MODELING, DYNAMICS AND OPTIMAL CONTROL OF WEST NILE VIRUS WITH
Bibliographic record
Abstract
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,
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".