorder (SUD) on opioid overdose death rates (OODR) in the U.S. from 2010–21.MethodsWe used a retrospective study design using the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) dataset to analyze overdose death rates from any opioid during 2010–21 using ICD-10 codes. We used t-tests and two-way ANOVA to compare the OODR between the U.S. states with the law as compared to those without by using GraphPad Prism 10.0.ResultsWe found no significant difference in the annual mean age-adjusted OODR from 2010–21 between U.S. states with and without CC SUD laws. During the pre-COVID era (2010–19), the presence or absence of CC SUD law had no difference in age-adjusted OODR. However, in the post-COVID era (2020–21), there was a significant increase in OODR in states with a CC SUD law compared to states without the law (p = 0.032). We also found that OODR increased at a faster rate post-COVID among both the states with CC SUD laws (p 

Left hand columns: CDC data from 42 states for ratio of non-fatal drug-related ED visits in Jan.-Sept. 2020. Table shows ratio of visits during 2020 to visits during same month in 2019. Right hand columns: Data from ED staffing company on drug-related ED visits to 181 EDs in 24 states over January 2017-June 2022. Table shows average for indicated periods of monthly ratios of visits in January 2017-February 2020 to visits in the same months a year earlier and March-December 2020 and January 2021-June 2022 to visits in the same months in 2019. Ratios are computed at the ED level and then averaged across EDs within each month. 95% confidence intervals are reported in brackets. Last row shows average ratio of opioid/related ED visits to all overdose visits for the months in the indicated period.

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

NOTE: The cumulative Fatal Accidental Overdoses resource (the first table below) has been modified to address a number of issues, including (but not limited to) duplication of many records. Fatal accidental overdose incidents in Allegheny County, denoting age, gender, race, drugs present, zip code of incident and zip code of residence. Zip code of incident is where the Office of the Medical Examiner received the body, not necessarily where the overdose occurred. Data includes closed cases only and the previous calendar year data will be updated monthly until the close of the current calendar year. For example, the 2014 resource will be updated monthly until December 2015. If you are looking for the old yearly files they have been archived and compressed and are available below as a zip file.

Number of deaths and age-specific mortality rates for selected grouped causes, by age group and sex, 2000 to most recent year.

Descriptive statistics and results from adjusted and unadjusted longitudinal GEE models predicting overdose death rates from 2017–2020.

Este paquete de datos contiene todos los datos de origen para gráficos y visualización utilizados en la página, Preguntas frecuentes (FAQ): muertes por sobredosis de drogas en Europa.. Incluye las siguientes tablas.
Cuadro A. Año de los datos más recientes sobre sobredosis

Cuadro 1. Muertes inducidas por drogas en la Unión Europea, Noruega y Türkiye: número total entre adultos de 15 a 64 años si está disponible, de lo contrario todas las edades, 2021

Cuadro 2. Tasas de mortalidad inducidas por drogas por millón entre adultos (15-64): tendencias seleccionadas

Cuadro 3. Tasas de mortalidad inducidas por drogas por millón entre adultos (15-64)

Cuadro 4. Proporción de hombres entre las muertes relacionadas con las drogas en la Unión Europea, Noruega y Türkiye, 2021

Cuadro 5. Distribución de muertes inducidas por drogas notificadas en 2012 y en 2020, o más reciente

Cuadro 6. Distribución de las muertes inducidas por drogas notificadas en 2021, o año más reciente, por grupo de edad y por país

Cuadro 7. Proporción de muertes inducidas por drogas entre las personas mayores (40+ años) en la Unión Europea, Noruega y Türkiye, 2020 (o los datos más recientes disponibles)

Cuadro 8. Proporción de muertes inducidas por drogas entre las personas mayores (40+ años) en la Unión Europea, Noruega y Türkiye, 2021 (o los datos más recientes disponibles)

Cuadro 9. Proporción de muertes inducidas por drogas con opioides implicados en la Unión Europea, Noruega y Türkiye, 2020 (o los datos más recientes disponibles)

Cuadro 10. Tendencias indexadas en el número de muertes en algunos países del sudeste de Europa, 2011-2020 (2011 = 100)

Cuadro 11. Tendencias indexadas en el número de muertes en algunos países del norte de Europa, 2011-2020 (2011 = 100)

Cuadro 12. Fuentes utilizadas por los países para notificar las muertes inducidas por drogas al OEDT, 2020 (o los datos más recientes disponibles)

Cuadro 13. Fuentes preferidas por los países para notificar las muertes inducidas por drogas al OEDT, 2020 (o los datos más recientes disponibles)

Cuadro 14. Estudios de cohortes de mortalidad entre personas que consumen drogas en Europa: países con estudios realizados en los últimos 10 años o antes. Junio de 2021 — conclusiones provisionales

Cuadro 15. Países incluidos en el «sudeste» y el «norte» de Europa para este análisis de tendencias

Cuadro 16. Número de países europeos que aplican intervenciones de reducción de daños, hasta 2022

Data by medical encounter for the following conditions by age, race/ethnicity, and gender:

Alcohol Poisoning
Alcohol Related Disorders
Anxiety and Fear Related Disorders
Cannabis Overdoses
Cannabis Related Disorders
Depression
Impulse and Conduct Disorders
Miscellaneous Mental Health Disorders
Mood Disorders
Neurodevelopmental Disorders
Opioid Overdoses
Opioid Related Disorders
Personality Disorders
Schizophrenia
Sedative Overdoses
Sedative Related Disorders
Stimulant Overdoses
Stimulant Related Disorders
Substance Related Disorders
Suicide
Trauma and Stressor Related Disorders

Rates per 100,000 population. Age-adjusted rates per 100,000 2000 US standard population.
Blank Cells: Rates not calculated for fewer than 11 events. Rates not calculated in cases where zip code is unknown. Geography not reported where there are no cases reported in a given year. SES: Is the median household income by SRA community. Data for SRAs only.

*The COVID-19 pandemic was associated with increases in all-cause mortality. COVID-19 deaths have affected the patterns of mortality including those of Behavioral Health conditions.

Data sources: California Department of Public Health, Center for Health Statistics, Office of Health Information and Research, Vital Records Business Intelligence System (VRBIS). California Department of Health Care Access and Information (HCAI), Emergency Department Database and Patient Discharge Database, 2020. SANDAG Population Estimates, 2020 (vintage: 09/2022). Population estimates were derived using the 2010 Census and data should be considered preliminary. Prepared by: County of San Diego, Health and Human Services Agency, Public Health Services, Community Health Statistics Unit, February 2023.

2020 Community Profile Data Guide and Data Dictionary Dashboard: https://public.tableau.com/app/profile/chsu/viz/2020CommunityProfilesDataGuideandDataDictionaryDashboard_16763944288860/HomePage

Information on the numbers of deaths which were caused by Volatile Substance Abuse and by Helium, 2020 and previous years.

Suburb-based crime statistics for crimes against the person and crimes against property. The Crime statistics datasets contain all offences against the person and property that were reported to police in that respective financial year. The Family and Domestic Abuse-related offences datasets are a subset of this, in that a separate file is presented for these offences that were flagged as being of a family and domestic abuse nature for that financial year. Consequently the two files for the same financial year must not be added together.