The first case of Mpox infection in Iran during the 2022 outbreak
Bibliographic record
Abstract
INTRODUCTION: The unexpected outbreak of human Mpox infection beginning in some European countries that were non-endemic for Mpox stunned the world during the Coronavirus Disease 2019 (COVID-19) pandemic in May 2022. The re-emerging Mpox outbreak, which has a greater capacity for human-to-human transmission, was mainly due to traveling. In this paper, we describe the first case of the disease was observed in an Iranian woman infected by her husband who had a history of traveling to Canada. CASE REPORT: The 34-year-old woman had flu-like syndrome with some skin rashes on her hand, finger, and arm. No antivirals were prescribed in this case, and supportive care was used to help her recover. RT-PCR and Sanger sequencing were used to analyze the sample from the oropharyngeal swab and the rash, and the results confirmed the Mpox infection. CONCLUSIONS: The risk of infectious disease outbreaks after COVID-19, such as Mpox, is of great importance, and health systems should be vigilant for timely identification and preparedness.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".