Estimated Number of Injection-Involved Overdose Deaths in US States From 2000 to 2020: Secondary Analysis of Surveillance Data
Notice bibliographique
Résumé
BACKGROUND: In the United States, both drug overdose mortality and injection-involved drug overdose mortality have increased nationally over the past 25 years. Despite documented geographic differences in overdose mortality and substances implicated in overdose mortality trends, injection-involved overdose mortality has not been summarized at a subnational level. OBJECTIVE: We aimed to estimate the annual number of injection-involved overdose deaths in each US state from 2000 to 2020. METHODS: We conducted a stratified analysis that used data from drug treatment admissions (Treatment Episodes Data Set-Admissions; TEDS-A) and the National Vital Statistics System (NVSS) to estimate state-specific percentages of reported drug overdose deaths that were injection-involved from 2000 to 2020. TEDS-A collects data on the route of administration and the type of substance used upon treatment admission. We used these data to calculate the percentage of reported injections for each drug type by demographic group (race or ethnicity, sex, and age group), year, and state. Additionally, using NVSS mortality data, the annual number of overdose deaths involving selected drug types was identified by the following specific multiple-cause-of-death codes: heroin or synthetic opioids other than methadone (T40.1, T40.4), natural or semisynthetic opioids and methadone (T40.2, T40.3), cocaine (T40.5), psychostimulants with abuse potential (T43.6), sedatives (T42.3, T42.4), and others (T36-T59.0). We used the probabilities of injection with the annual number of overdose deaths, by year, primary substance, and demographic groups to estimate the number of overdose deaths that were injection-involved. RESULTS: In 2020, there were 91,071 overdose deaths among adults recorded in the United States, and 93.1% (84,753/91,071) occurred in the 46 jurisdictions that reported data to TEDS-A. Slightly less than half (38,253/84,753, 45.1%; 95% CI 41.1%-49.8%) of those overdose deaths were estimated to be injection-involved, translating to 38,253 (95% CI 34,839-42,181) injection-involved overdose deaths in 2020. There was large variation among states in the estimated injection-involved overdose death rate (median 14.72, range 5.45-31.77 per 100,000 people). The national injection-involved overdose death rate increased by 323% (95% CI 255%-391%) from 2010 (3.78, 95% CI 3.33-4.31) to 2020 (15.97, 95% CI 14.55-17.61). States in which the estimated injection-involved overdose death rate increased faster than the national average were disproportionately concentrated in the Northeast region. CONCLUSIONS: Although overdose mortality and injection-involved overdose mortality have increased dramatically across the country, these trends have been more pronounced in some regions. A better understanding of state-level trends in injection-involved mortality can inform the prioritization of public health strategies that aim to reduce overdose mortality and prevent downstream consequences of injection drug use.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,011 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,005 | 0,004 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».