Mpox Surveillance Based on Rash Characteristics — 13 Emergency Departments, United States, June–December 2023
Bibliographic record
Abstract
In 2022, a global mpox outbreak occurred, primarily affecting gay and bisexual men who have sex with men (GBMSM). To screen for mpox's reemergence and investigate potentially unsuspected cases among non-GBMSM, prospective surveillance of patients aged ≥3 months with an mpox-compatible rash (vesicular, pustular, ulcerated, or crusted) was conducted at 13 U.S. emergency departments (EDs) during June-December 2023. Demographic, historical, and illness characteristics were collected using questionnaires and electronic health records. Lesions were tested for monkeypox virus using polymerase chain reaction. Among 196 enrolled persons, the median age was 37.5 years (IQR = 21.0-53.5 years); 39 (19.9%) were aged <16 years, and 108 (55.1%) were male. Among all enrollees, 13 (6.6%) were GBMSM. Overall, approximately one half (46.4%) and one quarter (23.5%) of enrolled persons were non-Hispanic White and non-Hispanic Black or African American, respectively, and 38.8% reported Hispanic or Latino (Hispanic) ethnicity. Unstable housing was reported by 21 (10.7%) enrollees, and 24 (12.2%) lacked health insurance. The prevalence of mpox among ED patients evaluated for an mpox-compatible rash was 1.5% (95% CI = 0.3%-4.4%); all persons with a confirmed mpox diagnosis identified as GBMSM and reported being HIV-negative, not being vaccinated against mpox, and having engaged in sex with one or more partners met through smartphone dating applications. No cases were identified among women, children, or unhoused persons. Clinicians should remain vigilant for mpox and educate persons at risk for mpox about modifying behaviors that increase risk and the importance of receiving 2 appropriately spaced doses of JYNNEOS vaccine to prevent mpox.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".