Virulence and Vertically Transmitted Pathogens: The Role of Costs Paid by Co‐Evolving Hosts in a Self‐Regulating Population
Bibliographic record
Abstract
Many pathogens transmit horizontally through usual routes and vertically from parent to offspring. Co-evolution is predicted, under certain circumstances, to produce a positive relationship between host-pathogen antagonism and the rate of vertical transmission. We cannot disentangle the roles of host demographics and the costs of host immune function in establishing this pattern. On one hand, models that assume no density-dependent growth of host populations and limit the cost of immune function to infected hosts only predict that the positive relationship is possible. On the other hand, models that assume density-dependent growth of host populations and impose the cost of immune function on all hosts, regardless of infection status, suggest that the positive relationship is not possible. Here, we seek to resolve the confusion. We model the co-evolution of a host and its pathogen when the latter can transmit both vertically and horizontally. We assume host population growth is self-limiting, and we impose the cost of immune function only on infected hosts. We find that a positive relationship between host-pathogen antagonism and vertical transmission is possible under our assumptions. Our finding points to the critical role played by assumptions about when hosts pay the cost of immune function. We also find that the combination of density-dependent host population growth and the cost-free lifestyle of uninfected hosts raises the possibility of selection-driven pathogen extinction. We discuss our findings in relation to previous theory and empirical findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".