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Record W2800055480 · doi:10.1111/zph.12469

Crimean–Congo haemorrhagic fever virus: Past, present and future insights for animal modelling and medical countermeasures

2018· review· en· W2800055480 on OpenAlexaff
Emely Julieth Cedeño Mendoza, Bryce M. Warner, David Safronetz, Charlene Ranadheera

Bibliographic record

VenueZoonoses and Public Health · 2018
Typereview
Languageen
FieldMedicine
TopicViral Infections and Vectors
Canadian institutionsUniversity of ManitobaPublic Health Agency of Canada
Fundersnot available
KeywordsZoonosisCase fatality rateCrimean–Congo hemorrhagic feverTickVirologyTick-borne diseaseMedicineDiseaseIntensive care medicineImmunologyBiologyEpidemiologyInternal medicine

Abstract

fetched live from OpenAlex

Crimean-Congo haemorrhagic fever (CCHF) is a widespread tick-borne viral zoonosis with a case-fatality rate ranging from 9% to 50% in humans. Although a licensed vaccine to prevent infection by the CCHF virus (CCHFV) exists, its ability to induce neutralizing antibodies is limited and its efficacy against CCHFV remains undetermined. In addition, controlling CCHF infections by eradication of the tick reservoir has been ineffective, both economically and logistically, and the treatment options for CCHF remain limited. In this review, we first critically discuss the existing animal models to evaluate therapeutics for CCHF. We then review the therapeutic options for CCHF that have been investigated in human cases, followed by investigational drugs that have been evaluated in pre-clinical studies. We highlight the importance of understanding human prognostic factors in developing an animal model for CCHF that recapitulates hallmarks of human disease and its implication for selecting therapeutic candidates.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.146
GPT teacher head0.389
Teacher spread0.244 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations31
Published2018
Admission routes1
Has abstractyes

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