Why the Jenner/Pasteur paradigm is insufficient for controlling vector-borne diseases and the role of microbiota-mediated interactions
Bibliographic record
Abstract
Vaccination campaigns have profoundly influenced the dynamics of infectious diseases, acting as one of the largest ecological experiments in history. By vaccinating billions across decades, we have imposed powerful selective pressures on pathogens, illuminating their ability to adapt, evade, or persist. Rooted in the Jenner/Pasteur paradigm - where exposure to an antigen induces protective immunity - vaccines have revealed how pathogens differ in their ecological susceptibility to immunity. Using this framework, pathogens can be categorized based on their strategies to endure, from those limited by direct immunity to those relying on antigenic variation, chronic infection, or reservoirs. Vector-borne pathogens (VBPs) present a set of challenges to vaccination efforts due to their complex life cycles, stage-specific antigen expression, and reliance on arthropod vectors for transmission. These pathogens not only evade host immunity but also adapt to selective pressures within the vector's microbiome and immune system. Such complexity often places VBPs beyond the scope of traditional vaccine paradigms, requiring alternative strategies such as transmission-blocking and vector-targeted vaccines. This review explores these insights, examining the interplay between vaccination, pathogen ecology, and evolution - with special emphasis on VBPs - to guide future strategies in vector-borne disease (VBD) control.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".