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Record W4403576507 · doi:10.3855/jidc.18589

The first case of Mpox infection in Iran during the 2022 outbreak

2024· article· en· W4403576507 on OpenAlexaboutno aff
Ali Maleki, Arash Arashkia, Mohammad Hassan Pouriayevali, Tahmineh Jalali, Mahsa Tavakoli, mohammad modoodi yaghooti, Farideh Niknam Oskouei, Zahra Fereydouni, Kayhan Azadmanesh, Mostafa Salehi-Vaziri, Mahdi Rohani

Bibliographic record

VenueThe Journal of Infection in Developing Countries · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicPoxvirus research and outbreaks
Canadian institutionsnot available
FundersPasteur Institute of Iran
KeywordsOutbreakRashPreparednessTransmission (telecommunications)PandemicMedicineDiseaseInfectious disease (medical specialty)Emerging infectious diseaseVirologyCoronavirus disease 2019 (COVID-19)DermatologyInternal medicinePolitical science

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.251
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.014
GPT teacher head0.282
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2024
Admission routes1
Has abstractyes

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