In 2023, Estonia had the highest incidence of drug-induced deaths in Europe at *** per million population. This was followed by Latvia at *** deaths per million population, and ** deaths per million in Norway. On the other hand, in Romania, there were only * drug-induced deaths per million population in 2023. Number of drug-induced deaths There were nearly *** thousand drug-related deaths reported in the EU in 2022. There was a steady increase in the number of deaths in the EU from only *** thousand cases in 2013. When combined with Turkey and Norway, the number of drug-induced deaths in 2022 nearly reached ***** thousand. This was the highest number of drug-related deaths recorded in the given period. Drug deaths by gender and age In 2022, 77 percent of drug-induced deaths reported in the EU were attributed to men. Half of the deaths that occurred among men were among those aged between 25 and 44 years. Similarly, the largest share of female deaths due to drug use was also reported in the same age group.

This is historical data. The update frequency has been set to "Static Data" and is here for historic value. Updated on 8/14/2024

Drug-Induced Death Rate - This indicator shows the drug-induced death rate per 100,000 population. Drug-induced deaths include all deaths for which illicit or prescription drugs are the underlying cause. In 2007, drug-induced deaths were more common than alcohol-induced or firearm-related deaths in the United States. Between 2012-2014, there were 2793 drug-induced deaths in Maryland. Link to Data Details

The number of drug-related deaths in Norway fluctuated during the period from 2008 to 2023. In 2023, there were 363 drug-related deaths recorded in Norway, the highest in the given time interval.

Annual number of deaths registered related to drug poisoning, by local authority, England and Wales.

This data presents provisional counts for drug overdose deaths based on a current flow of mortality data in the National Vital Statistics System. Counts for the most recent final annual data are provided for comparison. National 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. To address this, methods were developed to adjust provisional counts for reporting delays by generating a set of predicted provisional counts. Several data quality metrics, including the percent completeness in overall death reporting, percentage of deaths with cause of death pending further investigation, and the percentage of drug overdose deaths with specific drugs or drug classes reported are included to aid in interpretation of provisional data as these measures are related to the accuracy of provisional counts. Reporting of the specific drugs and drug classes involved in drug overdose deaths varies by jurisdiction, and comparisons of death rates involving specific drugs across selected jurisdictions should not be made. Provisional data presented will be updated on a monthly basis as additional records are received. For more information please visit: https://www.cdc.gov/nchs/nvss/vsrr/drug-overdose-data.htm

In 2023, there were ***** deaths in Germany that were caused by the consumption of drugs. *** of those deaths were the effects of long-term damage done by drug use. The second most common cause of death was from heroin or morphine in combination with other drugs.

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

Drug Induced Death reports the number and rate of drug-induced deaths.

Deaths as a result of drug overdoses in Portugal amounted to ** in 2019, which is the second highest number of annual deaths reported in the provided time interval. In 2011, drug deaths fell to only **, before reaching ** just four years later. In 2020, drug-induced deaths were counted at **. In 2021, there were ** deaths by overdose, the highest value recorded. Low death rate compared to Europe When compared with the rest of Europe, Portugal has a fairly low incidence of drug deaths. A rate of ** drug deaths per million population (pmp) means that Portugal only had a higher drug death rate than a few countries in the continent, and a significantly lower rate than the ** deaths pmp in Norway, which is the highest in Europe. In 2001, Portugal became the first country in the world to decriminalize the consumption of drugs. The low amount of drug deaths in Portugal is usually attributed to this policy of decriminalization. Breakdown of drugs consumed The class of drugs that caused the highest share of individuals seeking treatment in Portugal, in 2021, were cannabis, with approximately ** percent of Portuguese drug treatment entrants seeking treatment primarily due to the use of this drug class. With a slightly lower share, opioids caused **** percent of drug treatment entries in Portugal. In 2022, Portugal had approximately ****** individuals in opioid substitution treatment, which was the sixth-highest in Europe.

A listing of each accidental death associated with drug overdose in Connecticut from 2012 to 2024. 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

Drug Induced Death reports the number and rate of drug-induced deaths. Dimensions Year,Measure Type,Variable Full Description Deaths in which drugs may have been a contributing but not primary cause are not included. The age-adjusted mortality rate (AAMR) controls for the impact of different age structures in order to better evaluate risk levels that are independent of the age composition of the population. Connecticut Department of Public Health collects data annually. CTdata.org carries three year aggregations of annual data.

From 1999 to 2023, the number of drug overdose deaths among U.S. females increased from ***** in 1999 to ****** in 2023. Globally, drug use is a general problem. As of 2021, there were an estimated *** million global drug consumers and **** million drug addicts. Opioid use in the United States Among many demographics, drug overdose deaths continue to rise in the United States. Opioids are the most commonly reported substance in drug-related deaths. The number of drug-related deaths in the U.S. due to opioids has dramatically increased since the early 2000s. In 2017, then-President Donald Trump declared a national emergency over the opioid crisis in the United States. Since then, there have been joint efforts among various governmental departments to address the opioid crisis through education and outreach. Substance use treatment Substance abuse treatment is vital in reducing the number of drug overdose deaths in the United States. As of 2020, the state of California had the largest number of substance abuse treatment facilities . However, many states in the U.S. have less than 100 substance abuse treatment facilities.

Data on drug overdose death rates, by drug type and selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Vital Statistics System, numerator data from annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics.2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This dataset presents drug overdose death rates in the United States, categorized by drug type, sex, age group, race, and Hispanic origin. It provides comprehensive statistics on mortality rates attributed to various drugs, offering insights into the impact across different demographic segments. The data enables detailed analysis of trends and disparities in drug-related fatalities, crucial for public health research, policy development, and intervention strategies aimed at reducing overdose deaths.

Format: CSV

A brief description of each column: INDICATOR: The specific indicator or metric being measured (e.g., drug overdose death rates). PANEL: Indicates the panel or group within which the data is categorized or reported. PANEL_NUM: Numeric identifier for the panel or group. UNIT: Unit of measurement for the data (e.g., rates per 100,000 population). UNIT_NUM: Numeric identifier for the unit of measurement. STUB_NAME: Name or identifier for the stub variable, typically related to demographic categories (e.g., drug type, sex, age, race, Hispanic origin). STUB_NAME_NUM: Numeric identifier for the stub variable. STUB_LABEL: Label or description corresponding to the stub variable. STUB_LABEL_NUM: Numeric identifier for the stub label. YEAR: Year of the data observation or reporting. YEAR_NUM: Numeric identifier for the year. AGE: Age group of the population (e.g., 0-17, 18-34, 35-54, 55+). AGE_NUM: Numeric identifier for the age group. ESTIMATE: The numerical estimate or value corresponding to the indicator being measured (e.g., death rate per 100,000 population).

This dataset appears to be structured to facilitate detailed analysis of drug overdose death rates across various demographic dimensions over multiple years, providing essential information for public health research and policy formulation.

Accidental Drug Related Deaths by Drug Type reports totals and subtotals of deaths attributable to accidental drug overdoses by place of death as reported by the Connecticut Office of the Chief Medical Examiner. Deaths are grouped by age, race, ethnicity, and gender and by the types of drugs detected post-death.

This 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

Deaths related to drug poisoning in England and Wales by cause of death, sex, age, substances involved in the death, geography and registration delay.

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Annual number of deaths in the United States from drug overdose per 100,000 people. Overdoses can result from intentional excessive use of a substance, but can also result from 'poisoning' where substances have been altered or mixed, such that the user is unaware of the drug's potency.

The data of this indicator is based on the following sources: US Centers for Disease Control and Prevention WONDER Data published by US Centers for Disease Control and Prevention WONDER

Retrieved from https://www.drugabuse.gov/related-topics/trends-statistics/overdose-death-rates How we process data at Our World in Data: All data and visualizations on Our World in Data rely on data sourced from one or several original data providers. Preparing this original data involves several processing steps. Depending on the data, this can include standardizing country names and world region definitions, converting units, calculating derived indicators such as per capita measures, as well as adding or adapting metadata such as the name or the description given to an indicator.

At the link below you can find a detailed description of the structure of our data pipeline, including links to all the code used to prepare data across Our World in Data.

Read about our data pipeline How to cite this data: In-line citation If you have limited space (e.g. in data visualizations), you can use this abbreviated in-line citation:

Any opioids Deaths per 100,000 people attributed to any opioids.

Source US Centers for Disease Control and Prevention WONDER – processed by Our World in Data Unit deaths per 100,000

Drug-induced deaths, including deaths due to medical narcotics, from 2011 to 2021 by sex, age, type of death, marital status, and educational attainment provided by Statistics Korea

Note on the data sets: 1) There will be initial issues with encoding so I used Chardet to fix this. Please use the below code in your notebooks:

import chardet # to help with encoding import numpy as np # linear algebra import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)

import os for dirname, _, filenames in os.walk('/kaggle/input'): for filename in filenames: print(os.path.join(dirname, filename))

with open('../input/drugrelated-deaths-in-scotland/drug-related-deaths-20-tabs-figs_1 - summary.csv', 'rb') as f: enc = chardet.detect(f.read()) opioid_data = pd.read_csv('../input/drugrelated-deaths-in-scotland/drug-related-deaths-20-tabs-figs_1 - summary.csv', encoding = enc['encoding'])

opioid_data.head(20)

2) There will need to be data cleaning due to the empty spaces in the data file. Running .head(20) will show this

The opioid epidemic is an international phenomenon. It began in the United States but has spread to other countries with similarly devastating effect. Here we have the drug-related deaths in Scotland, from the National Records of Scotland.

Here is the main data source https://www.nrscotland.gov.uk/statistics-and-data/statistics/statistics-by-theme/vital-events/deaths/drug-related-deaths-in-scotland/2020

Here is the news release on the drug-related deaths in 2020 with a 5% increase from 2019. Several key findings: - The number of drug-related deaths has increased substantially over the last 20 years – there were 4½ times as many deaths in 2020 compared with 2000. - Men were 2.7 times as likely to have a drug-related death than women, after adjusting for age. - After adjusting for age, people in the most deprived parts of the country were 18 times as likely to die from a drug-related death as those in the least deprived. - Scotland’s drug-death rate continues to be over 3½ times that for the UK as a whole, and higher than that of any European country. https://www.nrscotland.gov.uk/news/2021/drug-related-deaths-rise

These are similar patterns to what we see in the United States, with a rapid increase in the death rate over the past several decades, and hitting already struggling communities particularly hard.

Here are the key reports and analyses put out by the National Records of Scotland: - https://www.nrscotland.gov.uk/files//statistics/drug-related-deaths/20/drug-related-deaths-20-additional-analyses.pdf I'll highlight here: "one or more opiates or opioids (including heroin/morphine, methadone, codeine and dihydrocodeine) were implicated in 1, 192 drug-related deaths (89%)". So although Scotland's data set groups together all drug-related deaths, it is opioids in particular that are driving it. - and with graphs: https://www.nrscotland.gov.uk/files//statistics/drug-related-deaths/20/drug-related-deaths-20-pub.pdf

I previously published data sets on Opioids in the United States and Canada: https://www.kaggle.com/datasets/craigchilvers/opioids-vssr-provisional-drug-overdose-statistics https://www.kaggle.com/datasets/craigchilvers/opioids-in-the-us-cdc-drug-overdose-deaths https://www.kaggle.com/datasets/craigchilvers/opioids-in-the-us-cdc-nonfatal-overdoses https://www.kaggle.com/datasets/craigchilvers/opioids-in-canada