Control of Predator Disease Dynamics Under Prey Refuge and Harvesting: A Fuzzy Computational Modeling Approach
Bibliographic record
Abstract
The control of infectious diseases plays a critical role in safeguarding the health of species and ecosystems. In this study, we investigate the combined effects of prey refuge and harvesting as mechanisms to limit the spread of disease within predator populations. A deterministic model is developed to examine the system dynamics through local stability analysis of equilibria, and the framework is further extended to an uncertain setting via a fuzzified model. The analysis shows that for small refuge values, the system reaches a stable state where infected predators move toward extinction, while prey and susceptible predators exhibit strong oscillations. As the refuge increases, the system undergoes a Hopf bifurcation, transitioning from periodic oscillations to a stable interior equilibrium. Beyond a critical threshold, oscillations disappear entirely. Harvesting of susceptible predators reveals that moderate harvesting induces oscillatory behavior in both prey and susceptible predator populations, whereas excessive harvesting can drive both predator classes to extinction. Harvesting of infected predators, by contrast, consistently drives their extinction regardless of harvesting intensity, with the other populations maintaining oscillatory patterns. These results indicate that an appropriate combination of prey refuge and harvesting can serve as an effective strategy for disease control in predator populations.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".