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Record W4392751765 · doi:10.1007/s42452-024-05763-y

Analysis of the dynamics of anthrax epidemic model with delay

2024· article· en· W4392751765 on OpenAlexaff
Ali Raza, Kenzu Abdella

Bibliographic record

VenueDiscover Applied Sciences · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacillus and Francisella bacterial research
Canadian institutionsTrent University
Fundersnot available
KeywordsDynamics (music)Epidemic modelCoronavirus disease 2019 (COVID-19)Computer scienceGeographyMedicinePsychologyEnvironmental healthInfectious disease (medical specialty)Internal medicine

Abstract

fetched live from OpenAlex

Abstract Anthrax is a potentially fatal infectious zoonotic disease caused by the spore-forming bacterium Bacillus anthracis. While it is a disease of herbivores which primarily affects livestock and wildlife, it could also lead to serious and lethal infections in humans. Its large-scale outbreak could result in devastating economic impact related to losses in livestock and livestock products. Due to its ability to cause widespread disease and death, Anthrax has also become one of the numerous biological agents that is being considered in biowarfare and bioterrorism. Therefore, the modelling and analysis of Anthrax dynamics is crucial for the proper understanding of its prevention and control. In the present study, we investigate the nonlinear dynamics of Anthrax with delay effects which incorporates the mechanism of its incubation period. The sensitivity of the reproduction number dynamics with the model parameters is studied. The local and global stabilities of the model are studied. It is shown that the delay mechanism plays an important role in the dynamics of disease propagation.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.727
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.014
GPT teacher head0.281
Teacher spread0.267 · 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 designBench or experimental
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

Citations11
Published2024
Admission routes1
Has abstractyes

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