Relative host body condition and food availability influence epidemic dynamics: a<i>Poecilia reticulata-Gyrodactylus turnbulli</i>host-parasite model
Bibliographic record
Abstract
Understanding disease transmission is important to species management and human health. Host body condition, nutrition and disease susceptibility interact in a complex manner, and while the individual effects of these variables are well known, our understanding of how they interact and translate to population dynamics is limited. Our objective was to determine whether host relative body condition influences epidemic dynamics, and how this relationship is affected by food availability. Poecilia reticulata (guppies) of roughly similar size were selected and assembled randomly into populations of 10 guppies assigned to 3 different food availability treatments, and the relative condition index (Kn) of each fish was calculated. We infected 1 individual per group ('source' fish) with Gyrodactyus turnbulli and counted parasites on each fish every other day for 10 days. Epidemic parameters for each population were analysed using generalized linear models. High host Kn-particularly that of the 'source' fish-exerted a positive effect on incidence, peak parasite burden, and the degree of parasite aggregation. Low food availability increased the strength of the associations with peak burden and aggregation. Our findings suggest that host Kn and food availability interact to influence epidemic dynamics, and that the condition of the individual that brings the parasite into the host population has a profound impact on the spread of infection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".