Predicting the Thermal and Allometric Dependencies of Disease Transmission via the Metabolic Theory of Ecology
Bibliographic record
Abstract
and a microsporidian gut parasite, we conducted two experiments across a wide thermal range and fitted transmission models that utilize MTE submodels for transmission parameters. We decomposed transmission into contact rate and probability of infection and further decomposed probability of infection into a product of gut residence time (GRT) and per-parasite infection rate of gut cells. Contact rate generally increased with temperature and scaled positively with body size, whereas infection rate had a narrow hump-shaped thermal response and scaled negatively with body size. GRT increased with host size and was longest at extreme temperatures. GRT and infection rate inside the gut combined to create a 3.5 times higher probability of infection for the smallest relative to the largest individuals. Small temperature changes caused large differences in transmission. We also fit several alternative transmission models to data at individual temperatures. The more complex models-parasite antagonism or synergism and host heterogeneity-did not substantially improve the fit to the data. Our results show that transmission rate is the product of several distinct thermal and allometric functions that can be predicted continuously across temperature and host size using the MTE.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".