Pandemic meets epidemic: Co-location of COVID-19 and drug overdose deaths in the United States
Bibliographic record
Abstract
Drug overdose deaths (DOD) in the last two decades have increased over 300 percent. In 2019 alone, 71,000 deaths represented a 7% increase from the previous year. According to recent data released by the Center for Disease Control and Prevention (CDC), 81,230 overdose deaths occurred in the United States from June 2019 to May 2020, the highest number of DOD recorded in a 12-month period. Early 2020 saw the spread of the COVID-19 pandemic in the United States, which CDC suggests has amplified the previously alarming rise in drug-related mortalities. A hot spot analysis of COVID-19 and DOD rates, as well as a spatial correlation between the two datasets at the state level on a monthly time step, showed a significant increase in DOD during the COVID-19 pandemic. This study, conducted for the period of March through July 2021, showed a spatial correlation between the two types of mortalities in the initial months of 2020. Furthermore, the hot spots for both types of mortalities were concentrated in the northeastern states. The COVID-19 mortalities shifted southeast in July 2020, but DOD data was unavailable for further analysis. Since DOD are a leading contributor to preventable deaths, the results of the study may help focus the efforts of effective and innovative programs to reduce substance use disorder and related mortality through increased access to treatment. During the pandemic, access to such facilities was reduced.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".