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.

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

This dashboard provides in-depth analysis surrounding events and characteristics of individuals who experienced non-fatal and/or fatal opioid overdoses in the District of Columbia. It includes data on ambulance transports for overdoses, fatalities, naloxone distribution, harm reduction efforts and the results of our used syringe testing. Data is aggregated at the neighborhood and ward levels. Data on fatal opioid overdoses will include deaths from 2021-2024. Data on non-fatal opioid overdoses will include incidents from 2021-2024. Note: Fatal opioid overdose data are delayed by approximately 90 days due to toxicological testing.

This data presents counts of provisional drug overdose deaths by selected drugs and U.S. Department of Health and Human Services (HHS) public health regions, based on provisional mortality data from the National Vital Statistics System. This data is limited to drug overdose deaths with an underlying cause of death assigned to International Statistical Classification of Diseases, 10th Revision (ICD-10) code numbers X40-X44 (unintentional), X60-X64 (suicide), X85 (homicide), or Y10-Y14 (undetermined intent). Specific drugs were identified using methods for searching literal text from death certificates.

The provisional data are based on a current flow of mortality data and include reported 12 month-ending provisional counts of drug overdose deaths by jurisdiction of occurrence and specified drug. Provisional drug overdose death counts presented on this page 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 2022 would include deaths occurring from July 1, 2021, through June 30, 2022. Evaluation of trends over time should compare estimates from year to year (June 2021 and June 2022), rather than month to month, to avoid overlapping time periods. It is important to note that the data represent counts of deaths, and not mortality ratios or rates, which are the standard measure used to compare groups, and therefore should not be used to determine populations at disproportionate risk of drug overdose death.

This dashboard provides in-depth analysis surrounding events and characteristics of individuals who experienced non-fatal and/or fatal opioid overdoses in the District of Columbia. It includes data on ambulance transports for overdoses, fatalities, naloxone distribution, harm reduction efforts and the results of our used syringe testing. Data is aggregated at the neighborhood and ward levels. Data on fatal opioid overdoses will include deaths from 2021-2024. Data on non-fatal opioid overdoses will include incidents from 2021-2024. Note: Fatal opioid overdose data are delayed by approximately 90 days due to toxicological testing.

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

A. SUMMARY This dataset comes from the San Francisco Emergency Medical Services Agency and includes all opioid overdose-related 911 calls responded to by emergency medical services (ambulances). The purpose of this dataset is to show how many opioid overdose-related 911 calls the San Francisco Fire Department and other ambulance companies respond to each week. This dataset is based on ambulance patient care records and not 911 calls for service data. B. HOW THE DATASET IS CREATED The San Francisco Fire Department and other ambulance companies send electronic patient care reports to the California Emergency Medical Services Agency for all 911 calls they respond to. The San Francisco Emergency Medical Services Agency (SF EMSA) has access to the state database that includes all reports for 911 calls in San Francisco County. In order to identify overdose-related calls that resulted in an emergency medical service (or ambulance) response, SF EMSA filters the patient care reports based on set criteria used in other jurisdictions called The Rhode Island Criteria. These criteria filter calls to only include those calls where EMS documented that an opioid overdose was involved and/or naloxone (Narcan) was administered. Calls that do not involve an opioid overdose are filtered out of the dataset. Calls that result in a patient death on scene are also filtered out of the dataset. This dataset is created by copying the total number of calls each week when the state makes this data available. C. UPDATE PROCESS Data is generally available with a 24-hour lag on a weekly frequency but the exact lag and update frequency is based on when the State makes this data available. D. HOW TO USE THIS DATASET This dataset includes the total number of calls a week. The week starts on a Sunday and ends on the following Saturday. This dataset will not match the Fire Department Calls for Service dataset, as this dataset has been filtered to include only opioid overdose-related 911 calls based on electronic patient care report data. Additionally, the Fire Department Calls for Service data are primarily based on 911 call data (i.e. calls triaged and recorded by San Francisco’s 911 call center) and not the finalized electronic patient care reports recorded by Fire Department paramedics. E. RELATED DATASETS Fire Department Calls for Service San Francisco Department of Public Health Substance Use Services Unintentional Overdose Death Rates by Race/Ethnicity Preliminary Unintentional Drug Overdose Deaths F. CHANGE LOG 1/17/2024 - updated date/time fields from Coordinated Universal Time (UTC) to Pacific Time (PT) which caused a slight change in historic case counts by week.

Accuracy: Data are from the "Weekly Update on Suspect Drug-Related Deaths in Ontario, by PHU Region" published weekly by the OCCO. Data are preliminary and subject to change.Suspect-drug related deaths include deaths where the preliminary investigation by the investigating coroner indicated: drugs were found at the scene, substance use equipment found at the scene, history of drug abuse, history of naloxone use, physical sign of drug use, positional asphyxia, unresponsive with snoring prior to death, or preliminary findings from autopsy indicate a suspected drug intoxication.Suspect-drug related deaths exclude deaths associated with trauma and medical assistance in dying cases. Investigations of suspect-drug related deaths may take several months, with identification of a number of death types, including: (1) opioid; (2) non-opioid acute drug toxicity, or (3) natural deaths (e.g., cardiac events), with different manners of death (natural, suicide, accident).When deaths initially thought to be drug related are determined to be natural deaths, this death is not removed from the preliminary suspected drug related death count to maintain comparable baseline data for the most recent months. Geographic regions are assigned based primarily on location of incident, however due to delays in data entry, may not yet be assigned for some recent deaths. Update Frequency: Weekly

Attributes:Week Starting on Monday – first date of the week, starting on Monday and ending on Sunday, when the death occurred. Number of suspected drug overdose deaths in Ottawa – number of suspected drug overdose deaths that occurred in Ottawa Contact: Ottawa Public Health Epidemiology Team

For those interested in data on student drug addiction in 2024, several sources offer valuable datasets and statistics.

1. Kaggle Dataset: Kaggle hosts a specific dataset on student drug addiction. This dataset includes various attributes related to student demographics, substance use patterns, and associated behavioral factors. It's a useful resource for data analysis and machine learning projects focused on understanding drug addiction among students【5†source】.

2. National Survey on Drug Use and Health (NSDUH): This comprehensive survey provides detailed annual data on substance use and mental health across the United States, including among students. It covers a wide range of substances and demographic details, helping to track trends and the need for treatment services【6†source】【8†source】.

3. Monitoring the Future (MTF) Survey: Conducted by the National Institute on Drug Abuse (NIDA), this survey tracks drug and alcohol use and attitudes among American adolescents. It provides annual updates and is an excellent source for understanding trends in substance use among high school and college students【7†source】.

4. Australian Institute of Health and Welfare (AIHW): For those interested in a more global perspective, the AIHW offers data from the National Drug Strategy Household Survey, which includes information on youth and young adult drug use in Australia. This can be useful for comparative studies【10†source】.

For detailed datasets and further analysis, you can explore these resources directly:

• Kaggle Student Drugs Addiction Dataset
• NSDUH Data
• Monitoring the Future
• AIHW Drug Survey

Overview

This dataset contains the number of yearly deaths due to Unintentional Drug Overdoses in the United States at a County Level between 2003-2015. To overcome the limitation of the original dataset, it is merged with population dataset to identify missing combinations and imputation is performed on the dataset taking into account the logical rules of the source dataset. Users can decide the proportion of the imputed values in the dataset by using the provided population and… See the full description on the dataset page: https://huggingface.co/datasets/revanth7667/usa_opioid_overdose.

This dataset is deprecated and will be removed by the end of the calendar year 2024. Updated on 8/18/2024

Drug and alcohol-related Intoxication death data is prepared using drug and alcohol intoxication data housed in a registry developed and maintained by the Vital Statistics Administration (VSA) of the Maryland Department of Health and Mental Hygiene (DHMH). The methodology for reporting on drug-related intoxication deaths in Maryland was developed by VSA with assistance from the DHMH Alcohol and Drug Abuse Administration, the Office of the Chief Medical Examiner (OCME) and the Maryland Poison Control Center. Assistance was also provided by authors of a 2008 Baltimore City Health Department report on intoxication deaths. Data in this table is by incident location, where the death occurred, rather than by county of residence.

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.

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

This data package includes the underlying data to replicate the charts, tables, and calculations presented in Stopping the flow: The effects of US-China cooperation on fentanyl markets and overdose deaths, PIIE Working Paper 25-9.

If you use the data, please cite as:

Noland, Marcus, Julieta Contreras, and Lucas Rengifo-Keller. 2025. Stopping the flow: The effects of US-China cooperation on fentanyl markets and overdose deaths. PIIE Working Paper 25-9. Washington: Peterson Institute for International Economics.

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

This dataset is deprecated and will be removed by the end of the calendar year 2024. Updated on 8/18/2024

Data sources: heroin overdose deaths/infant mortality-Vital Statistics Administration; lead-Medicaid; HIV diagnoses-Prevention and Health Promotion Administration; and immunizations-National Immunization Survey.

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.

Dataset - Diseases in the news

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

La mortalità legata alla droga è un fenomeno complesso, che rappresenta una percentuale considerevole di decessi tra i giovani in molti paesi europei. L'OEDT, in collaborazione con esperti nazionali, ha definito un indicatore epidemiologico composto attualmente da due componenti: decessi causati direttamente da droghe illegali (morti indotte da droghe) e tassi di mortalità tra i tossicodipendenti problematici. Queste due componenti possono soddisfare diversi obiettivi di salute pubblica, in particolare come indicatore dell'impatto complessivo sulla salute del consumo di droghe e delle componenti di tale impatto, individuare modelli di consumo particolarmente rischiosi e potenzialmente individuare nuovi rischi.

Ci sono circa 50 tabelle statistiche in questo set di dati. Ogni tabella dati può essere vista come una tabella HTML o scaricata in un foglio di calcolo (formato Excel).