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 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

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.

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

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.

The ongoing “fourth wave” of the U.S. overdose epidemic has been marked by rising deaths co-involving fentanyl with stimulants such as methamphetamine and cocaine. Using data obtained from the CDC WONDER Multiple Cause of Death database, this serial cross-sectional study analyzed stimulant overdose mortality trends between 1999 and 2023. We stratified crude mortality rates by sex, race and ethnicity, and opioid co-involvement. We used Joinpoint regression to examine temporal trends and estimate annual percentage changes (APC) within time segments. From 1999 to 2023, methamphetamine-involved overdose deaths increased from 547 to 34,855, with mortality rates rising from 0.20 (95% CI, 0.18–0.21) to 10.41 (95% CI, 10.30–10.52) per 100,000 (AAPC: 18.49% [95% CI, 17.67–20.17]; p 

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.

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

Actual and predicted rolling 12-month drug-overdose deaths per 100,000 persons over 2015-December 2021, divided into those related to synthetic opioids and other, and predicted overdose deaths in 2020 and through March 2021 for all overdoses and synthetic opioids overdoses using fourth order polynomial fitted to pre-pandemic data starting from either 2015 (2015 model) or 2017 (2017 model) through Feb. 2020.

IntroductionFentanyl is the leading cause of opioid-related overdose deaths in the United States. Given the exogenous market shock of fentanyl and subsequent transition in the illicit opioid supply, our analysis sought to explore the social and relational experiences of people who use opioids (PWUO).MethodsWe conducted qualitative interviews with 30 PWUO (n = 30) in Los Angeles, CA from July 2021 to April 2022. To be eligible for this study, participants had to report being 18 years of age or older and any self-reported opioid, cannabis, and injection drug use within the past 30 days. We used constructivist grounded theory to analyze the contexts that contribute to lived experiences surrounding opioid use behaviors within social networks.ResultsWithin an unpredictable drug market contaminated by fentanyl, participants reported: 1) avoiding opioid withdrawal symptoms by sharing financial and material resources within social networks, 2) securing and cultivating known, predictable social ties to prioritize safe/ safer supply of opioids, and 3) avoiding and mitigating risk of overdose fatality by using opioids within peer groups.ConclusionsOur findings emphasize that while peer support plays a critical role in safety within moral economies of PWUO, structural changes are needed to address the additional harms from an unregulated drug supply. Harm reduction interventions such as fentanyl test strip and naloxone distribution, as well as medication for opioid use disorders may improve safety. However, with a fentanyl-contaminated drug supply increasing risk for PWUO, safer opioid distribution of pharmaceutical-grade opioids and overdose prevention programs are needed to effectively address the burden of withdrawal, overdose, and fatality prevention within peer groups.

Number and percentage of deaths subject to an autopsy or not subject to an autopsy, 1991 to most recent year.

Model-based estimates for the proportion of non-COVID-19 excess deaths attributable to opioids.