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Record W7095719908

MODELING, DYNAMICS AND OPTIMAL CONTROL OF WEST NILE VIRUS WITH

2014· article· en· W7095719908 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Comparative Analysis Research
Canadian institutionsnot available
Fundersnot available
KeywordsOptimal controlTransmission (telecommunications)West Nile virusPopulationOrdinary differential equationEpidemic modelDynamics (music)Control (management)Bifurcation
DOInot available

Abstract

fetched live from OpenAlex

West Nile virus (WNv) is a mosquito-borne disease which arrived in Canada in 2001. It has kept spreading across the country and still remains a threat to public health. In this dissertation, we formulate dynamical models and apply theory of dynamical systems to investigate the behavior of the transmission of WNv in the mosquito-bird cycle and humans. In the first part, we propose a system of ordinary differential equations to model the role of corvids and non-corvids birds in the transmission of WNv in the mosquito-bird cycle in a single season and proved the existence of backward bifurcation in the model. In the second part, we consider another deterministic model to study the impact of seasonal variations of the mosquito population on the transmission dynamics of WNv. We prove the existence of periodic solutions under specific conditions. As for the third part, the latter model is extended to assess the impact of some anti-WNv control measures; by re-formulating the model as an optimal control problem. For mosquito-borne diseases, it is essential to access and forcast the virus risk. Therefore in the final part, we generalize the risk index, minimum infection rate (MIR) by using a compartment model for WNv,

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.969
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.045
GPT teacher head0.396
Teacher spread0.352 · 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 designSimulation or modeling
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

Citations0
Published2014
Admission routes1
Has abstractyes

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