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

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.

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 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.

Prior dataset name - Estimated Accidental and Undetermined Drug Overdose Deaths CY 2012-Current County Health
View annual counts of Any Drug overdose deaths for 2012 forward, including provisional estimates of annual counts of overdose deaths for recent years, as noted with an asterisk and the month the data was pulled. NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9. Counts do not include suicides or homicides where someone intended to harm another person by poisoning.
Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Drug-poisoning deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include the following:
- R99 when the Injury Description indicates an overdose death.
- X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses
- X47 when substance indicated is difluoroethane, alone or in combination with other drugs
- X85 when it does not appear that someone intended to harm another person by poisoning
Source Office of Drug Surveillance and Misuse Prevention*
* These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions.
Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths

View annual counts of Accidental or Undetermined overdose deaths for 2012 forward, including provisional estimates of annual counts of overdose deaths for recent years, as noted with an asterisk and the month the data was pulled. NOTE: Finalized death records for overdose deaths are often delayed by 3-6 months. Counties labeled “no value” have data suppressed because the counts are between 1 and 9. Dataset includes overdose deaths where the Manner of Death is Accidental or Undetermined. County complement counts file located here - https://data.pa.gov/Opioid-Related/Estimated-Accidental-and-Undetermined-Drug-Overdos/azzc-q64m Overdose Deaths are classified using the International Classification of Diseases, Tenth Revision (ICD–10). Accidental and Undetermined drug overdose deaths are identified using underlying cause-of-death codes X40–X44, and Y10–Y14, and include - R99 when the Injury Description indicates an overdose death. - X49 when literal COD is Mixed or Combined or Multiple Substance Toxicity, as these are likely drug overdoses - X47 when substance indicated is difluoroethane, alone or in combination with other drugs Source Pennsylvania Prescription Drug Monitoring Program * * These data were supplied by the Bureau of Health Statistics and Registries, Harrisburg, Pennsylvania. The Bureau of Health Statistics and Registries specifically disclaims responsibility for any analyses, interpretations or conclusions. - Estimates are broken down by type of drugs involved in the overdose - Any Drug Overdose Death - all drug overdose deaths, regardless of type of drug involved, excluding alcohol only deaths - Opioid Overdose Death - any overdose death involving opioids, prescription or illegal

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

Life expectancy at birth, at the health region level, is decomposed by drug overdose deaths. Changes in mortality rates for a given cause of death change over time and contribute to the overall change in life expectancy.

To: State, territorial, tribal, and local policymakers and administrators of agencies and programs focused on child, youth, and family health and well-being

Dear Colleagues,

Thank you for your work to support children, youth, and families. Populations served by Administration for Children and Families (ACF)-funded programs — including victims of trafficking or violence, those who are unhoused, and young people and families involved in the child welfare system — are often at particularly high risk for substance use and overdose. A variety of efforts are underway at the federal, state, and local levels to reduce overdose deaths. These efforts focus on stopping drugs from entering communities, providing life-saving resources, and preventing drug use before it starts. Initiatives across the country are already saving lives: the overdose death rate has declined over the past year but remains too high at 32.6 per 100,000 individuals.

Fentanyl, a powerful synthetic opioid, raises the risk of overdose deaths because even a tiny amount can be deadly. Young people are particularly at risk for fentanyl exposure, driven in part by widespread availability of counterfeit pills containing fentanyl that are marketed to youth through social media. While overdose deaths among teens have recently begun to decline, there were 6,696 deaths among adolescents and young adults in 2022 (the latest year with data available)[1], making unintentional drug overdose the second leading cause of death for youth ages 15—19 and the first leading cause of death among young adults ages 20-24.[2]

Often these deaths happen with others nearby and can be prevented when opioid overdose reversal medications, like naloxone, are administered in time. CDC’s State Unintentional Drug Overdose Reporting System dashboard shows that in all 30 jurisdictions with available data, 64.7% of drug overdose deaths had at least one potential opportunity for intervention.[3] Naloxone rapidly reverses an overdose and should be given to any person who shows signs of an opioid overdose or when an overdose is suspected. It can be given as a nasal spray. Studies show that naloxone administration reduces death rates and does not cause harm if used on a person who is not overdosing on opioids. States have different policies and regulations regarding naloxone distribution and administration. Forty-nine states and the District of Columbia have Good Samaritan laws protecting bystanders who aid at the scene of an overdose.[4]

ACF grant recipients and partners can play a critical role in reducing overdose deaths by taking the following actions:

Stop Overdose Now

(U.S. Centers for Disease Control and Prevention)

Integrating Harm Reduction Strategies into Services and Supports for Young Adults Experiencing Homelessness (PDF) (ACF)

Thank you for your dedication and partnership. If you have any questions, please contact your local public health department or state behavioral health agency. Together, we can meaningfully reduce overdose deaths in every community.

/s/

Meg Sullivan

Principal Deputy Assistant Secretary

[1] Products - Data Briefs - Number 491 - March 2024

[2] WISQARS Leading Causes of Death Visualization Tool

[3] SUDORS Dashboard: Fatal Drug Overdose Data | Overdose Prevention | CDC

[4] Based on 2024 report from the Legislative Analysis and Public Policy Association

(PDF). Note that the state of Kansas adopted protections as well following the publication of this report.

Metadata-only record linking to the original dataset. Open original dataset below.

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).

Source: Office of State Medical Examiners (OSME), Rhode Island Department of Health (RIDOH)Note: Counts may not add to annual totals due to missing case information. Percentages may not add to 100 due to rounding. Percentages are displayed as decimals. Prescription medications include prescription opioids such as oxycodone, hydrocodone, and benzodiazepines. Illicit drugs include substances such as heroin, illicit fentanyl, and cocaine.

These data show total annual Maryland drug intoxication deaths from 2007 to 2016, broken down by substance. Since an intoxication death may involve more than one substance, counts of deaths related to specific substances do not sum to the total number of deaths. Benzodiazepine deaths include deaths caused by benzodiazepines and related drugs with similar sedative effects.

Fatal drug overdoses have involved both xylazine and fentanyl. Xylazine is a non-opioid substance used in veterinary medicine. This study aimed to model changes in fatal xylazine-involved drug overdose deaths from 2019 to 2023 in Connecticut using overdose death data from the Office of the Chief Medical Examiner. Xylazine-involved drug overdose fatality rates were calculated by number of deaths per year per 100,000 population from 2019 to 2023. We used joinpoint regression modeling to evaluate quarterly overdose rates across age, number of drugs, and drug types with a significance level of p 

This dataset presents the age-standardised mortality rate from drug misuse across the population. It captures deaths where the underlying cause is linked to mental and behavioural disorders due to psychoactive substance use (excluding alcohol, tobacco, and volatile solvents), as well as deaths involving poisoning by controlled drugs. The data is sourced from the Office for National Statistics (ONS) and is intended to support public health monitoring and policy development aimed at reducing drug-related harm.

Rationale The indicator is designed to track and reduce the mortality rate from drug misuse. Monitoring these deaths helps inform public health strategies, resource allocation, and interventions aimed at preventing drug-related harm and supporting individuals with substance use disorders.

Numerator The numerator includes deaths where the underlying cause is coded to specific categories of mental and behavioural disorders due to psychoactive substance use (excluding alcohol, tobacco, and volatile solvents), as well as deaths involving poisoning by drugs controlled under the Misuse of Drugs Act 1971. These include accidental, intentional, undetermined, and assault-related poisonings, as well as disorders due to volatile solvents.

Denominator The denominator is the total population of the relevant age group, as recorded in the 2021 Census.

Caveats There are limitations in the classification and reporting of drug-related deaths, including potential underreporting or misclassification in death records. The indicator may not capture all deaths indirectly related to drug misuse, and changes in coding practices or legal definitions over time may affect comparability.

External references Public Health England - Fingertips: Deaths from drug misuse

Click here to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.

Introduction: The recreational use of fentanyl in combination with xylazine (i.e., “tranq-dope”) represents a rapidly emerging public health threat characterized by significant toxicity and mortality. This study quantified the interactions between these drugs on lethality and examined the effectiveness of potential rescue medications to prevent a lethal overdose.Methods: Male and female mice were administered acute doses of fentanyl, xylazine, or their combination via intraperitoneal injection, and lethality was determined 0.5, 1.0, 1.5, 2.0, and 24 h after administration. Both fentanyl and xylazine produced dose-dependent increases in lethality when administered alone.Results: A nonlethal dose of fentanyl (56 mg/kg) produced an approximately 5-fold decrease in the estimated LD50 for xylazine (i.e., the dose estimated to produce lethality in 50% of the population). Notably, a nonlethal dose of xylazine (100 mg/kg) produced an approximately 100-fold decrease in the estimated LD50 for fentanyl. Both drug combinations produced a synergistic interaction as determined via isobolographic analysis. The opioid receptor antagonist, naloxone (3 mg/kg), but not the alpha-2 adrenergic receptor antagonist, yohimbine (3 mg/kg), significantly decreased the lethality of a fentanyl-xylazine combination. Lethality was rapid, with death occurring within 10 min after a high dose combination and generally within 30 min at lower dose combinations. Males were more sensitive to the lethal effects of fentanyl-xylazine combinations under some conditions suggesting biologically relevant sex differences in sensitivity to fentanyl-xylazine lethality.Discussion: These data provide the first quantification of the lethal effects of “tranq-dope” and suggest that rapid administration of naloxone may be effective at preventing death following overdose.

Date Created: November 2023Update Frequency: WeeklyLast Reviewed: November 2023Accuracy, Completeness, and Known Issues: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. Data Steward: OPH Epidemiology TeamData Steward Email: oph-epidemiology@ottawa.caDepartment or Agency: Ottawa Public HealthBranch/Unit: Epidemiology and Evidence

This dataset contains mortality statistics for opioid drugs poisoning in the US at state level starting from 2013 to 2016. The indicators used crude and age-adjusted mortality. At the same time it contains data about the number of deaths and the increase of the number, along with statistical significance (for a probability level of 95%) of increase between the years.

The Drug-Involved Mortality (DIM) data are an enhancement to the National Vital Statistics System, Mortality data providing information on substances, as well as prescription (using generic names only – no trademarks) and illicit drugs mentioned on death certificates of residents of the United States and the District of Columbia. Data files were created by examining the literal text of three fields on the death certificate: Part I-Cause of Death, Part II –Significant Conditions Contributing to Death and Box 43, a verbatim description of how the injury occurred. The DIM data system does not support individual examination of “literal text” and the actual variables showing free-form text are not included in these files.

Severe adverse drug reactions (ADRs) are the fourth leading cause of fatality in the U.S. with more than 100 000 deaths per year. As up to 30% of all ADRs are believed to be caused by drug–drug interactions (DDIs), typically mediated by cytochrome P450s, possibilities to predict DDIs from existing knowledge are important. We collected data from public sources on 1485, 2628, 4371, and 27 966 possible DDIs mediated by four cytochrome P450 isoforms 1A2, 2C9, 2D6, and 3A4 for 55, 73, 94, and 237 drugs, respectively. For each of these data sets, we developed and validated QSAR models for the prediction of DDIs. As a unique feature of our approach, the interacting drug pairs were represented as binary chemical mixtures in a 1:1 ratio. We used two types of chemical descriptors: quantitative neighborhoods of atoms (QNA) and simplex descriptors. Radial basis functions with self-consistent regression (RBF-SCR) and random forest (RF) were utilized to build QSAR models predicting the likelihood of DDIs for any pair of drug molecules. Our models showed balanced accuracy of 72–79% for the external test sets with a coverage of 81.36–100% when a conservative threshold for the model’s applicability domain was applied. We generated virtually all possible binary combinations of marketed drugs and employed our models to identify drug pairs predicted to be instances of DDI. More than 4500 of these predicted DDIs that were not found in our training sets were confirmed by data from the DrugBank database.